JP2016127479A - Image processor, image forming apparatus, image processing method and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To reduce density shortage of a high density part and a deterioration in sharpness in a steep part of a thin line, an edge part, or the like while suppressing density fluctuation due to a landing position deviation in each dot group.SOLUTION: An image processor for generating a plurality of pieces of halftone image data to be used by image formation means for forming an image based on input image data on a recording medium by overlapping dot groups of different dot patterns in the same region includes halftone processing means for converting the input image data into a plurality of pieces of halftone image data by halftone processing. In a dot pattern represented by at least two pieces of halftone image data among the plurality of pieces of halftone image data by the halftone processing means, a portion of dots overlaps, and a ratio of the overlapping dots occupying the dot pattern is different in accordance with density in the input image data.SELECTED DRAWING: Figure 5

Description

  The present invention relates to image processing for creating a dot pattern suitable for image formation.

  As an apparatus that outputs an image processed by a personal computer, an image captured by a digital camera, or the like, an apparatus that forms an image using dots on a recording medium is often used. Among such image forming apparatuses, a system for forming an image on a recording medium by attaching a coloring material to the recording medium has been widely put into practical use, and an ink jet recording system is known as a typical example. An image forming apparatus that employs an ink jet recording system includes a nozzle group in which a plurality of ink discharge ports (nozzles) that can discharge ink of the same color and the same density are arranged in an integrated manner in order to improve recording speed and improve image quality. . In order to improve image quality, there are nozzle groups that can eject ink of the same color and different density, and nozzle groups that can eject by changing the ejection amount of ink of the same color and the same density in several stages. It may be provided. In some cases, a plurality of nozzle groups are arranged.

  As typical examples of such an ink jet recording method, there are a multi-pass method and a full line method. In the multi-pass method, a recording head having a nozzle group is main-scanned relatively to the recording medium, and the recording medium is less than the length of the nozzle group in the sub-scanning direction substantially perpendicular to the main-scanning direction. An image is formed by repeatedly performing an operation of conveying with a carry amount. In the full line method, an image is formed by relatively scanning the recording head and the recording medium using a recording head having a plurality of nozzle groups having a length that covers the width of the recording medium. In either method, a final image is formed by overlapping different dot groups in a plurality of times of recording in the same recording area of the recording medium.

  In such image formation, it is known that the image quality of the finally formed image is affected by the difference in the image in which each dot group overlaps (that is, the ink dot arrangement). In an actual image forming apparatus, for example, it is difficult to make physical registration fluctuations such as the conveyance amount of the recording medium and the displacement of the nozzles zero, so the ink landing position for each dot group is the target position. It is inevitable that it will deviate. Then, the deviation of the ink landing position for each dot group causes image quality deterioration such as density fluctuation, and an intended image is not formed when the dot group is recorded a plurality of times.

  In this regard, conventionally, there has been proposed a technique for generating a dot group for suppressing density fluctuations due to landing position deviation for each dot group. Patent Document 1 discloses a technique for suppressing density fluctuations by controlling the amount of dot overlap between passes in a multi-pass method.

  A technique for forming an image at a high speed and with a high resolution by using a plurality of heads or a plurality of scans in the recording direction has also been proposed. Patent Document 2 discloses a technique related to a so-called column thinning recording method. When the same raster is recorded by being divided into a plurality of scans, the positions of dots formed in each scan are moved in the main scanning direction by a distance equal to or less than the basic resolution. A technique for performing shifting control is disclosed. In this technique, in the case of two scans, even and odd columns of print data are printed by separate scans. Patent Document 3 discloses a technique related to a so-called multi-row head recording method in which a plurality of recording heads are arranged in the transport direction to form an image. Ink of the same color is supplied to the plurality of recording heads and the transport speed of the printing paper is A technique for increasing the ratio by two times or more is disclosed. In this technique, in the case of two heads, it is only necessary to record half of the image data with each recording head in the transport direction, so that the transport speed of the printing paper can be doubled compared to the case of one head.

  Both Patent Document 2 and Patent Document 3 complete an image using a plurality of scans or a plurality of recording heads in the recording direction, and as described above, landing position deviation is likely to occur for each dot group. In such a recording method, by applying the dot overlap amount control of Patent Document 1, it is possible to suppress density fluctuations due to landing position deviation for each dot group.

JP 2011-87262 A JP 2003-291323 A JP-A-2005-14436

  In the conventional column thinning recording method and multi-row head recording method, if dots are overlapped in order to suppress density fluctuations due to landing position deviation for each dot group, the dots are placed before and after the main scanning direction or the paper transport direction. Pixels that cannot be arranged are generated, resulting in image quality degradation. The image quality deterioration here means insufficient density at a high density portion of an image, or reduction of sharpness at a steep portion such as a fine line or an edge portion. For example, in a two-row head recording method using two recording heads, each recording head continuously discharges ink droplets at the maximum discharge frequency, and corresponds to each recording head in the transport direction on the printing paper. Assume that images are formed so that dots are alternately arranged. In this case, if some dots are overlapped, the ink supply to the nozzles cannot catch up with the pixels before and after that, and a phenomenon occurs in which no recording head can record dots. In particular, the above problem becomes apparent under recording conditions that require high-speed image formation.

