JP4814820B2 - Image forming apparatus, image forming method, and image forming program - Google Patents

Description

  The present invention relates to an image forming apparatus, an image forming method, and an image forming program, and more particularly, to an image forming apparatus, an image forming method, and an image forming program for realizing highly accurate gradation correction.

  Conventionally, as represented by a laser printer or the like, in an image forming apparatus in which pixels (dots) of a minimum printing unit are quantized into two states of ON / OFF, when expressing an intermediate density, per unit area Image processing called gradation processing that performs intermediate density expression by changing the area ratio of ON pixels is used.

  Here, in the gradation processing described above, for example, by combining a plurality of pixels, halftone processing that simulates halftone dots whose area changes according to the input gradation, and the area ratio of ON dots is set. There is an error diffusion process that increases uniformly, but in the case of a laser printer or the like in which the reproduction of one pixel is unstable, the former halftone process tends to be used preferably.

  Furthermore, when the number of gradations is insufficient only by halftone gradation processing, PWM (Pulse-Width Modulation) that increases the number of gradations by subdividing the laser pulse for one pixel is used in combination. In some cases. Note that a method for realizing halftone processing using PWM is already disclosed (see, for example, Patent Document 1).

  In the halftone processing, the halftone density is called the number of lines, and is expressed by the number of halftone dots per 25.4 mm (1 inch). For example, in a printer having a resolution of 600 pixels per 25.4 mm (600 dpi) and a halftone dot composed of 16 pixels of 4 × 4 in the vertical and horizontal directions, the number of lines of the halftone dot is expressed as 150 lpi.

  In a normal color printer, the number of lines of each color to be used is set to be approximately the same. However, in order to reduce moire caused by color superposition, a different angle (screen angle) is provided in the arrangement direction of halftone dots for each color plane, so the number of lines for each color is slightly different.

  On the other hand, the basic area of one pixel is designed to be strictly larger than one pixel so that the solid image covers the entire area. This fat portion of the pixel (dot) is called dot gain. Since the dot gain changes slightly depending on the new and old conditions of the device and the environmental conditions of temperature and humidity, the halftone dots with a higher number of lines are more significantly affected by the dot gain, and the density gradation characteristics with respect to the input value change more sensitively. Will do. For this reason, the higher the number of halftone dots, the higher the resolution, but at the expense of gradation and stability. Conversely, the lower the number of halftone lines, the lower the resolution, but the higher the gradation and stability. There is a tendency.

  Due to the difference in gradation characteristics due to the number of halftone lines, there are originals mainly composed of photographic images where gradation is more important than resolution, and text / line drawings where resolution is more important than gradation. The appropriate number of lines for halftone processing differs depending on the original document. Further, even if it is a photographic image, it is required to output it with a high number of lines as much as possible when importance is attached to the resolution.

  In order to meet these requirements, color printers and the like tend to be able to select combinations of a plurality of lines. On the other hand, since the dot gain described above is affected by a subtle characteristic difference of the printer engine, it is necessary to calibrate gradation characteristics in order to always obtain a constant image reproduction.

  However, when calibration is performed on the total number of halftone lines supported, problems such as an increase in time and labor required for calibration, and confusion in operation by the user occur. For this reason, various methods have been disclosed for the purpose of reducing the number of calibration steps with respect to the number of gradation processes supported (see, for example, Patent Documents 2 to 5).

  For example, in Patent Document 2, the gradation characteristics of a pattern having a large gradation width (2 × 2 halftone dots) are corrected, and the gradation characteristics of a pattern halftone having a narrow gradation width (1 × 1 halftone dot) are estimated. Thus, a technique for reducing the calibration man-hour is disclosed.

  Further, Patent Document 3 discloses a method of performing gradation characteristic calibration in accordance with gradation processing appropriate for each of copying of a normal document and re-copying of a copied document by reading a reference document once. Yes. Japanese Patent Application Laid-Open No. 2004-228561 discloses a technique that supports various types of gradation processing by automatically dividing a calibration patch area.

Further, Patent Document 5 provides user calibration performed by a user using a test chart and engine calibration performed while the printer engine unit is in operation, and the user calibration targets only image processing that emphasizes gradation. Thus, a technique for reducing the number of user calibration steps is disclosed.
Japanese Patent No. 3801364 Japanese Patent No. 3738346 Japanese Patent No. 3734675 JP 2002-374416 A JP 2002-300309 A

  In the conventional technique as described above, for example, the technique disclosed in Patent Document 2 discloses an example in which a function (formula) model is used for estimation of gradation characteristics that are not directly measured. However, in the case of the technique disclosed in Patent Document 2, it is assumed that the image output characteristics that are automatically determined are generated by being combined with the base image output characteristics. Other image output characteristics cannot be estimated for missing portions.

  For this reason, in the method disclosed in Patent Document 2, the first image output characteristic serving as a base is restricted to a pattern having a wider gradation width than the estimated second image output characteristic. Specifically, the 2 × 2 output gradation value of FIG. 12 of Patent Document 1 corresponds to the 1 × 1 output gradation value range in which the density value shown in FIG. This corresponds to the fact that the 1 × 1 output gradation value corresponding to 0 is offset. That is, the technique disclosed in Patent Document 2 has a problem in that 2 × 2 output gradation characteristics cannot be obtained from 1 × 1 output gradation characteristics.

  More generally, when estimating the general gradation characteristics based on the combination with the reference correction characteristics, the gradation characteristic information lost due to highlight skipping, gradation collapse, or reduction in resolution based on the correction, etc. This means that since it is impossible to generate other gradation characteristics, it is necessary to use gradation processing with no information loss as much as possible as a reference. That is, in this case, the gradation processing that can be used as a reference is limited to the gradation processing with the minimum number of lines that is not always used. In addition, there is a problem that the estimation error of the characteristics of gradation processing with a high number of lines, which is more likely to cause an estimation error, tends to increase.

  In the method disclosed in Patent Document 3, the second input / output characteristic when the copied image is re-copied is stored in advance as the first input / output characteristic value created for the normal document. It is disclosed that it is created by comparing with a fixed value.

  However, in the case of a method of holding a difference value of gradation characteristics for such correction, correction values corresponding to the number of gradation patches are required for the number of gradation processes to be supported. Particularly, in the case of color printing using four or more primary colors, the memory consumption for the difference value to be held increases, so that the number of gradation processes that can be supported is limited or the cost is increased. Cause problems.

  The method disclosed in Patent Document 4 generates a correction table for the necessary number of gradation processes by automatically dividing a calibration patch area. However, this also limits the number of lines that can be supported because the patch area cannot be divided below the minimum number of patches whose gradation characteristics can be estimated. This limit is very low especially when there is a restriction that cannot take a very large patch area from the beginning.

  Further, in the technique disclosed in Patent Document 5, the number of gradation processes (image processing) targeted for engine calibration is not reduced. Therefore, if the number of supported line combinations increases, the interval between the original image output processes is increased. There arises a problem that real-time calibration becomes difficult, such as when performing calibration with. In particular, it is impossible to handle any number of lines. In addition, an increase in the number of calibration patches leads to an increase in color materials used in addition to the original printing, resulting in problems such as waste of resources and an increase in user burden costs.

  The present invention has been made in view of the above-described problems, and an object thereof is to provide an image forming apparatus, an image forming method, and an image forming program for realizing highly accurate gradation correction. Specifically, an object of the present invention is to minimize the number of steps for performing calibration for halftone dot patterns of all lines in image formation that supports gradation processing using a halftone dot pattern of a plurality of lines. This is to reduce the time required for calibration and the amount of color material consumed in addition to printing, and further to the gradation characteristics of gradation processing with one specific number of specific lines with the highest frequency of use for each color. Based on this, it is possible to calibrate the gradation characteristics of gradation processing with an arbitrary number of lines having a lower number or a higher number of lines. This provides an image forming apparatus, an image forming method, and an image forming program that reduce the estimation error in the entire number of supported lines and realize high-accuracy gradation correction.

  In order to solve the above problems, the present invention employs means for solving the problems having the following characteristics.

According to the first aspect of the present invention, there is provided an image forming apparatus that forms a tone-corrected image, a halftone dot selecting unit that selects a specific halftone dot pattern from a plurality of different halftone dot patterns set in advance, A gradation processing means for associating an input gradation value with a halftone dot area ratio of an output image by a halftone dot pattern obtained by a halftone dot selection means, and a gradation for correcting the input gradation value based on gradation correction data A correction unit; an image forming unit that forms an image based on an output from the gradation processing unit; a density detecting unit that detects a density of an image obtained by the image forming unit; and a detection value obtained by the density detecting unit. A gradation correction data generation means for generating gradation correction data of the gradation correction means and a reference image holding means for holding a reference image composed of a plurality of gradation patches. The gradation correction data generation means, of the number of lines f of selectable dot pattern in the dot selecting means, intermediate one of said network lines number f ₀ output from the reference image holding means A gradation characteristic parameter characterizing a gradation characteristic is extracted based on a detection value of the density detection means in the reference image based on a point pattern , and the network is calculated by using the gradation characteristic parameter and a predetermined function model. Gradation correction data corresponding to a halftone dot pattern having an arbitrary number of lines selected by the point selection means is generated.

  According to the first aspect of the invention, highly accurate gradation correction can be realized. Therefore, a highly accurate image can be formed.

According to a second aspect of the present invention, there is provided an image forming apparatus that forms a tone-corrected image, a halftone dot selecting unit that selects a specific halftone dot pattern from a plurality of different halftone dot patterns set in advance, A gradation processing means for associating an input gradation value with a halftone dot area ratio of an output image by a halftone dot pattern obtained by a halftone dot selection means, and a gradation for correcting the input gradation value based on gradation correction data Based on the output from the correction means, the reference image generation means for generating a reference image composed of gradation patches composed of a plurality of gradations , and the gradation processing means or the reference image generation means , a plurality of gradations An image forming unit that forms an image of a reference image composed of patches, a density detecting unit that detects the density of an image obtained by the image forming unit, and a detection value obtained by the density detecting unit And a gradation correction data generating means for generating tone correction data for gradation correction means, the gradation correction data generation means, of the number of lines f of selectable dot pattern in the dot selection means A gradation characteristic parameter characterizing a gradation characteristic is extracted based on a detection value of the density detection means in the reference image by the halftone dot pattern having one intermediate line number f ₀ , and the gradation characteristic parameter Gradation correction data corresponding to a halftone dot pattern having an arbitrary number of lines selected by the halftone dot selection means is generated by calculation using a predetermined function model.