  Therefore, an object of the present invention is to generate halftone image data for outputting a high-quality image when an image is formed using a plurality of scanning or recording heads.

  An image processing apparatus according to the present invention uses an image based on input image data in a plurality of halves for use in an image forming unit that forms a dot group of different dot patterns on a recording medium by overlapping the same region. An image processing apparatus for generating tone image data, comprising: halftone processing means for converting input image data into a plurality of halftone image data by a halftone process, and the plurality of halftones by the halftone processing means In the dot pattern represented by at least two halftone image data of the image data, some of the dots overlap, and the proportion of the overlapping dots in the dot pattern varies depending on the density in the input image data. It is characterized by.

  According to the present invention, when an image is formed using a plurality of scanning or recording heads, halftone image data for outputting a high-quality image can be generated. .

1 is a block diagram illustrating a configuration example of a printing system. FIG. 3 is a block diagram illustrating an internal configuration of a halftone processing unit according to the first embodiment. It is a figure explaining the halftone process by a general dither method. It is a flowchart which shows the flow of a halftone process (quantization process). FIG. 3 is a diagram illustrating a configuration example of a recording head. It is a figure showing an example of the pixel position which can be recorded by each of the 1st nozzle group and the 2nd nozzle group. 6 is a flowchart illustrating a flow of a threshold matrix creation method according to the first embodiment. (A) is a figure which shows an example of a unit potential, (b) is a figure which shows an example of the potential map corresponding to the dot arrangement | positioning in which four ON dots exist. It is a flowchart which shows the detail of the process which adds an on dot to the Mth gradation. It is a graph which shows the phase difference of the pattern A produced when the value of the vertex of a unit potential is changed. 6 is a flowchart illustrating a flow of the entire printing process. It is the table | surface which showed the relationship of the overlapping rate of dot groups with respect to the combination of the image area and gradation value of an input image. It is a graph which shows an example of the relationship between the gradation and dot overlap rate in a flat part. FIG. 10 is a block diagram illustrating an internal configuration of a halftone processing unit according to a second embodiment. 10 is a flowchart illustrating a flow of a threshold matrix creation method according to the second embodiment. It is a flowchart which shows the detail of a non-common threshold value matrix candidate creation process. The process of creating a comprehensive potential map is illustrated.

  Hereinafter, the present invention will be described in detail based on preferred embodiments with reference to the accompanying drawings. In addition, the structure shown in the following Examples is only an example, and this invention is not limited to the structure shown in figure.

[Example 1]
FIG. 1 is a block diagram illustrating a configuration example of a printing system according to the present embodiment. The printing system 100 includes an image processing apparatus 110 and an image forming apparatus 120, and is connected to each other.

  The image processing apparatus 110 is an apparatus such as a general personal computer (PC) in which a printer driver is installed, and functions described below are realized by a CPU in the PC executing a predetermined program.

  The image processing apparatus 110 includes an input image buffer 111, an image feature extraction unit 112, a color separation processing unit 113, a halftone processing unit 114, and a halftone image buffer 115.

  The input image buffer 111 stores input image data to be printed (for example, color image data) input to the image processing apparatus 110. Color image data is generally composed of three color components of red (R), green (G), and blue (B).

  The image feature extraction unit 112 acquires input image data from the input image buffer 111 and extracts features of the input image. Here, the extracted features include information regarding the image area and information regarding the gradation value. First, for the image area, image area determination is performed on the input image data, and whether each pixel constituting the input image data belongs to a flat part where the density change is small or a steep part where the density change such as a thin line or an edge is large. Determine if it belongs. As an image area determination method, for example, various edge detection processes such as a high-pass filter, a Sobel filter, and a Laplacian filter are applied to the input image data to determine whether it is a flat portion or a steep portion according to the amount of the edge portion. Is done. The size of the filter at this time can be arbitrary, for example, 3 × 3. Alternatively, when image area information is added to the input image data from the beginning, the information may be referred to determine whether the portion is flat or steep. A specific method for determining the image area is not limited. Next, for the gradation value, the gradation value of each pixel (that is, the pixel value for each target pixel to be processed) is acquired from the input image data. Alternatively, a value derived based on the pixel value of the pixel of interest and the pixel values of pixels around it may be used as the gradation value to be processed. As a method of acquiring the gradation value, various processes such as an average value filter and a weighted average value filter may be used. At this time, the size of each filter can be arbitrarily set to 3 × 3, for example. Note that both image area determination and gradation value acquisition are not essential, and only one of them may be performed. That is, only the image area determination result may be used as the image feature information, or only the gradation value information may be used as the image feature information.

  The color separation processing unit 113 separates the input RGB color image data into image data corresponding to the color of the color material included in the image forming apparatus 120. In this color separation process, a color separation lookup table (not shown) is used. In this embodiment, a case where color conversion to black (K) single color will be described as an example. In the case of forming a color image on a recording medium, for example, color separation processing may be performed on four colors of cyan (C), magenta (M), yellow (Y), and black (K). In this embodiment, the image data after color separation is handled as 8-bit data representing 256 gradations from 0 to 255, but conversion to a gradation number higher than that may be performed. A configuration in which CMYK color image data is input from the beginning and the color separation processing unit 113 is skipped may be employed.

  A halftone processing unit (quantization processing unit) 114 generates halftone image data based on post-color separation image data obtained from the color separation processing unit 113. Specifically, using a plurality of threshold matrixes, conversion to the number of gradations that can be directly expressed by the image forming apparatus 120 (quantization) and determination of the dot arrangement (dot pattern) formed by each nozzle group of the recording head I do. In this embodiment, there are two nozzle groups for each color, and each of them converts 8-bit color-separated image data into 1-bit (binary) data. Details of the processing will be described later. At this time, the color image is processed individually for each color using, for example, a plurality of threshold matrixes prepared for each color of CMYK. The generated halftone image data is sent to the halftone image buffer 115.

  The halftone image buffer 115 is a buffer for temporarily storing the halftone image data generated by the halftone processing unit 114. The halftone image data stored in the halftone image buffer is output to the image forming apparatus 120 as appropriate.

  The image forming apparatus 120 includes a head driving circuit 121 and a recording head 122. The image forming apparatus 120 forms an image on the recording medium by moving the recording medium relative to the recording head 122 based on the halftone image data received from the image processing apparatus 110. In this embodiment, the image forming apparatus 120 is a full line system, and the recording head 122 is an ink jet recording system. The head drive circuit 121 generates a drive signal corresponding to each nozzle group for controlling the recording head 122.

  The recording head 122 includes two nozzle groups (first nozzle group and second nozzle group) for each color so as to cover the width direction of the recording medium, and each nozzle group has the same color and the same density of ink. A plurality of nozzles capable of discharging the gas are integrated and arranged. Then, the two nozzle groups are installed at a fixed distance with respect to the recording medium conveyance direction, and a final image is formed by superimposing partial images formed by ink dots based on the drive signals corresponding to the nozzle groups. An image is formed on the recording medium. Note that the image forming apparatus 120 may include the image processing apparatus 110, or the whole may be an image forming apparatus.

[Halftone processing section]
Next, details of the halftone processing unit 114 according to the present embodiment will be described. FIG. 2 is a block diagram illustrating an internal configuration of the halftone processing unit 114 according to the present embodiment. The halftone processing unit 114 includes a threshold matrix selection unit 201, a memory 202, a comparison unit 203, and a halftone image generation unit 204. Here, an outline of the halftone process will be described.

  FIG. 3 is a diagram for explaining halftone processing by a general dither method. The threshold value matrix 302 has a width = 4 pixels and a height = 4 pixels, and one threshold value “0 to 15” is stored in each pixel. Here, if the input pixel value is greater than or equal to the threshold value, an on dot (dot is applied) is output, and if the input pixel value is less than the threshold value, an off dot (dot is not applied) is output. Output. Therefore, when this threshold value matrix 302 is used, a dot arrangement of 17 gradations is obtained. For example, the input image 301 is an image having a single pixel value “3” and having a width = 4 pixels and a height = 4 pixels. When the threshold matrix 302 is applied to the input image 301, the output image 303 is displayed. can get. In this embodiment, halftone processing is performed by applying threshold matrixes having different dot arrangements corresponding to the first nozzle group and the second nozzle group, respectively. Hereinafter, each part which comprises the halftone process part 114 is demonstrated.

  In the memory 202, a threshold matrix set (one set of a threshold matrix for the dot group formed by the first nozzle group and a threshold matrix for the dot group formed by the second nozzle group ( Hereinafter, N threshold matrix sets) are held. N threshold matrix groups, each of which has a threshold matrix corresponding to each of the different dot arrangements, are “1 to N”, and the first nozzle group and the second nozzle group are “# 1” and “#”. 2 ”. As shown in FIG. 2, after each threshold matrix, “1_ # 1”, “2_ # 1”,..., “N_ # 1” and “1_ # 2”, “2_ # 2”, ..., an identification number such as “N_ # 2” is assigned.

  The threshold matrix selection unit 201 selects one threshold matrix set to be used for halftone processing from the N threshold matrix sets based on the above-described image feature information.