According to the second aspect of the present invention, highly accurate gradation correction can be realized. Therefore, a highly accurate image can be formed.
The invention described in claim 3 is characterized in that at least one of the gradation characteristic parameters is a highlight offset x ₀ which is a rising gradation value of density .
The invention described in claim 4 is characterized in that the gradation characteristic parameter is three or less.

According to a fifth aspect of the present invention, the gradation characteristic parameter includes at least a maximum value of an output image density characteristic of the image forming apparatus with respect to an input gradation value to the gradation processing means, and an input at the beginning of the rising of the gradation. It has three parameters: a highlight offset value that is a value, and a gradation gradient that is an inclination of the rising edge of the gradation.

According to the fifth aspect of the present invention, the three parameters are at least the maximum value of the output image density characteristic, the highlight offset value that is the input value at the beginning of the gradation rise, and the gradation gradient that is the inclination of the gradation rise. By having it, gradation correction can be easily performed, and the accuracy can be further improved.

According to a sixth aspect of the present invention, there is provided an image forming apparatus for forming a color image by superimposing colors by image formation of at least three or more colors. A halftone dot selecting unit that selects a combination of halftone dot patterns designated by the user from a combination of patterns, and an input gradation value is determined based on the halftone dot pattern selected by the halftone dot selecting unit. Gradation processing means for associating with the area ratio, gradation correction means for correcting the input gradation value based on gradation correction data, and image forming means for forming an image based on the output of the gradation processing means A gradation detecting unit for detecting a density of an image obtained by the image forming unit; and a gradation correction of the gradation correcting unit for each color based on a detection value obtained by the density detecting unit. A gradation correction data generation means for generating data, and a reference image storage means for storing a reference image composed of gradation patch comprising a plurality gradation, the gradation correction data generation means, the dot of the line numbers f selectable dot pattern selecting means, wherein in the reference image by the dot pattern of the reference image holding means intermediate one ruling f ₀ which defines for each output color from A gradation characteristic parameter characterizing the gradation characteristic is extracted based on the detection value of the density detection means, and each color selected by the halftone dot selection means is calculated by using the gradation characteristic parameter and a predetermined function model. The tone correction data corresponding to a halftone dot pattern having an arbitrary number of lines is generated.

According to the sixth aspect of the present invention, highly accurate gradation correction can be realized even in color printing or the like. Therefore, a highly accurate image can be formed.

According to a seventh aspect of the present invention, the gradation characteristic parameter includes at least a maximum value of an output image density characteristic of the image forming apparatus with respect to an input gradation value to the gradation processing unit for each color, and a rising edge of the gradation. It has three parameters: a highlight offset value that is an initial input value, and a gradation gradient that is an inclination of a rising edge of gradation.

According to the seventh aspect of the present invention, the three parameters are at least the maximum value of the output image density characteristic, the highlight offset value that is the input value at the beginning of the gradation rise, and the gradation gradient that is the inclination of the gradation rise. By having it, modeling of gradation characteristics with a small number of parameters is realized.
In the invention described in claim 8, the function model of the highlight offset x ₀ is x ₀ = x ₀ (f ₀ ) · (f / f ₀ ) ² (where f: general number of halftone lines, f ₀ : specific number of halftone lines, x ₀ (f ₀ ): highlight offset value for each color with respect to specific number of halftone lines f ₀ ).
In the invention described in claim 9, the predetermined function model is D ⁻¹ (x) = x ₀ + (1−x ₀ ) {1− (1−x) ^{1 / {(1−x0) g. }} } (Where g is the gradation gradient and x is the input gradation value), and the function model of the gradation gradient g is g = x−x ₀ (f) + A · Sqrt (xx−x ₀ (f) ) · F (where A: constant, x> x ₀ , Sqrt: positive square root).

According to a tenth aspect of the present invention, there is provided an image reading unit capable of reading a print output of the image forming apparatus instead of the density detection unit, and the image reading unit is an image obtained by the image forming unit. The density | concentration of is detected.

According to the tenth aspect of the present invention, the entire print output can be evaluated. Accordingly, more gradation patches can be measured, and more accurate gradation correction can be realized.

According to an eleventh aspect of the present invention, in the image forming method in an image forming apparatus for forming a tone-corrected image, a halftone dot selection for selecting a specific halftone dot pattern from a plurality of preset different halftone dot patterns A gradation processing step for associating an input gradation value with an area ratio of a halftone dot of an output image based on a halftone dot pattern obtained by the halftone dot selection step, and the input gradation value based on gradation correction data A gradation correcting step for correcting, an image forming step for forming an image based on an output from the gradation processing step, a density detecting step for detecting a density of an image obtained by the image forming step, and the density detecting step. A gradation correction data generation step for generating gradation correction data in the gradation correction step based on the obtained detection value, and a plurality of gradations That the gradation patch and a reference image holding step of holding a reference image composed, the gradation correction data generating step, among the number of lines f of selectable dot pattern in the dot selection step, A gradation characteristic parameter characterizing the gradation characteristic is extracted based on the detection value of the density detection step in the reference image by the halftone dot pattern of one intermediate line number f ₀ output from the reference image holding step. And generating gradation correction data corresponding to a halftone dot pattern of an arbitrary number of lines selected by the halftone dot selection step by an operation using the gradation characteristic parameter and a predetermined function model. To do.

According to the eleventh aspect of the present invention, highly accurate gradation correction can be realized. Therefore, a highly accurate image can be formed.

According to a twelfth aspect of the present invention, in the image forming method in the image forming apparatus for forming a tone-corrected image, a halftone dot selection for selecting a specific halftone dot pattern from a plurality of different halftone dot patterns set in advance. A gradation processing step for associating an input gradation value with an area ratio of a halftone dot of an output image based on a halftone dot pattern obtained by the halftone dot selection step, and the input gradation value based on gradation correction data A gradation correction step for correction, a reference image generation step for generating a reference image composed of gradation patches composed of a plurality of gradations , and a plurality of levels based on the output from the gradation processing step or the reference image generation step. An image forming step for forming a reference image composed of tone gradation patches, and density detection for detecting the density of the image obtained by the image forming step And step, based on detection values obtained by the concentration detection step, and a gradation correction data generating step of generating a tone correction data of the tone correction step, the gradation correction data generating step, the of ruling f screen pattern can be selected in halftone dot selection step, based by intermediate one of said dot pattern with a line number f ₀ of the detected value of the concentration detection step in the reference image, the gradation A gradation characteristic parameter that characterizes a characteristic is extracted, and a gradation corresponding to a halftone dot pattern having an arbitrary number of lines selected by the halftone dot selection step is obtained by calculation using the gradation characteristic parameter and a predetermined function model. Correction data is generated.

According to the twelfth aspect of the present invention, highly accurate gradation correction can be realized. Therefore, a highly accurate image can be formed.
The invention described in claim 13 is characterized in that at least one of the gradation characteristic parameters is a highlight offset x ₀ which is a rising gradation value of density .
The invention described in claim 14 is characterized in that the gradation characteristic parameter is three or less.

According to a fifteenth aspect of the present invention, the gradation characteristic parameter includes at least a maximum value of an output image density characteristic of the image forming apparatus with respect to an input gradation value to the gradation processing step, and an input at the beginning of gradation rising. It has three parameters: a highlight offset value that is a value, and a gradation gradient that is an inclination of the rising edge of the gradation.

According to the fifteenth aspect of the present invention, the three parameters are at least the maximum value of the output image density characteristic, the highlight offset value that is the input value at the beginning of the gradation rise, and the gradation gradient that is the inclination of the gradation rise. By having it, gradation correction can be easily performed, and the accuracy can be further improved.

According to a sixteenth aspect of the present invention, in an image forming method in an image forming apparatus for forming a color image by superimposing colors by image formation of at least three colors, a plurality of different lines are formed for image formation of each color. A halftone dot selection step for selecting a halftone dot pattern combination designated by the user from a combination of a plurality of halftone dot patterns, and an input gradation value is output based on the halftone dot pattern selected in the halftone dot selection step A gradation processing step that correlates to the halftone dot area ratio of the image, a gradation correction step that corrects the input gradation value based on gradation correction data, and image formation based on the output of the gradation processing step An image forming step, a density detecting step for detecting a density of an image obtained by the image forming step, and a density detecting step. A gradation correction data generation step for generating gradation correction data of the gradation correction step for each color based on the detected value, and a reference image holding for holding a reference image composed of a plurality of gradation patches The gradation correction data generation step includes an intermediate step determined for each color output from the reference image holding step out of the number f of halftone dot lines that can be selected in the halftone dot selection step. A gradation characteristic parameter characterizing a gradation characteristic is extracted based on a detection value of the density detection step in the reference image by the halftone dot pattern having a single line number f ₀ , and the gradation characteristic parameter and a predetermined function are extracted A gradation correction data corresponding to a halftone dot pattern having an arbitrary number of lines for each color selected by the halftone dot selection step is generated by calculation using a model. To.

According to the sixteenth aspect of the present invention, highly accurate gradation correction can be realized even in color printing or the like. Therefore, a highly accurate image can be formed.

According to a seventeenth aspect of the present invention, the gradation characteristic parameter includes at least a maximum value of an output image density characteristic of the image forming apparatus with respect to an input gradation value to the gradation processing step for each color, and a rising edge of the gradation. It has three parameters: a highlight offset value that is an initial input value, and a gradation gradient that is an inclination of a rising edge of gradation.

According to the seventeenth aspect of the present invention, the three parameters are at least the maximum value of the output image density characteristic, the highlight offset value that is the input value at the beginning of the gradation rise, and the gradation gradient that is the gradient of the gradation rise. By having it, modeling of gradation characteristics with a small number of parameters is realized.
In the invention described in claim 18, the function model of the highlight offset x ₀ is x ₀ = x ₀ (f ₀ ) · (f / f ₀ ) ² (where f: general number of halftone lines, f ₀ : specific number of halftone lines, x ₀ (f ₀ ): highlight offset value for each color with respect to specific number of halftone lines f ₀ ).
According to the nineteenth aspect of the present invention, the predetermined function model is: D ⁻¹ (x) = x ₀ + (1−x ₀ ) {1− (1−x) ^{1 / {(1−x0) g }} } (Where g is the gradation gradient and x is the input gradation value), and the function model of the gradation gradient g is g = x−x ₀ (f) + A · Sqrt (xx−x ₀ (f) ) · F (where A: constant, x> x ₀ , Sqrt: positive square root).