  The comparison unit 203 compares the pixel value of the input image data with the threshold value at the corresponding position in the threshold value matrix of the selected threshold value matrix set.

  The halftone image generation unit 204 generates and outputs halftone image data for each nozzle group based on the comparison result of the comparison unit 203.

  FIG. 4 is a flowchart showing a flow of halftone processing (quantization processing) in the halftone processing unit 114.

  In step 401, the threshold matrix selection unit 201 selects one threshold matrix set i to be used from among N threshold matrix sets based on the above-described image feature information. In this case, i is any value from 1 to N.

  In step 402, it is determined whether to generate halftone image data for the first nozzle group or to generate halftone image data for the second nozzle group.

  In step 403, the threshold matrix selection unit 201 reads and acquires a threshold matrix corresponding to the nozzle group determined as the processing target from the threshold matrix set selected in step 401. For example, if a threshold matrix set of i = 2 is selected in step 401 and the first nozzle group is determined as a processing target nozzle group in step 402, “threshold matrix 2_ # 1” is acquired. become.

  In step 404, a pixel to be compared (hereinafter referred to as a pixel of interest) among the pixels in the input image data is determined. In this case, since the threshold value matrix is selected based on the above-described image feature information, the target pixel determined here is determined from the region corresponding to the image feature in the input image.

  In step 405, the comparison unit 203 compares the pixel value of the target pixel determined in step 404 with the threshold value of the corresponding position in the threshold value matrix acquired in step 403. Specifically, the pixel value of the pixel of interest at the coordinates (x, y) in the input image data In is In (x, y), and the threshold value of the corresponding position (x% W, y% H) in the threshold matrix is matrix ( x% W, y% H) and compare the two. Here, “%” represents the remainder, and “W” and “H” represent the width and height of the threshold value matrix, respectively. In this way, pixel values are compared so that a threshold matrix is repeatedly assigned to input image data. As a result of the comparison, if the pixel value of the target pixel represented by In (x, y) is equal to or larger than the threshold value of the threshold value matrix, the process proceeds to step 406. On the other hand, if the pixel value of the target pixel is less than the threshold value matrix threshold value, the process proceeds to step 407.

  In step 406, the halftone image generation unit 204 determines a value representing dot-on (on-dot), for example, “1” as an output pixel value for the target pixel.

  In step 407, the halftone image generation unit 204 determines a value indicating that dots are not applied (off dot), for example, “0” as the output pixel value of the target pixel.

  In step 408, it is determined whether there is an unprocessed pixel that has not been processed as a target pixel. If there is an unprocessed pixel, the process returns to step 404 to continue the process with the next pixel as the target pixel. On the other hand, if all the pixels in the area corresponding to the image feature of the input image data have been processed, the process proceeds to step 409.

  In step 409, it is determined whether or not the processing has been completed for all the nozzle groups (both the first nozzle group and the second nozzle group in this embodiment). If there is an unprocessed nozzle group, the process returns to step 402, the next nozzle group is determined as a nozzle group for generating a halftone image, and the process is continued. On the other hand, if the processing has been completed for all the nozzle groups (that is, if halftone images have been generated for all the nozzle groups), this processing ends.

  Halftone processing as described above is executed in units of image features of the input image, and halftone image data for each nozzle group for the entire input image is generated. The generated halftone image data is stored in the halftone image buffer 115.

  The above is the content of the halftone processing in the halftone processing unit 114.

[Configuration example of recording head]
Next, a printing method in the image forming apparatus 120 will be described. FIG. 5 is a diagram illustrating a configuration example of the recording head 122, which is a recording head having a plurality of nozzle groups (recording nozzle arrays) called a so-called multi-row head. The recording head 122 typically has nozzles for four types of ink, cyan (C), magenta (M), yellow (Y), and black (K), so as to cover the width of the recording medium. Each color has two nozzle groups (a first nozzle group and a second nozzle group). Hereinafter, in order to simplify the description, black (K) will be described as an example. Further, for convenience of explanation, the nozzles in this figure are shown in a perspective view, and are shown in a larger size than the actual size with respect to the recording medium and each nozzle group.

  In FIG. 5, the first nozzle group and the second nozzle group are fixedly arranged, and ink is ejected from each nozzle group while conveying the recording medium relative to each nozzle group in the main scanning direction. An image is formed by overlapping two recordings. At this time, the first nozzle group forms ink dots using the halftone image data generated using the “threshold matrix i_ # 1”. The second nozzle group forms ink dots using the halftone image data generated using the “threshold matrix i_ # 2”.

  Note that, as described above, the following description will be made on the assumption that the first nozzle group and the second nozzle group eject ink of the same color (K) and the same diameter. Nozzle groups for ejecting different inks, or nozzle groups for ejecting inks of different densities and different colors may be included.