The invention described in claim 20 has an image reading step capable of reading a print output of the image forming apparatus instead of the density detection step, and the image reading step is an image obtained by the image forming step. The density | concentration of is detected.

According to the twentieth aspect , the entire print output can be evaluated. Accordingly, more gradation patches can be measured, and more accurate gradation correction can be realized.

The invention described in claim 21 is an image forming program for causing a computer to execute the image forming method described in any one of claims 11 to 20 .

According to the twenty- first aspect of the present invention, highly accurate gradation correction can be realized. Therefore, a highly accurate image can be formed. Further, by installing the program, the image formation in the present invention can be easily realized by a general-purpose personal computer or the like.

  According to the present invention, highly accurate gradation correction can be realized. Therefore, a highly accurate image can be formed.

  Hereinafter, embodiments in which an image forming apparatus, an image forming method, and an image forming program according to the present invention are suitably implemented will be described with reference to the drawings. In the following description, “density” is not necessarily a density in an accurate sense, but is used as a concept expressing the color density. Examples of the density in this sense include the complement of the reflected luminance and the color difference ΔE from the paper surface in the printing result in addition to the density in the original meaning. In particular, in the following embodiments, the printing result is mainly used. Is used to mean CIE (Commission Internationale de l'Eclairage: International Lighting Commission) color difference ΔE from the page.

<Image forming apparatus: apparatus configuration example>
FIG. 1 is a diagram illustrating a configuration example of an image forming apparatus according to the present embodiment. As an example of the image forming apparatus described below, for example, a schematic configuration of a 600 dpi color laser printer printer is shown, but the image forming apparatus according to the present invention is not limited to this.

  A printer engine 10 as an image forming apparatus shown in FIG. 1 includes a photosensitive member (photosensitive member) 11, an intermediate transfer member 12, a developing device 13, a charger 14, an exposure device 15, a reflection luminance sensor 16, and a controller. 17, a transfer roller 18, a cassette unit 19, a fixing device 20, and an operation panel (operation means) 21.

  The photoconductor 11 shown in FIG. 1 has a belt shape, for example, and rotates at a predetermined timing and speed in the direction of arrow A shown in FIG. Further, the intermediate transfer body 12 transfers toner images of four different colors formed one by one on the photoconductor 11 one color at a time for each rotation. That is, as an example, the intermediate transfer body 12 employs an intermediate transfer body system that forms one color image by four rotations.

  In FIG. 1, the belt-shaped photoconductor 11 is disposed at the center of the printer engine 10, and an intermediate transfer body 12 is disposed in contact with the photoconductor 11 on one surface thereof.

Further, around the photoconductor 11, along the rotation direction, the developer 13, the charger 14, the exposure device 15, and the toner adhering to the photoconductor 11, which are process parts that form a toner image on the photoconductor 11. A reflection luminance sensor 16 for detecting the amount is arranged. Further, in the case side of the printer engine 10, board of the controller 17 as control means for controlling the overall functional components of the printer engine 10 shown by broken lines is placed.

  The developing unit 13 includes four developing units (a black developing unit 13K, a yellow developing unit 13Y, and a magenta developing unit 13M) that store toners of different colors on the side opposite to the intermediate transfer member 12 in the photoconductor 11 that is elongated vertically. , Cyan developing devices 13C) are vertically stacked. The developing unit 13 attaches an image visualization agent such as toner corresponding to each color component of black (K), yellow (Y), magenta (M), and cyan (C) to the photoreceptor 11.

  The charger 14 uniformly charges the surface of the photoconductor 11. The exposure device 15 exposes the surface of the charged photoconductor 11 by irradiating a laser beam to form an electrostatic latent image.

  That is, the photoconductor 11 to which the image visualization agent corresponding to each color is attached performs transfer of each color to a predetermined position on the intermediate transfer body 12 that rotates at a predetermined timing and speed. As a result, a visible image (color image) is formed on the intermediate transfer body 12.

  The reflected luminance sensor 16 emits luminance detection light to a predetermined area of the photoconductor 11 and detects (receives) the reflected light. Note that the luminance detection signal from the reflection luminance sensor 16 is converted into a density value for image output by a conversion table or the like stored (mounted) in advance in the controller 17. In this sense, the reflected luminance sensor 16 has a function as a density detecting means. Thus, the accuracy of image formation can be grasped by detecting the adhesion amount of the image visualization agent on the photoconductor 11 by the reflection luminance sensor 16.

  Further, around the intermediate transfer body 12, a transfer roller 18 which is a process component for forming a toner image and transporting a print medium (recording medium) such as paper is disposed. Specifically, the transport path for transporting the paper is configured to discharge from the cassette unit 19 such as a paper cassette disposed at the lower part of the main body to the upper surface of the main body through the outer side of the intermediate transfer body 12. A transfer roller 18 that presses a printing medium such as paper against the intermediate transfer body 12 to transfer a visible image (color image) formed on the intermediate transfer body 12 to the paper and conveys the paper in a predetermined direction. A fixing device 20 is provided for fixing the visible image (toner image) transferred from the intermediate transfer body 12 to the printing medium by passing the printing medium while supplying heat. As another configuration, for example, a sheet static eliminator (not shown) for gradually depressing the print medium may be provided at a predetermined position.

  Further, an operation panel (operation means) 21 as a user interface having halftone dot selection means is provided facing the outside of the housing. A manual calibration command or the like by the user is sent to the controller 17 through the operation panel 21.

<Image forming apparatus: functional configuration example>
Next, a functional configuration example in the image forming apparatus 10 will be described with reference to the drawings. FIG. 2 is a diagram illustrating an example of a functional configuration of the image forming apparatus according to the present invention. The image forming apparatus 10 shown in FIG. 2 includes an input unit 31, an output unit 32, a storage unit 33, an image expansion unit 34, a color correction unit 35, a reference image generation unit 36, and a reference image holding unit 37. 4-color separation means 38, halftone dot selection means 39, color selection means 40, gradation correction data generation means 41, gradation correction means 42, gradation processing means 43, density detection means 44, The image forming unit 45 includes a transmission / reception unit 46 and a control unit 47.

  The input unit 31 receives an input of each instruction such as an instruction to execute an image forming process from the user, an instruction to read or write predetermined data from the storage unit 33, and the like. Note that the input unit 31 includes, for example, an input interface such as a touch panel, and may be a pointing device such as a keyboard or a mouse, a voice input interface such as a microphone, or the like.

  The output unit 32 selects the instruction content input by the input unit 31 and the tone correction color generated based on the instruction content, displays the correction result, and forms the image forming process result. Data such as images, messages for notifying the user of the start and end of processing, and the like are displayed and / or output as audio. Note that the output unit 32 includes a monitor, a speaker, and the like.

  In addition, the storage unit 33 includes a gradation correction data table, a threshold value array table, history data, a conversion table, a reference image (gradation value data (patch data)), various parameters, and image density detection results (for example, patch images) described later. Brightness information), RGB data color-corrected by image development, and the like, various data necessary for executing each process and various data generated after the process is executed are stored.

  Further, the image expansion means 34 expands an input image into, for example, dot sequential RGB data for one page. In addition, the color correction unit 35 converts the developed RGB data into color information that matches the characteristics of the printing device of the color information included in the input drawing command. The color-corrected RGB data is stored in the storage means 33.

  In addition, the reference image generation unit 36 generates gradation value data (patch data) composed of gradation patches composed of a plurality of gradations as reference image data. The reference image holding unit 37 holds a reference image composed of gradation patches made up of a plurality of gradations. The reference image may be stored in the storage unit 33.

  The four-color separation unit 38 separates the RGB data stored in the storage unit 33 into four colors of black (K), cyan (C), magenta (M), and yellow (Y). Here, the method of decomposing RGB (three colors) into KCMY (four colors) can change the setting according to the ability of the machine, the drawing intention, etc. For example, the four-color decomposing means 38 corresponds to KCMY. A lookup table composed of K [i], C [i], M [i], Y [i] (i = 0,..., 255) is prepared in advance, and K = K [max {R, G, B}], C = C [R], M = M [G], and Y = Y [B] can be separated into four colors. Also, K = K [k], C = C [c], M = M [m], Y = Y [y] (where k = min {R, G, B}, c = 255-R, m = 255-G, y = 255-B).

  Also, the halftone dot selection means 39 selects a specific halftone dot pattern from a plurality of different line numbers (halftone dot patterns). The halftone dot selection means 39 also provides a user interface for allowing the user to select the number of lines (halftone dot pattern). The details of the user interface in the halftone dot selection means 39 will be described later.

  In addition, the color selection means 40 is set in advance for which color to perform tone correction among the line number selection signal, the color selection signal, and the signal decomposed by the four-color separation means 38. Further, the color selection means 40 performs processing such as which signal is selected as an output color among the selected K, C, M, and Y.

  Further, the gradation correction data generation means 41 generates a lookup table (LUT) for performing gradation correction. Specifically, the gradation correction data generation unit 41 uses a method described later on the basis of the reflected luminance signal corresponding to each patch of the patch image that has been sent, and uses a threshold value array network registered in the threshold value array table. Tone correction data corresponding to each number of dotted lines is generated.

  The gradation correction data generation unit 41 stores the generated gradation correction data in the storage unit 33 as a gradation correction data table. The generated gradation correction data table is implemented as a lookup table (LUT) having 256 8-bit entries.

  Further, the gradation correction means 42 corrects an 8-bit image signal of one pixel from 0 to 255 to an 8-bit output gradation value according to the gradation correction data table 40. Here, the gradation correction data is implemented as a lookup table (LUT) having 256 8-bit entries.

  The gradation processing unit 43 outputs an 8-bit gradation value of one pixel output from the gradation correction unit 42 as a pulse width modulation (PWM) signal of one pixel using a preset threshold array.