  FIGS. 6A and 6B are diagrams illustrating examples of pixel positions that can be recorded by the first nozzle group and the second nozzle group, respectively. Pixel positions that can be recorded by each nozzle group are determined by the above-described threshold value matrix.

  FIG. 6A shows a dot pattern in which pixels recorded by the first nozzle group and pixels recorded by the second nozzle group appear regularly alternately in the main scanning direction. In this dot pattern, the pixels recorded by the first nozzle group and the pixels recorded by the second nozzle group are completely exclusive. At this time, the pixels of each nozzle group do not overlap each other, and the entire image can be recorded by both nozzle groups.

  On the other hand, FIG. 6B shows that the pixels recorded by the first nozzle group and the pixels recorded by the second nozzle group are irregularly arranged in the main scanning direction, and some pixels are The dot pattern which overlaps (the black coating part in a figure) is shown. Here, an example in which both the first nozzle group and the second nozzle group have nozzles with an ejection frequency that can be recorded at the timing of only one pixel with respect to two pixels (not including dots that are continuous in the recording direction) An example) is shown, and pixels that cannot be recorded (white areas in the figure) appear before and after overlapping pixels in the paper conveyance direction. This non-recordable pixel cannot be recorded by any of the first nozzle group and the second nozzle group.

  The dot pattern in FIG. 6A has a completely exclusive relationship in which dots included in the dot pattern recorded by each nozzle group do not overlap each other. In such a dot pattern, a density variation is likely to occur when a positional deviation occurs between the dot patterns. That is, the tolerance (robustness) against positional deviation tends to be low. In particular, a large density fluctuation occurs in a flat portion of halftone (intermediate between highlight and high density). However, since all the dots in the entire image can be recorded, it can be said that it is easy to ensure the maximum density in the high density portion.

  On the other hand, the dot pattern of FIG. 6B is an arrangement in which some of the dots included in the dot pattern recorded by each nozzle group overlap each other, and tends to be highly resistant to density fluctuations. In particular, density fluctuations can be satisfactorily suppressed in a halftone flat portion. However, as described above, pixels in which dots cannot be arranged are generated, so that the paper surface cannot be sufficiently covered with dots in the high density portion, and the density may be lowered. In addition, since there are pixels that cannot be arranged, the sharpness of steep portions such as thin lines and edge portions may deteriorate.

  To summarize the above, it is preferable to record a dot pattern in which a part of the dots overlaps like the dot pattern of FIG. 6B in a halftone flat portion where the density fluctuation accompanying the landing position deviation of the dot group is conspicuous. It is. When it is desired to secure the density of the high density part or to ensure the sharpness of the steep part such as the thin line or the edge part, a dot pattern in which the dots do not overlap each other like the dot pattern of FIG. It is preferable to record.

  In this embodiment, the above-described image feature extraction unit extracts features of the input image, that is, features such as an image area and gradation, and based on the extraction result, the overlapping amount of dots recorded in each nozzle group is calculated. I have control. The overlapping amount of dots is taken into consideration when creating a threshold matrix described below.

[How to create a threshold matrix]
Next, a method for creating a threshold matrix will be described. The following description is a common creation method when creating each of the N threshold matrix sets. By adjusting a parameter (vertical height of unit potential) described later, the amount of overlap of dots differs. , N threshold matrix sets can be created.

  FIG. 7 is a flowchart illustrating a flow of a threshold matrix creation method according to the present embodiment. A series of processing shown below is realized by executing a threshold matrix creation tool (program) created by a product designer or the like on a PC or the like. Normally, the user does not use the threshold matrix creation tool, but an operator or maintenance person with a certain authority may create a threshold matrix using this. The threshold matrix created by this process corresponds to 8-bit (0 to 255) grayscale, and a rule that outputs on-dots when the pixel value of the pixel of interest in the input image data is greater than or equal to the threshold in the threshold matrix Is following. The size of the threshold matrix may be arbitrary, but it is more preferable to use a quadrangle (for example, 256 × 256) having sides with a length of power of 2. The vertical and horizontal sizes of the threshold matrix may be different. In the present embodiment, the threshold matrix is created from the bright gradation to the dark gradation.

  In step 701, two matrices (MatrixA and MatrixB) in the threshold matrix set to be created are initialized. Specifically, the values of all threshold values of MatrixA and MatrixB are set to “0”.

  In step 702, two initial dot arrangements for the brightest gradation value (g = 1) including on dots are arbitrarily determined. Here, the dot arrangement corresponding to Matrix A is referred to as “pattern A”, and the dot arrangement corresponding to Matrix B is referred to as “pattern B”. Pattern A and pattern B are arrays having the same size as the threshold matrix, and take either black (255) or white (0) as the threshold. Here, it is more preferable that the pattern A and the pattern B each have high dispersibility, and the dot arrangement in which both patterns are superimposed also has high dispersibility (blue noise characteristics). Such a pattern can be obtained, for example, by allocating the highly dispersive dot arrangement obtained by a known method to the pattern A and the pattern B so as not to be biased as much as possible.

  In step 703, a unit potential (potential function) that is applied to one on dot (black) is created. Here, the unit potential is a monovalent function with respect to a position from the focused on-dot having a two-dimensional spread, and is typically a function that monotonously decreases in accordance with the distance from the origin. Such a function can be generated by applying a low-pass filter to a single dot, for example. However, if any value can be set, it does not matter. FIG. 8A shows an example of the unit potential, which is a two-dimensional Gaussian function of σ = 1.5 normalized so that the value at the vertex is 1.00.

  In step 704, a potential map is generated for g = 1, which is the brightest gradation including on dots. Here, the potential map is an array having the same size as the threshold matrix, and the pixel value is the sum when the above-described unit potential is applied to the dot arrangement. Hereinafter, the potential maps corresponding to the patterns A and B will be referred to as “PotentialA” and “PotentialB”. In creating the potential map, first, all pixel values of PotentialA and PotentialB are set to “0”. Next, paying attention to the on dots in each of the patterns A and B, a unit potential centered on the position of the on dots is considered, and the value is added to Potential A and Potential B for each pixel. These processes are repeated for all on dots. At this time, the boundary conditions are set so that the left end and the right end, and the upper end and the lower end of the potential map are in contact and continuous. When the above addition processing is completed, the potential maps PotentialA and PotentialB correspond to the dot arrangement of the pattern A and pattern B, the potential map of the pixel in which the on-dot is in the vicinity has a large value, and the pixel of the pixel in which the on-dot is not in the vicinity The potential map should have a smaller value. FIG. 8B is a diagram showing an example of a potential map corresponding to a dot arrangement in which four on-dots exist, the left side showing the dot arrangement, and the right side showing the potential map. In FIG. 8B, black dots indicate on dots. In the potential map on the right side, the gray color gradually decreases in a concentric manner centering on the on-dot, and the dark gray area indicated by the arrow 801 indicates a high dot density area, and the gray area indicated by the arrow 802 (blank area). (Area) represents a portion where the dot density is low. Then, when adding a new dot to the current dot arrangement, refer to the potential map as described above and place the next dot in a sparse dot density area to build an arrangement with high dot dispersion Can do.

  In step 705, the value of the same position (x, y) in Matrix A is updated to “1” for all the positions (x, y) where the on dots of pattern A are present. Similarly for MatrixB, the value of the same position (x, y) in MatrixB is updated to “1” for all the positions (x, y) where the on-dots of pattern B exist. When the processing in step 705 is completed, the processing for the brightest gradation (g = 1) as the base ends.

  In step 706, a process of adding on dots to the dot arrangements of the pattern A and the pattern B is performed up to a predetermined Mth gradation after the gradation value g = 2. In this case, the value of M is arbitrary. FIG. 9 is a flowchart showing details of the process for adding ON dots up to the M-th gradation for pattern A. This will be described in detail below.

  In step 901, a gradation value g (2 ≦ g) to be processed is determined.

  In step 902, the number of ON dots to be newly added per gradation is determined. The on-dot number NA is most simply determined by dividing the total number of pixels of the threshold matrix by the total number of gradations, and is a constant value for each gradation value g. However, in consideration of effects such as dot gain at the time of image formation, a different NA may be used for each gradation.

  In step 903, a cumulative potential map “PotentialS” corresponding to the dot pattern recorded by all the nozzle groups (the first nozzle group and the second nozzle group in this embodiment) is derived. Specifically, the above two potential maps “PotentialA” and “PotentialB” are added for each pixel, and the sum of the two is obtained.

In step 904, a position to add one on dot is determined. This position is the position where no on-dots still exist in the pattern A, and the calculation result for each pixel of the potential evaluation formula shown in the following formula (1) is the smallest as a potential function for determining the position where the on-dot is added. Let it be position (x, y).
(Α × PotentialS + β × PotentialA) (1)
In the above formula (1), α and β are arbitrary coefficients. According to the applicant's experiment, for example, the value of α is preferably “1.0” and the value of β is “0.3”, but is not limited thereto. When a plurality of positions where the potential evaluation formula takes the minimum value is found, one position (x, y) may be selected at random.

  In step 905, an on dot is placed at the position (x, y) determined in step 904 in pattern A.

  In step 906, the potential map “PotentialA” is updated. Specifically, the unit potential centered on the position (x, y) determined in step 904 is added to the current PotentialA.

  In step 907, processing for replacing the value of the position (x, y) in Matrix A with the current gradation value g is performed. For example, when the gradation value g = 2, “2” is set as the value of the threshold value matrix at the position (x, y).