  Specifically, the gradation processing unit 43 first loads the threshold interval Δh and the bit shift amount s in initialization prior to page processing. The bit shift amount s is a value set in advance corresponding to Δh as a value sufficient to round down Δh to 4 bits, which is the number of divisions by PWM. Next, a difference Δn between the input pixel value ni and the threshold nc is calculated. The threshold nc is sequentially input in synchronization with the input pixel value ni based on the threshold array or the simplified threshold array.

  Next, Δn is compared with Δh. When the PWM output value p is Δn <0, p = 0, Δn ≧ Δh, p = f (hexadecimal), and 0 ≦ Δn <Δh, p = (Δn / 2 ^ s) (2 ^ s represents 2 to the power of s). However, the remainder of the process of dividing Δn by 2 ^ s is rounded down or rounded up.

  Next, the final PWM output level value p ′ is acquired according to the threshold value array using the PWM output value p as an index. The above-described processing is repeated until the processing of the pixels for one page is completed, and then is repeated from the beginning as the processing for the next page or the next color plane. Note that the above-described processing can use, for example, the technique disclosed in Patent Document 1.

  Further, the density detection unit 44 detects the luminance of the patch image attached to the photoconductor 11 and the like, and detects the detected luminance information. Further, the detected result is accumulated by the accumulation means 33. The density detection unit 44 is configured by a sensor (reflection luminance sensor 16) that detects the reflected luminance, for example.

  Further, the image forming unit 45 develops the input image and character data for each surface (each color) of YMCK, and finally prints it on a printing medium such as paper. The transmission / reception means 46 is a communication interface for acquiring data from other external devices or the like via a communication network and transmitting various data generated such as image formation results to an external terminal.

  The control unit 47 controls the entire functional configuration of the image forming apparatus 10. Specifically, the control unit 47 is configured to perform image development, color correction, reference image generation, four-color separation, halftone dot selection, output color selection, level selection based on input information from the user input by the input unit 31 and the like. Control is performed such as generation and display of a screen in each processing such as generation of tone correction data, gradation processing, density detection, and image formation, and accumulation of information generated in each of the above-described processing.

<Image processing procedure>
Next, an image forming process procedure in the image forming apparatus 10 of the present invention having the above-described functional configuration will be described with reference to the drawings. FIG. 3 is a diagram showing an example of an image forming process procedure in the present embodiment. Also, the alternate long and short dash line in FIG. 3 indicates repetition of processing, not signal flow. Also, the numerical values shown on the arrows in FIG. 3 show an example of the number of bits of information to be output.

<Image processing procedure during normal printing>
First, the flow of image processing during normal printing will be described. First, image data to be printed is input (S01), the image expansion process is performed by the above-described image expansion unit 34 (S02), and the color correction process is performed by the color correction unit 35. RGB data is acquired (S03). The acquired result is stored in the image buffer as the storage means 33 (S04).

  Further, the color selection signal 51 selected by the user or the like by the controller 17 is a 2-bit signal that is automatically incremented by one each time output of each color plane is completed, for example, in accordance with a synchronization signal from the printer engine 10 side. At the start of page printing, it is initialized to 0.

  Here, the line number selection signal 52 is one of values 0, 1, and 2 selected through a user interface as a halftone dot selection means 39 by the printer driver 10 or the operation panel 21 to be described later. Each mode is given as “gradation priority”, 1 is “standard”, and 2 is “resolution priority”. An example of the number of dotted lines assigned to these modes will be described later.

  The RGB image data stored in the image buffer as the storage means 34 is decomposed into signals of four colors K, C, M, and Y by the four-color separation means 38 (S05). In addition, the value of the color selection signal 51 already set by the color selection means 40 is set to four output values of K, C, M, and Y according to any of 0, 1, 2, and 3, respectively. The output is selected from the output of the disassembling means 38 (S06).

  Further, the gradation correction means 42 corrects the image signal of 1 pixel 8 bits from 0 to 255 to the same 8-bit output gradation value according to the gradation correction data 53 (S07). Here, the gradation correction data 53 is implemented as a lookup table (LUT) having 256 8-bit entries. In the gradation processing, the 8-bit gradation value of one pixel output from the gradation correction unit 42 using the threshold array 54 is output as a pulse width modulation (PWM) signal of one pixel 4 bits (S08).

  Further, the value of the gradation correction data 53 is obtained from the gradation correction data table 55 according to the combined selection signal obtained by combining the color selection signal 51 and the line number selection signal 52 before the data is read from the image buffer. Is selected and loaded as gradation correction data 53.

  An example of the number of halftone lines assigned to the combined line number selection signal 52 will be described later. Similarly, one corresponding threshold array is selected from the threshold array table 56 and loaded as the threshold array 54.

  Here, the gradation correction table value loaded as the gradation correction data 53 is corrected so that the density of the image output output with respect to the input value of the gradation processing means 43 for each color is substantially linear. As described above, it is generated by the gradation correction data generating means 41 in association with the threshold value array 54 during the calibration operation described later.

  Each threshold value array stored in the threshold value array table 56 is accurately stored with information on the array size and the number of halftone lines. The threshold value array 54 is loaded together with the information.

  The threshold array that forms halftone dots with various lines serving as elements of the threshold array table 56 is an array size together with a basic threshold pattern set in advance and a threshold array value that is built in advance by a threshold array configuration method using the threshold array. The number of halftone lines is held as a fixed value.

  The controller 17 repeats the processing after the image buffer in FIG. 3 for four sides of K, C, M, and Y (four times) in accordance with the color selection signal 51 that is automatically switched, so that four KCMY values for the printer engine 10 are obtained. Data for each color plane necessary for the color development process is generated.

The printer engine 10 forms a full-color image by superimposing these colors (S09), forms it on the paper surface, and outputs it as an image (S10). In the process of S09, the output value ref _i (i = 1, 2, 3, 4) obtained by detecting the patch image formed on the photoconductor 11 from the reflection luminance sensor 16 is output to the CPU or the like as the control means 47. This value is used for the above-described gradation correction processing and the like.

<Basic threshold pattern example>
Here, FIG. 4 is a diagram illustrating an example of a basic threshold pattern. For example, the array size and the number of halftone lines are held as fixed values together with the basic threshold pattern as shown in FIGS. 4A to 4E and the threshold array value constructed in advance by the threshold array configuration method using the basic threshold pattern. . For example, the contents shown in FIGS. 10 and 17 in Patent Document 1 can be used as the basic threshold pattern.

  FIG. 5 is a diagram illustrating an example of a table entry corresponding to the threshold value array. FIG. 5 shows an example of a table entry corresponding to the threshold value array of FIG. 8 in Patent Document 1, and can also be applied to this embodiment.

  Here, the address offset shown in FIG. 5 is the offset value (decimal) of the address from the entry head, and the value stored at each address is a 1-byte value in decimal notation. Both the s value (bit shift amount) and the number of PWM stages correspond to those in FIG. 4 described above.

  Note that the number of halftone dots (lpi) is rounded off to the nearest whole number. For example, when the maximum gradation value exceeds 255 as shown in FIG. 4C, the entry with address offset = 2 is stopped at 255.

<Operation procedure during calibration>
Next, the operation at the time of calibration will be described mainly according to the flow shown by the broken line in FIG. The calibration operation is activated when the printer is activated, when the number of output sheets reaches a predetermined value, or by a user instruction from the operation panel 21 (FIG. 1).

  At the time of the calibration operation, a patch image generated based on the gradation value data (patch data) generated by the reference image generation unit 36 and stored in the reference image holding unit 37 or the like with respect to the image buffer as shown in FIG. Write 57 directly.

  On the other hand, the four-color separation means 38 performs internal processing on the RGB signal (r, g, b) with (k, c, m, y) = (min {c, m, y}, 255-r, The process is switched to the process corresponding to the KCMY signal of 255-g, 255-b). Further, the processing of the gradation correction means 42 is passed through without being executed.

  Accordingly, for example, by preparing data in which g and b are fixed to g = b = 255 and r is shaken as patch data, a cyan single-color patch image corresponding to a signal value of c = 255-r can be obtained. Are sent to the printer engine 10. The above-described processing can be similarly performed for magenta and yellow, but for black, a patch corresponding to a signal value of k is prepared by preparing data of r = g = b = 255-k. The image is sent to the printer engine 10.

  In the calibration operation mode, the printer engine 10 executes the same process as the normal printing described above except that the paper is not picked up and the process after the transfer to the printing medium such as the paper is not executed. Is done.

<Example of patch image formed on photoconductor>
FIG. 6 is a diagram illustrating an example of a patch image formed on the photoconductor. As a result of the above-described processing, as shown in FIG. 6, a patch image 57 can be formed at a predetermined position on the photoconductor 11 of the printer engine 10 (for example, a position not in contact with the intermediate transfer body 12). Further, the reflection luminance sensor 16 mounted on the printer engine 10 detects the reflection luminance signal of the patch image 57 and transmits it to the gradation correction data generation means 41. As a result, the reflected luminance signal of the patch image can be detected without performing image output to a print medium such as paper.

  Further, the gradation correction data generation means 41 uses the number of halftone dots of the threshold value array registered in the threshold value array table 56 by a method described later based on the reflected luminance signal corresponding to each patch of the received patch image 57. Are generated and registered in the gradation correction data table 55.

  In the present embodiment, the generation of gradation correction data is realized by a CPU as the control means 47 mounted on the controller 17, a peripheral memory as the storage means 33, and a program incorporated therein in advance. In FIG. 3, the threshold array table 56, the gradation correction data table 55, and the history data 58 are realized as specific address spaces in the peripheral memory in the storage unit 33 although they are written for convenience. Similarly, the reference image generation process is realized by a program for the CPU or the like.

<Generation Method of Tone Correction Data by Tone Correction Data Generation Unit 41 >
Next, a method for generating gradation correction data by the gradation correction data generating means 41 will be described. FIG. 7 is a diagram illustrating an example of a gradation characteristic model of the image forming apparatus according to the present embodiment. In FIG. 7, the horizontal axis indicates the input gradation value for the gradation processing means 43 with the range normalized to a range of 0 to 1, and the vertical axis D indicates the color difference ΔE from the paper surface of the image output with its maximum value ΔE. _The relative value D normalized by _max = ΔE / ΔE _max is shown. In the following description, D is referred to as a relative density.

In this case, tone characteristic D of relative density D with respect to the input gray-scale value x (x) is, K, using C, M, the appropriate x ₀ and γ for each color of Y, following expressions (1) Is approximated by
D (x) = 0 (0 ≦ x <x ₀ )
D (x) = 1− {1-((x−x ₀ ) / (1−x ₀ )) ^γ } (x ₀ <x ≦ 1) (1)
Is approximated by

Here, the rising gradation value x ₀ of the relative density is called a highlight offset, γ is a gamma value, and the gradient g = γ / (1−x ₀ ) near the highlight offset is called a gradation gradient. The above model, the characteristics of halftones highlight offset x ₀ and gradation gradient g and will be characterized by three parameters Delta] E _max.

In particular, the maximum value Delta] E _max of the color difference from the sheet surface, by controlling so that a constant value by a separate printer engine 10 side (e.g., control of the developing bias), the gradation correction data x ₀ and two parameters g Will be characterized.

Further, the tone correction function in this case is D ⁻¹ (x) = x ₀ + (1−x ₀ ) given by the following equation (2) obtained by reversing the above equation (1). {1- (1-x) ^{1 / {(1-x0) g}} } (2)
Therefore, if x ₀ and g are given, the gradation correction data can be generated using the above-described equation (2).

However, in general, these parameters x ₀ and g both change depending on the dot gain and the number of halftone lines f that are different for each color. Therefore, it is necessary to execute for a combination of the number of lines.

  From the beginning, for all entries and color combinations in the threshold array 56, the patch image 57 is accumulated in the reference image holding means 37 as a binarized image and sent directly to the printer engine 10. However, in this case, there is a problem that the scale of the reference image holding unit 37 becomes large, and the management complexity for matching the entries of the threshold value array table 56 and the entries of the storage unit 33. This causes a problem that causes a decrease in productivity in device development.

However, if the change in x ₀ and g with respect to the number of halftone lines f can be estimated from the gradation patch having a specific number of halftone lines, the gradation processing in the calibration operation described above is performed on one threshold value array 54. By executing only this, it is possible to generate gradation correction data corresponding to all elements of the threshold value array table 56, and the calibration process can be greatly reduced.

  In addition, the reference image holding unit 37 only needs to hold a few gradation values to be evaluated regardless of the selected color and the entry contents of the threshold value array table 56, so that the storage area can be greatly saved. The advantage that the development man-hour is reduced is obtained.

Next, a method for estimating the highlight offset x ₀ and the gradation gradient g from the specific line number f = f ₀ will be described. Note that tone characteristic correction is correction performed for each color, and therefore, in the following description, description will be made using a single color output image.

  FIG. 8 is a diagram illustrating an example of the relationship between the highlight offset and the dot area. FIG. 8A is a conceptual diagram of a gradation processed image output in which one halftone dot region 61 is configured by 3 × 3 9 pixels, and FIG. 8B is 4 × 4 16 pixels. 6 is a conceptual diagram of gradation processing image output that constitutes one halftone dot region 63. FIG.

  In FIG. 8A, the minimum square included in the halftone dot 60 indicated by hatching in hatching represents a logical pixel unit, and is an auxiliary line that is not actually printed. Similarly, a halftone dot region 61 indicated by a thick line for every 3 × 3 pixels conceptually indicates a break between adjacent halftone dot regions, and is an auxiliary line that is not actually printed.

  A halftone dot 60 in FIG. 8A conceptually shows a halftone dot formed for the case where the input gradation value corresponds to one logical pixel. The input gradation value x at this time is the reciprocal x = 1/9 of the area S of the halftone dot region 61. Further, as the input gradation value x increases, the area of the halftone dot 60 increases, resulting in a solid image that fills the entire 3 × 3 region 61 with x = 1.

  Similarly, in the case of FIG. 8B, the area of the halftone dot region 63 is S = 4 × 4 = 16, and the input gradation value to the gradation processing means 43 corresponding to one logical pixel is x = 1/16.

On the other hand, if both halftone dots 60 and 62 are sufficiently separated from adjacent halftone dots, neither halftone dot 60 in FIG. 8A nor halftone dot 62 in FIG. The screen area product per point can be considered to be equal. Therefore, if if dot 60, 62, at a concentration of barely to be reproduced as a halftone image output, highlight offset _{x 0,} in the case of FIG. _{8 (a), x 0 =} 1/9 In the case of FIG. 8B, x ₀ = 1/16.

From these considerations, the highlight offset value x _0, it is understood that is inversely proportional to the halftone dot region area S. On the other hand, the area of the halftone dot region S is S = d ^ 2 where d is the halftone dot interval. For example, when the resolution of the printer engine 10 is 600 (dpi), the halftone dot interval d is the number of halftone dots f. Therefore, since d = 600 / f, S = (600 / f) ² is obtained. As a result, it can be seen that the highlight offset x ₀ is proportional to the square of the number of halftone lines f.

Figure 9 is a diagram showing an example of approximating the relationship between the halftone frequency f and highlights the offset value x ₀ by a quadratic function of f. In FIG. 9, “●” is cyan, “▲” is magenta, “■” is yellow, “♦” is black, and “● (cyan)” and “■ (yellow)” are approximate values. The curves are overlapping. As shown in FIG. 9, the highlight offset of each color is sufficiently approximated by a quadratic function of f.

From this, by obtaining the highlight offset value x ₀ (f ₀ ) for each color with respect to a specific halftone dotted line number f ₀ (eg, f ₀ = 150 (lpi)), the general line number f (lpi) is It is estimated by the following equation (3).
x ₀ = x ₀ (f ₀ ) · (f / f ₀ ) ² (3)
<Estimation method of gradation gradient g>
Next, a method for estimating the gradation gradient g will be described. FIG. 10 is a diagram showing an example of a 4 × 4 halftone dot region corresponding to the input gradation value x = 4/16 to the gradation processing means. In FIG. 10, one of the 4 × 4 halftone dot regions 63 shown in FIG. 8B is shown. In general, the area s of the halftone dot 64 actually formed as an image output is generally slightly larger than the corresponding logical halftone dot 65. The dot thickness is the dot gain.

  Here, it is assumed that the dot gain occurs with a constant width ε along the circumference of the logical halftone dot 65. At this time, if it is noted that the area of the logical halftone dot 65 is given by xS by the area S of the halftone dot area 63 and the input gradation value x, the area s of the halftone dot 64 is expressed as s = xS + 4εl. The

Therefore, the effective halftone dot area ratio a = s / S in this case is a = x + 4ε · Sqrt (x / S) (where Sqrt is a positive square root). Further, using the fact that l = Sqrt (xS) and S = (600 / f) ² , the following expression (4) is obtained.
a = x + 4ε / 600 · Sqrt (x) · f (4)
The contents described above, and is a simplified model based on the case shown in FIG. 8, also established in the vicinity of x> x ₀ side x ₀ for general input tone value x, further By assuming that the gradation gradient g matches the effective halftone dot area ratio a within the same neighborhood, the gradation gradient g is modeled as shown in the following equation (5).
g = x−x ₀ (f) + A · Sqrt (x−x ₀ (f)) · f
... (5)
However, at _x> x _0, A is an appropriate constant. In particular if fixed measurement patch gradation value for gradation gradient measured by x _1, gradation gradient g and becomes Equation (6) shown below.
g = x ₁ −x ₀ (f) + A · S qrt (x ₁ −x ₀ (f)) · f
... (6)
Here, if the gradation gradient g (f ₀ ) at f = f ₀ is known, the constant A is determined by solving the above equation (6) for A as shown in equation (7) below. The
A = {g (f ₀ ) − (x ₁ −x ₀ (f ₀ ))} / {Sqrt (x ₁ −x ₀ (f ₀ )) · f ₀ }
... (7)
Here, FIG. 11 is a diagram illustrating an example in which the relationship between the number of halftone lines f and the gradation gradient g is approximated by a function model. However, Expression (6) is used as the function model. Further, in the formula (6), x ₁ = 0.2. In FIG. 11, “●” indicates cyan, “▲” indicates magenta, “■” indicates yellow, and “♦” indicates black. In this case, the gradation gradient of each color is represented by the equation (6). It is sufficiently approximated by the model.

From this, the gradation gradient g is also obtained from the above equation (6) by obtaining the value of the constant A for each color with respect to a specific number of halftone dots f ₀ (for example, f ₀ = 150 lpi). It can be seen that it can be estimated.

<About Patch Image 57>
Next, the patch image 57 shown in FIG. 6 will be specifically described. FIG. 12 is a diagram illustrating an example of a patch image formed on the photoconductor. Prior to the calibration operation in this embodiment, the threshold value array table 56 shown in FIG. 3 is loaded with a threshold value array corresponding to a halftone dot with a predetermined moderate number of lines f ₀ (for example, f ₀ = 150 lpi). It is assumed that

  The patch image 57 is a single-color image generated by the reference image generation unit 36 based on the patch data held in the reference image holding unit 37 or the like for each of the K, C, M, and Y development processes.

  In addition, the direction indicated by the arrow in FIG. The marker 70 is a solid pattern for detecting the patch writing position, and the reflectance of the subsequent patch images 71a to 74d is sequentially detected as an 8-bit digital value by the reflection luminance sensor 16 shown in FIG.

Here, the patch image 71a, 71b, 71c, 71d are all in response to the input grayscale value _x 1 = 2/16, a halftone image of the ruling _{f 0,} which is formed on the photoconductor 11. The average of the output values of the reflected luminance sensor 16 for four points corresponding to these is defined as an output value ref ₁ for x ₁ .

Similarly, the patch image 72a, 72b, 72c, 72d corresponds to the input tone value _x 2 = 3/16, patch images 73a, 73b, 73c, 73d is the input gradation value _x 2 = 4/16 Correspondingly, the patch images 74a, 74b, 74c, and 74d correspond to the input gradation value x ₂ = 16/16. By averaging the output values of the reflected luminance sensor 16 corresponding to these, ref ₂ , ref ₃ and ref ₄ are obtained.

However, the values specifically selected as the above-mentioned x ₁ , x ₂ , x ₃ are selected as appropriate values for estimating the highlight offset x ₀ and the gradation gradient g, which are the feature quantities to be obtained from now on. As long as it has been done, it is not necessarily limited to the above value.