  In step 908, it is determined whether or not the on-dot number NA determined in step 902 has been reached. That is, it is determined whether or not the processing in steps 903 to 907 has been repeated NA times. If the on-dot number NA has been reached, the process proceeds to step 809. On the other hand, if the on-dot number NA has not been reached, the process returns to step 903 and the process is repeated until the on-dot number NA is reached.

  In step 909, it is determined whether or not the current gradation value g has reached a predetermined Mth gradation. If the current gradation value g has reached a predetermined Mth gradation, the present process ends. On the other hand, if the current gradation value g has not reached the predetermined Mth gradation, the process returns to step 901 to determine the next gradation value as the processing target gradation value g and continue the processing.

  The above is the content of the processing in step 706. Then, the same processing as described above is performed for the pattern B. In that case, in the flow of FIG. 9, “ON dot number NA” is “ON dot number NB”, “Pattern A” is “Pattern B”, “MatrixA” is “MatrixB”, and “PotentialA” is “PotentialB”. The processing for pattern B is performed by rereading each.

  Returning to the flowchart of FIG.

  With the processing so far, a threshold matrix from the brightest gradation to a predetermined Mth gradation darker than that is created. This threshold value matrix is a good pattern that is well dispersed by itself, and is a good pattern that is well dispersed when superimposed. This is because, in the potential evaluation formula shown in the above formula (1), the first term is a term that makes the dispersibility good when the dot arrangement is overlapped, and the second term is the dispersibility of the dot arrangement alone. This is because it functions as a good term. However, it is not guaranteed by the potential evaluation formula until it is robust with respect to relative positional deviation (no deterioration in image quality). Therefore, in the present embodiment, a robustness check process for relative positional deviation is performed on the threshold matrix up to the M-th gradation created. As described above, the value of M is arbitrarily determined by the user. With the dot arrangement created by this method at the same potential, substantially the same phase difference characteristic can be obtained regardless of the gradation value. However, in the case of highlights or shadows where the dot ratio is biased, the characteristics may be different in detail, so it is more preferable to select a value of an intermediate gradation. In the present embodiment in which the gradation value g is expressed by 0 to 255, M = 125.

  In step 707, the phase difference between the dot arrangement of pattern A and the dot arrangement of pattern B is checked. Specifically, the phase of the cross spectrum of the Mth gradation dot arrangement A and dot arrangement B created in step 706 is calculated, and the difference between the two is obtained.

In step 708, based on the phase difference derived in step 707, it is determined whether the following two conditions are satisfied.
-Low frequency components that are easy to perceive visually are set in opposite phases.-High frequency components are made uncorrelated (random) without having a specific phase relationship, and a specific determination method in this case will be described later. If the above two conditions are not satisfied, the process proceeds to step 709. On the other hand, if the above two conditions are satisfied, the process proceeds to step 711.

  In step 709, the process is returned to the state at the end of the process in step 705. That is, the dot arrangement (pattern A, pattern B), threshold matrixes (MatrixA, MatrixB), and potential maps (PotentialA, PotentialB) up to the Mth gradation created in step 706 are discarded and reset.

  In step 710, the height of the center (vertex) of the unit potential is changed according to the phase difference derived in step 707. FIG. 10 is a graph showing the phase difference between the pattern A and the pattern B created when only the value of the vertex of the unit potential is changed slightly from 1.00. In FIG. 10A, when the vertex value is changed to 0.98, (b) is changed to 0.99, (c) is changed to 1.00, (d) is changed to 1.01, the same (e ) Shows the case of changing to 1.02. When (a) to (e) in FIG. 10 are compared, as the value of the vertex of the unit potential is changed from small to large, the phase difference in the high frequency region continuously reverses from the same phase state through the random state. It turns out that it changes to a phase state. As a result of investigation, the robustness of the density fluctuation with respect to the positional deviation increases as the phase difference in the high frequency range becomes random, and conversely, the density fluctuation with respect to the positional deviation increases as the phase difference in the high frequency area becomes the opposite phase state. Has been found to be less robust. It is also known that the granularity deteriorates as the phase difference in the high frequency range is set to a random state, and the granularity improves as the phase difference in the high frequency range is set to an opposite phase state. Further, it has been found that by changing the phase difference in this manner, the overlapping state of dots changes, and the graininess changes even when there is no relative positional deviation. At this time, in the medium density region, the more the dots overlap, the worse the graininess. Conversely, the more the dots are exclusive, the more the graininess tends to improve. Accordingly, by appropriately changing the height of the vertex of the unit potential, it is possible to design dot arrangements having different robustness of density fluctuation and graininess fluctuation with respect to relative positional deviation, and different graininess. Instead of changing the height of the vertex of the unit potential, the height of the portion other than the vertex may be changed. Furthermore, the width of the unit potential may be changed. For example, when the width of the unit potential is changed, the frequency band in which the dots are mutually exclusive tends to be narrowed. Further, not only a Gaussian potential but also other potential shapes may be used.