Next, the luminance value ref _i for each i = 1, 2, 3, and 4 is converted into ΔE _i using a conversion table for ΔE values from the paper surface obtained in advance for each color. By normalizing with the value ΔE ₄ , the relative density D _i = ΔE _i / ΔE ₄ is obtained.

Here, an example of the conversion table in the present embodiment will be described. The analog output value of the reflection luminance sensor is an integer value of an 8-bit range 0 to 255 for each color with the reflection luminance of the photosensitive member ground as a reference value (maximum value = 128). Is encoded. The reason why the reference value is set to 128 is to allow a signal input exceeding 128 in consideration of power supply fluctuation. The conversion table for converting the reflected luminance into the density is an array of 8-bit value output with 256 entries for each color, D _k [i], D _c [i], D _m [i], D _y [i] (i = 0, 1,..., 255), and can be immediately converted as a density value using the encoded reflected luminance as an index. In the case of this embodiment, since the color difference ΔE from the paper surface is used as an amount to express the density, the actual output range is about 0 to 100 by rounding the decimal part of ΔE as an integer value. It is a value.

FIG. 13 is a diagram illustrating an example of the relationship between the input gradation and the relative density. As shown in FIG. 13, the obtained points 75 = (x ₁ , D ₁ ), points 76 = (x ₂ , D ₂ ), and points 77 = (x ₃ , D ₃ ) are obtained as least squares solutions. From the x intercept and the slope of the approximate straight line 79, the highlight offset x ₀ and the gradation gradient g are obtained, respectively.

<Tone Correction Data Generation Processing Procedure in Tone Correction Data Generation Unit 41>
Next, based on the description of FIG. 12 and FIG. 13 described above and the entire processing procedure of FIG. 3 described above, the flow of gradation correction data generation processing related to the gradation correction data generation means 41 will be described. FIG. 14 is a flowchart showing an example of the gradation correction data generation processing procedure. The entire process shown in FIG. 14 is repeated four times corresponding to the process for four colors K, C, M, and Y.

First, as described above, the threshold value array corresponding to the number of lines f = f ₀ (for example, f ₀ = 150 lpi) to the threshold value array 54 as described above as the calibration operation, or the description of FIG. Initialization of various parameters such as initialization of the conversion table from the reflected luminance sensor value to ΔE described in the above is performed for each color of the corresponding developing process (S101).

  Next, patch generation is performed to form the patch image 57 generated by the reference image generation unit 36 on the photoconductor 11 based on the patch data stored by the storage unit 33 (S102).

Further, the output value ref _i (i = 1, 2, 3, 4) obtained by detecting the patch image formed on the photoconductor 11 is acquired from the reflection luminance sensor 16 of the printer engine 10 (S103). Further, the relative density D _i is acquired from the sensor output value ref _i by the above-described method according to the present embodiment, and the relative density is obtained (S104). Further, as shown in FIG. 13, an approximate straight line of the relative density D _i (i = 1, 2, 3) is acquired (S105). Then, the x-intercept and slope of the obtained approximate line by processing S105, the highlight offset _{x 0,} obtains a gradation gradient g (S106).

Furthermore, a highlight offset x ₀ and gradation gradient g obtained by the process of S106, by comparing the past highlight offset x ₀ and gradation gradient g obtained so far (S107), the result of the comparison, _{x 0} and g obtained by the process of S106 to determine whether an abnormal value (S108).

Incidentally, in S107, the previous x ₀ and g, for example past several times held in the history data 58 as shown in FIG. 3 for each color (e.g., three times, etc.) each of x _0, g of Deviations from the average value can be used. Further, the processing of S108 performs comparison between the deviation of the mean of the resulting x ₀ and g and the last few doses of x ₀ and g by treatment of S106, when it exceeds a preset allowable value, The calculated value obtained by the process of S106 is determined as an abnormal value. Note that the determination as to whether or not the value is an abnormal value in the process of S108 is, for example, determined that the calculated value obtained by the process of S106 is an abnormal value when the calculated value is outside a preset allowable range. Also good.

In the processing of S108, (in S108, NO) if it is determined not to be abnormal value, the value of _{x 0} and g in step S105 described above, among the past _{x 0} and g stored in the history data 58 An update process for replacing the oldest data is performed (S109). Also, tone correction data is generated based on the above-described equation (2) for the number of lines f of each threshold array registered in the threshold array table 56 (S110), and the generated tone correction is performed. The gradation correction data for the data table 55 is updated (S111).

  Here, it is determined whether or not the gradation correction data has been updated for all the line numbers f (S112), and the gradation correction data has not been updated for all the line numbers f. (NO in S112), the process returns to S110 to generate and update the gradation correction data for the total number of lines. Further, in the process of S112, when the update of the gradation correction data has been completed for all the line numbers f (YES in S112), the process is then performed for all colors K, C, M, and Y. It is determined whether or not it is completed (S113).

  Here, in the processing of S113, when the processing has not been completed for all the colors K, C, M, and Y (NO in S113), a series of S101 to S113 is performed according to the development process of K, C, M, and Y. Repeat the process.

  Further, if it is determined that the value is an abnormal value in the process of S108 described above (YES in S108), the operation panel 21 shown in FIG. 1 described above or a determination as to whether or not to continue can be made on the computer side such as a PC that has executed the print command. A warning is output together with a message prompting the user (S114), and it is further determined whether or not the instruction signal instructed by the user is continued (S115).

  Here, in the process of S115, when the instruction signal from the user is continued (YES in S115), the process of S109 to S112 related to the update of the gradation correction data is skipped and the process of S113 is continued.

  Further, if the instruction signal from the user is not continued in the process of S115 (NO in S115), a service call or a message for prompting the user to execute calibration by another method is issued as the abnormal termination process ( S116), the process is terminated. Further, in the process of S113, when the process is completed for all the colors K, C, M, and Y (YES in S113), the process ends.

  As described above, according to the invention, the gradation correction data corresponding to the halftone dot pattern of all the lines is generated from the halftone dot pattern of a specific number of lines, and the formation of the patch image per color is completed once. Therefore, calibration is realized with the minimum man-hour.

  The tone correction data is not the difference from the reference tone correction data, but is generated by calculation using the tone characteristic parameters and a predetermined function model. It is possible to calibrate the gradation characteristics of halftone dot patterns with an arbitrary number of lines lower or higher than the gradation characteristics of the pattern, giving priority to the gradation correction accuracy of the frequently used lines. However, an error in calibration accuracy over the entire number of supported lines can be reduced.

  In particular, as described above, the gradation characteristics are characterized by the minimum number of parameters by characterizing the gradation characteristics with the three minimum necessary parameters of highlight offset, gradation gradient, and maximum density as described above. Therefore, the number of gradation patches necessary to determine these is also reduced, and the effect of reducing the amount of color material consumed for purposes other than calibration man-hours and printing purposes is improved.

  Further, the gradation characteristic parameter is at least the maximum value of the output image density characteristic of the image forming apparatus with respect to the input gradation value to the gradation processing means for each color, and the highlight offset that is the input value at the beginning of the gradation By adopting a configuration including three parameters of the value and the gradation gradient which is the gradient of the rising edge of the gradation, modeling of gradation characteristics with a small number of parameters is realized.

<Other embodiments>
Here, in the case where the image forming apparatus according to the present invention includes an image reading unit capable of reading the print output of the image forming unit, the image reading unit also serves as the density detecting unit, so that the labor of the user is increased manually. Instead, it is possible to obtain an advantage that gradation correction with higher accuracy is possible. The above contents will be described below.

<Image forming system: system configuration example>
Here, FIG. 15 is a diagram illustrating an example of a system configuration of the image forming system in the present embodiment. FIG. 15 shows an example in which a system is constructed by integrating a scanner unit 81 as an image reading unit and a PC (Personal Computer) 82 connected to the printer engine 10 which is an image forming apparatus according to this embodiment. ing. Note that the operation panel 21 in the system configuration example shown in FIG. 15 is integrated with an interface on the scanner unit 81 side.

  The operation panel 21 is a liquid crystal display screen integrated with the touch panel, and displays system messages such as warning output through the operation panel 21 as shown in the gradation correction data generation processing procedure shown in FIG. It is also possible to specify parameters from the user, such as specifying the number of halftone lines.

  In this case, the user interface displayed on the monitor 83 by the operation panel 21 or the printer driver of the PC 82 serves as a halftone dot selection means for the user. In the above-described embodiment, the example in which the reflection luminance sensor 16 in the printer engine 10 is used as the density detection unit has been described. However, the present invention is not limited to this example. It is also possible to use the scanner unit 81 as a density detecting means by converting a value obtained by reading a medium or the like with the scanner unit 81 as a relative density D.

  When the scanner unit 81 is used as a density detection means, the user is required to evaluate the entire print output, while increasing the manual labor such as causing the scanner unit 81 to read an image. There is an advantage that tone patches can be measured and gradation correction can be performed with higher accuracy.

<User interface example of halftone dot selection means>
Next, an example of a user interface of halftone dot selection means will be described with reference to the drawings. FIG. 16 is a diagram showing a display example of the user interface of the halftone dot selection means. In FIG. 16, as an example, the user interface 84 has a tag 85 for moving to a display screen for performing various settings such as “basic setting”, “image quality mode”, “density setting”, and one form of selection means. A radio button 86 is displayed. The radio button 86 functions as an exclusive on / off switch. In the example of FIG. 16, any one of “gradation priority”, “standard”, and “resolution priority” can be selected as the image quality mode.

  FIG. 17 is a diagram illustrating an example of assignment of the number of halftone lines. FIG. 17 specifically shows an example of assignment of the actual number of halftone lines for each mode selected by the radio button shown in FIG. Here, the selection signal in FIG. 17 corresponds to the selection signal input when the gradation correction data table 55 and the threshold array table 56 shown in FIG. 3 described above are generated.

In the example of FIG. 17, in the selection signal, the upper 2 bits correspond to the line number selection signal 52 and the lower 2 bits correspond to the color selection signal 51. The displacement vector is a vector corresponding to the amount of displacement between adjacent halftone dots, and is shown in units of pixels. In this case, assuming that the displacement vector is v and the number of halftone lines is f (lpi), in the case of an image forming apparatus with 600 (dpi) resolution, f = 600 / || v || and (screen angle) = (v ) And the area of the halftone dot region is || v || ² .

  Therefore, with the above-described configuration of the image forming apparatus, highly accurate gradation correction can be realized. Therefore, a highly accurate image can be formed.

<Image formation program>
Here, the image forming apparatus 10 described above can also perform image formation in the present invention using the dedicated apparatus configuration described above, but generates an execution program for causing a computer to execute the processing in each configuration, For example, the image formation according to the present invention can be realized by installing the program in a control unit such as a general-purpose personal computer, a server, or a controller of the image forming apparatus.

<Hardware configuration>
Here, a hardware configuration example of a computer capable of executing the image forming process according to the present invention will be described with reference to the drawings. FIG. 18 is a diagram illustrating an example of a hardware configuration capable of realizing the image forming process according to the present invention.

  18 includes an input device 91, an output device 92, a drive device 93, an auxiliary storage device 94, a memory device 95, a CPU (Central Processing Unit) 96 that performs various controls, and a network connection device. 97 are connected to each other by a system bus B.

  The input device 91 includes a keyboard and a pointing device such as a mouse operated by a user, a voice input device, and the like, and inputs various operation signals and voice signals such as a program execution instruction from the user. The output device 92 has a display, a speaker, and the like that display various windows and data necessary for operating the computer main body for performing the processing according to the present invention. Display or audio output is possible.

  Here, in the present invention, the execution program installed in the computer main body is provided by a recording medium 98 such as a CD-ROM or DVD, for example. The recording medium 98 on which the program is recorded can be set in the drive device 93, and the execution program included in the recording medium 98 is installed in the auxiliary storage device 94 from the recording medium 98 via the drive device 93.

  Further, the drive device 93 can record the execution program according to the present invention in the recording medium 98. Thus, the recording medium 98 can be used for easy installation on a plurality of other computers, and an image forming process can be easily realized.

  The auxiliary storage device 94 is a storage means such as a hard disk, and can store an execution program according to the present invention, a control program provided in a computer, and the like, and can perform input / output as necessary. The auxiliary storage device 94 can also be used as a storage means for storing various data according to the present invention described above.

  The memory device 95 stores an execution program or the like read from the auxiliary storage device 94 by the CPU 96. The memory device 95 includes a ROM (Read Only Memory), a RAM (Random Access Memory), and the like.

  Based on a control program such as an OS (Operating System) and an execution program read from the auxiliary storage device 94 and stored in the memory device 95, the CPU 96 inputs various calculations and data to each hardware component. Each processing in image formation can be realized by controlling processing of the entire computer such as output. Various information necessary during the execution of the program can be acquired from the auxiliary storage device 94 and stored.

  The network connection device 97 obtains an execution program from another terminal connected to the communication network or executes the program by connecting to a communication network such as a telephone line or a LAN (Local Area Network) cable. The execution result obtained in this way or the execution program in the present invention can be provided to other terminals or the like.

  With the hardware configuration as described above, an image forming process can be realized at a low cost without requiring a special device configuration. Further, by installing the program, the image forming process can be easily realized as software.

  As a result, the image forming program and various data are loaded into the memory device 95, and the CPU 96 executes the program using the data to perform the image forming process according to the present embodiment. Therefore, highly accurate gradation correction can be realized. In addition, a highly accurate image can be formed. Further, by installing the program, the image formation in the present invention can be easily realized by a general-purpose personal computer or the like.

  As described above, according to the present invention, highly accurate gradation correction can be realized. In addition, a highly accurate image can be formed. Specifically, the stored reference image data is subjected to gradation processing by a halftone dot pattern having a specific number of lines, a patch image is formed by the image forming means, and the density detection means for the formed patch image The gradation characteristic parameter of the gradation correction means is extracted by the gradation correction data generation means from the image density characteristic based on the detected value. Further, the gradation correction data generating means supports all halftone dot patterns selected by the halftone dot selecting means by calculation based on a predetermined function model characterized by the extracted gradation characteristic parameters. Tone correction data to be generated is generated. As a result, the gradation correction data corresponding to the halftone dot pattern of all lines is generated from the halftone dot pattern of a specific number of lines, and the formation of the patch image for each color is completed once. Calibration is realized.

  The tone correction data is not the difference from the reference tone correction data, but is generated by calculation using the tone characteristic parameters and a predetermined function model. It is possible to calibrate the gradation characteristics of halftone dot patterns with an arbitrary number of lines lower or higher than the gradation characteristics of the pattern, giving priority to the gradation correction accuracy of the frequently used lines. However, an error in calibration accuracy over the entire number of supported lines can be reduced.

  In particular, the gradation characteristics are approximated with the minimum number of parameters by characterizing the gradation characteristics with the minimum and required three parameters of highlight offset, gradation gradient, and maximum density as gradation characteristic parameters. The number of gradation patches necessary for determining these is also reduced, and the effect of reducing the amount of color material consumed for purposes other than calibration man-hours and printing purposes is improved. Further, in the present invention, when the reference image needs to be held, the data capacity of the reference image can be reduced, so that the load on the apparatus mounting can be reduced.

  Further, the gradation characteristic parameter is at least the maximum value of the output image density characteristic of the image forming apparatus with respect to the input gradation value to the gradation processing means for each color, and the highlight offset which is the input value at the beginning of the gradation By adopting a configuration including three parameters of the value and the gradation gradient which is the gradient of the rising edge of the gradation, modeling of gradation characteristics with a small number of parameters is realized.

  Further, when the image forming apparatus includes an image reading unit that can read the print output of the image forming unit, the image reading unit also serves as the density detection unit, thereby enabling more accurate gradation correction. Benefits are gained.

  The image forming apparatus, the image forming method, and the image forming program of the present invention can be provided in the field of image forming processing that performs gradation expression using digital halftone dots such as a copying machine and a printer that support a plurality of halftone lines. it can. In particular, the present invention is effective for reducing the number of calibration steps and reducing the cost of a color image forming apparatus that superimposes many primary colors for image reproduction.

  Although the preferred embodiment of the present invention has been described in detail above, the present invention is not limited to the specific embodiment, and various modifications, within the scope of the gist of the present invention described in the claims, It can be changed.

1 is a diagram illustrating a configuration example of an image forming apparatus according to an exemplary embodiment. It is a figure which shows an example of a function structure of the image forming apparatus in this invention in this invention. It is a figure which shows an example of the image formation process sequence in this embodiment. It is a figure which shows an example of a basic threshold pattern. It is a figure which shows an example of the table entry corresponding to a threshold value arrangement | sequence. It is a figure which shows an example of the patch image formed on a photoreceptor. FIG. 3 is a diagram illustrating an example of a gradation characteristic model of the image forming apparatus according to the present embodiment. It is an example for demonstrating the relationship between highlight offset and a halftone dot area | region. The relationship between the halftone frequency f and highlights the offset value x ₀ is a diagram showing an example of approximating by a quadratic function of f. It is a figure which shows an example of the 4 * 4 halftone dot area | region corresponding to the input gradation value x = 4/16 to a gradation process means. It is a figure which shows an example which approximated the relationship between the number of halftone lines f and the gradation gradient g with a function model. It is a figure which shows an example of the patch image formed on a photoconductor. It is a figure which shows an example of the relationship between an input gradation and relative density. It is a flowchart which shows an example of a gradation correction data generation process procedure. 1 is a diagram illustrating an example of a system configuration of an image forming system in the present embodiment. It is a figure which shows the example of a display of the user interface of a halftone dot selection means. It is a figure which shows an example of allocation of the number of halftone lines. It is a figure which shows an example of the hardware constitutions which can implement | achieve the image formation process in this invention.

Explanation of symbols

10 Printer engine (image forming device)
11 Photoconductor (Photosensitive member)
12 Intermediate transfer member 13 Developer 14 Charger 15 Exposure device 16 Reflection luminance sensor (luminance detection means)
17 Controller (control means)
18 Transfer roller 19 Cassette section 20 Fixing device 21 Operation panel (operation means)
DESCRIPTION OF SYMBOLS 30 Image forming apparatus 31 Input means 32 Output means 33 Accumulation means 34 Image development means 35 Color correction means 36 Reference image generation means 37 Reference image holding means 38 4 Color separation means 39 Halftone dot selection means 40 Color selection means 41 Tone correction data Generation means 42 Gradation correction means 43 Gradation processing means 44 Density detection means 45 Image forming means 46 Transmission / reception means 47 Control means 51 Color selection signal 52 Number of lines selection signal 53 Gradation correction data 54 Threshold array 55 Gradation correction data table 56 Threshold array table 57, 71, 72, 73, 74 Patch image 58 History data 60, 62, 64 Halftone dot 61, 63 Halftone dot area 65 Logical halftone dot 70 Marker 81 Scanner unit 82 PC
83 Monitor 84 User interface 85 Tag 86 Radio button (selection means)
91 Input Device 92 Output Device 93 Drive Device 94 Auxiliary Storage Device 95 Memory Device 96 CPU
97 Network connection device 98 Recording medium

Claims (21)

In an image forming apparatus for forming a tone-corrected image,
Halftone dot selecting means for selecting a specific halftone dot pattern from a plurality of different halftone dot patterns set in advance;
A gradation processing means for associating an input gradation value with the area ratio of the halftone dots of the output image by the halftone dot pattern obtained by the halftone dot selection means;
Gradation correction means for correcting the input gradation value based on gradation correction data;
Image forming means for forming an image based on the output from the gradation processing means;
Density detecting means for detecting the density of an image obtained by the image forming means;
Gradation correction data generation means for generating gradation correction data of the gradation correction means based on a detection value obtained by the density detection means;
Reference image holding means for holding a reference image composed of gradation patches composed of a plurality of gradations;
The gradation correction data generation means, of the number of lines f of selectable dot pattern in the dot selecting means, the dot of the intermediate one ruling f ₀ output from the reference image holding means Based on the detected value of the density detection means in the reference image by a pattern, a gradation characteristic parameter characterizing a gradation characteristic is extracted, and the halftone dot is calculated by an operation using the gradation characteristic parameter and a predetermined function model. An image forming apparatus for generating gradation correction data corresponding to a halftone dot pattern having an arbitrary number of lines selected by a selection unit. In an image forming apparatus for forming a tone-corrected image,
Halftone dot selecting means for selecting a specific halftone dot pattern from a plurality of different halftone dot patterns set in advance;
A gradation processing means for associating an input gradation value with the area ratio of the halftone dots of the output image by the halftone dot pattern obtained by the halftone dot selection means;
Gradation correction means for correcting the input gradation value based on gradation correction data;
A reference image generating means for generating a reference image composed of gradation patches composed of a plurality of gradations;
Image forming means for forming an image of a reference image composed of gradation patches of a plurality of gradations based on an output from the gradation processing means or the reference image generation means ;
Density detecting means for detecting the density of an image obtained by the image forming means;
Gradation correction data generation means for generating gradation correction data of the gradation correction means based on the detection value obtained by the density detection means;
The gradation correction data generation means, of the number of lines f of selectable dot pattern in the dot selecting means, wherein in the reference image by an intermediate one of said dot pattern with a line number f ₀ concentration detection Based on the detected value of the means, a gradation characteristic parameter characterizing the gradation characteristic is extracted,
An image characterized by generating gradation correction data corresponding to a halftone dot pattern of an arbitrary number of lines selected by the halftone dot selection means by an operation using the gradation characteristic parameter and a predetermined function model. Forming equipment. At least one of the gradation characteristic parameters is a highlight offset x which is a rising gradation value of density. ₀ The image forming apparatus according to claim 1, wherein the image forming apparatus is an image forming apparatus. The image forming apparatus according to claim 1, wherein the gradation characteristic parameter is three or less . The gradation characteristic parameter is:
At least the maximum value of the output image density characteristic of the image forming apparatus with respect to the input gradation value to the gradation processing means, the highlight offset value that is the input value at the beginning of the gradation rise, and the floor that is the gradient of the gradation rise The image forming apparatus according to claim 1, wherein the image forming apparatus has three parameters of a gradient. In an image forming apparatus that forms a color image by superimposing colors by image formation of at least three colors,
Halftone dot selecting means for selecting a combination of halftone dot patterns designated by the user from a plurality of halftone dot pattern combinations for image formation of each color;
Gradation processing means for associating the input gradation value with the area ratio of the halftone dots of the output image based on the halftone dot pattern selected by the halftone dot selection means;
Gradation correction means for correcting the input gradation value based on gradation correction data;
Image forming means for forming an image based on the output of the gradation processing means;
Density detecting means for detecting the density of an image obtained by the image forming means;
Gradation correction data generation means for generating gradation correction data of the gradation correction means for each color based on the detection value obtained by the density detection means;
Reference image holding means for holding a reference image composed of gradation patches composed of a plurality of gradations;
The gradation correction data generation means includes one intermediate line number f determined for each color output from the reference image holding means, out of the line number f of the halftone dot pattern selectable by the halftone dot selection means. Based on the detected value of the density detecting means in the reference image by the halftone dot pattern of _0, a gradation characteristic parameter characterizing the gradation characteristic is extracted,
Generating gradation correction data corresponding to a halftone dot pattern of an arbitrary number of lines for each color selected by the halftone dot selection means by an operation using the gradation characteristic parameter and a predetermined function model; Image forming apparatus. The gradation characteristic parameter is:
At least the maximum value of the output image density characteristic of the image forming apparatus with respect to the input gradation value to the gradation processing means for each color, the highlight offset value that is the input value at the beginning of the gradation rise, and the slope of the gradation rise The image forming apparatus according to claim 6 , wherein the image forming apparatus has three parameters of gradation gradient. Highlight offset x ₀ The functional model of
x ₀ = X ₀ (F ₀ ) ・ (F / f ₀ ) ²
(Where f: general number of halftone dots, f ₀ : Specific number of halftone dots, x ₀ (F ₀ ): Specific number of halftone lines f ₀ Highlight highlight value for each color)
The image forming apparatus according to claim 3, wherein the image forming apparatus is an image forming apparatus. The predetermined function model is:
D ^-1 (X) = x ₀ + (1-x ₀ ) {1- (1-x) ^{1 / {(1-x0) g}} }
(Where g: gradation gradient, x: input gradation value),
The function model of gradation gradient g is
g = xx ₀ (F) + A · Sqrt (xx ₀ (F)) ・ f
(Where A: constant, x> x ₀ , Sqrt: positive square root)
The image forming apparatus according to claim 8, wherein the image forming apparatus is determined by: In place of the density detection means, it has an image reading means capable of reading the print output of the image forming apparatus,
Wherein the image reading means, the image forming apparatus according to any one of claims 1 to 9, characterized in that for detecting the concentration of an image obtained by said image forming means. In an image forming method in an image forming apparatus for forming a tone-corrected image,
A halftone dot selection step of selecting a specific halftone dot pattern from a plurality of different halftone dot patterns set in advance;
A gradation processing step of associating an input gradation value with the area ratio of the halftone dots of the output image by the halftone dot pattern obtained by the halftone dot selection step;
A gradation correction step for correcting the input gradation value based on gradation correction data;
An image forming step of forming an image based on the output of the gradation processing step;
A density detecting step for detecting the density of the image obtained by the image forming step;
A gradation correction data generation step for generating gradation correction data of the gradation correction step based on the detection value obtained by the density detection step;
A reference image holding step for holding a reference image composed of gradation patches composed of a plurality of gradations,
The gradation correction data generating step, among the number of lines f of selectable dot pattern in the dot selecting step, said dot of intermediate one ruling f ₀ output from the reference image holding step A gradation characteristic parameter characterizing gradation characteristics is extracted based on a detection value of the density detection step in the reference image by a pattern , and the halftone dot is calculated by using the gradation characteristic parameter and a predetermined function model. An image forming method comprising: generating gradation correction data corresponding to a halftone dot pattern having an arbitrary number of lines selected in the selection step. In an image forming method in an image forming apparatus for forming a tone-corrected image,
A halftone dot selection step of selecting a specific halftone dot pattern from a plurality of different halftone dot patterns set in advance;
A gradation processing step of associating an input gradation value with the area ratio of the halftone dots of the output image by the halftone dot pattern obtained by the halftone dot selection step;
A gradation correction step for correcting the input gradation value based on gradation correction data;
A reference image generation step for generating a reference image composed of gradation patches composed of a plurality of gradations;
An image forming step of forming an image of a reference image composed of a plurality of gradation patches based on the output from the gradation processing step or the reference image generation step ;
A density detecting step for detecting the density of the image obtained by the image forming step;
A gradation correction data generation step for generating gradation correction data of the gradation correction step based on the detection value obtained by the density detection step;
The gradation correction data generating step, among the number of lines f of selectable dot pattern in the dot selection step, the in the reference image by an intermediate one of said dot pattern with a line number f ₀ concentration detection Based on the detected value of the step, the gradation characteristic parameter characterizing the gradation characteristic is extracted,
An image characterized by generating gradation correction data corresponding to a halftone dot pattern having an arbitrary number of lines selected by the halftone dot selection step by an operation using the gradation characteristic parameter and a predetermined function model. Forming method. At least one of the gradation characteristic parameters is a highlight offset x which is a rising gradation value of density. ₀ The image forming method according to claim 11, wherein the image forming method is an image forming method. 13. The image forming method according to claim 11, wherein the gradation characteristic parameter is three or less. The gradation characteristic parameter is:
At least the maximum value of the output image density characteristic of the image forming apparatus with respect to the input gradation value to the gradation processing step, the highlight offset value that is the input value at the beginning of the gradation rise, and the floor that is the gradient of the gradation rise The image forming method according to claim 11, wherein the image forming method has three parameters of a gradient. In an image forming method in an image forming apparatus for forming a color image by superimposing colors by image formation of at least three colors,
A halftone dot selecting step for selecting a combination of halftone dot patterns designated by the user from a plurality of halftone dot pattern combinations for image formation of each color;
A gradation processing step for associating the input gradation value with the area ratio of the halftone dots of the output image based on the halftone dot pattern selected by the halftone dot selection step;
A gradation correction step for correcting the input gradation value based on gradation correction data;
An image forming step of forming an image based on the output of the gradation processing step;
A density detecting step for detecting the density of the image obtained by the image forming step;
A gradation correction data generation step for generating gradation correction data of the gradation correction step for each color based on the detection value obtained by the density detection step;
A reference image holding step for holding a reference image composed of gradation patches composed of a plurality of gradations,
The gradation correction data generation step includes one intermediate line number f determined for each color output from the reference image holding step out of the line number f of the halftone dot pattern selectable in the halftone dot selection step. Based on the detection value of the density detection step in the reference image by the halftone dot pattern of _0, a gradation characteristic parameter characterizing the gradation characteristic is extracted,
Generating gradation correction data corresponding to a halftone dot pattern of an arbitrary number of lines for each color selected by the halftone dot selection step by an operation using the gradation characteristic parameter and a predetermined function model; Image forming method. The gradation characteristic parameter is:
At least the maximum value of the output image density characteristics of the image forming apparatus with respect to the input gradation value to the gradation processing step for each color, the highlight offset value that is the input value at the beginning of the gradation rise, and the slope of the gradation rise The image forming method according to claim 16 , wherein the image forming method has three gradation gradient parameters. Highlight offset x ₀ The functional model of
x ₀ = X ₀ (F ₀ ) ・ (F / f ₀ ) ²
(Where f: general number of halftone dots, f ₀ : Specific number of halftone dots, x ₀ (F ₀ ): Specific number of halftone lines f ₀ Highlight highlight value for each color)
The image forming method according to claim 13, wherein: The predetermined function model is:
D ^-1 (X) = x ₀ + (1-x ₀ ) {1- (1-x) ^{1 / {(1-x0) g}} }
(Where g: gradation gradient, x: input gradation value),
The function model of gradation gradient g is
g = xx ₀ (F) + A · Sqrt (xx ₀ (F)) ・ f
(Where A: constant, x> x ₀ , Sqrt: positive square root)
The image forming method according to claim 18, wherein the image forming method is determined by: In place of the density detection step, an image reading step capable of reading the print output of the image forming apparatus,
The image forming method according to claim 11 , wherein the image reading step detects a density of an image obtained by the image forming step. An image forming program for causing a computer to execute the image forming method according to any one of claims 11 to 20 .

Images