  After the completion of step 710, the process returns to step 706, and the threshold value matrix creation process up to a predetermined Mth gradation (g = 2 to M) is executed again.

  In step 711, since a desired robust threshold value matrix has been created, for the remaining gradation values g = (M−1) to 254, processing for adding on dots to the dot arrangements of the patterns A and B is performed. Since the contents of this process are the same as those in step 706 described above, description thereof is omitted.

  The above is the method for creating the threshold matrix according to the present embodiment. As a result, the threshold matrix i_ # 1 (i is any value from 1 to N) and the threshold matrix i_ # 2 (i is 1 to N) corresponding to each of the first nozzle group and the second nozzle group. N sets of (any value) can be created.

  As shown in FIG. 6A, in order to create a threshold matrix that can realize a dot pattern in which dots formed by each of a plurality of nozzle groups do not overlap each other (that is, a completely exclusive dot pattern), For PotentialA and PotentialB, the value of the pixel not to be recorded is a sufficiently large value (for example, when the potential map size is 256 x 256, 256 x 256 x 1 (maximum value of the potential map pixel value) = 65536 or more ) And a threshold value matrix may be created by the method described above.

[Flow of print processing]
Based on the above description, the flow of printing processing in the printing system 100 according to the present embodiment will be described.

  FIG. 11 is a flowchart illustrating the overall printing process according to this embodiment.

  In step 1101, the image processing apparatus 110 acquires multi-value input image data. The acquired input image data is stored in the input image buffer 111 and then sent to the image feature extraction unit 112 and the color separation processing unit 113.

  In step 1102, the image feature extraction unit 112 performs image area determination processing on the input image data. This image area determination processing determines the image area of the input image (more specifically, whether each pixel of the input image data is a pixel belonging to a flat part or a pixel belonging to a steep part such as a thin line or an edge). .

  In step 1103, the image feature extraction unit 112 acquires the gradation value of each pixel in the input image data.

  In step 1104, the halftone processing unit 114 (the threshold matrix selection unit 201) selects a threshold matrix set corresponding to the image feature information (that is, the image area determination result in step 1102 and the gradation value acquired in step 1103). To do. The concept for selecting one threshold matrix group based on the image area determination result and the gradation value information will be described later.

  In step 1105, the halftone processing unit 114 (the comparison unit 203 and the halftone image generation unit 204) executes halftone processing in units of areas corresponding to the image feature information using the selected threshold matrix set. When the halftone process for the entire input image data is completed, the generated halftone image data is stored in the halftone image buffer 115 and then sent to the image forming apparatus 120.

  In step 1106, the image forming apparatus 120 drives the recording head 122 based on the halftone image data received from the image processing apparatus 110 to form an image on a recording medium such as paper.

  The above is a rough flow of the printing process in the printing system 100 according to the present embodiment.

[Dot overlap ratio for image area and gradation]
FIG. 12 is a table showing the relationship of the overlapping rate between dot groups with respect to combinations of image areas and gradation values of the input image. As is apparent from the table of FIG. 12, the dot overlap rate is increased or decreased from the combination of the image area and the gradation value. In this embodiment, dot overlap is performed in a flat portion of a halftone area (a predetermined gradation range having a gradation value higher than that of a highlight area and lower than that of a high density area) in order to suppress density fluctuation. In other cases (highlight and high density areas other than halftone, or steep areas), the dots are used to ensure maximum density and sharpness, or to emphasize graininess in highlights. Try to reduce the overlap rate. As described above, the dot overlap rate can be controlled by changing the vertex height of the unit potential when creating the threshold matrix. In this way, a threshold matrix set based on the characteristics of the input image can be selected in consideration of the dot overlap rate determined by the image area and gradation value of the input image.

[Dot overlap rate for gradation values in flat areas]
FIG. 13 is a graph showing an example of the relationship between the gradation and the dot overlap rate in the flat portion. In the halftone, a threshold matrix set that realizes a dot pattern in which a part of the dots overlap as described with reference to FIG. 6B is selected so that the dot overlap rate increases. As a result, density fluctuations in halftone are suppressed. On the other hand, a threshold value matrix set that realizes a dot pattern in which dots do not overlap with each other as described with reference to FIG. 6A is selected so that the dot overlap rate decreases in the high density portion. As a result, the maximum density in the high density part is secured. In highlights, the number of dots is small in the first place, and we want to emphasize graininess. Therefore, basically, a threshold matrix set that realizes a dot pattern in which dots do not overlap with each other is selected, and a threshold matrix set that realizes a dot pattern with a high dot overlap rate gradually as it changes toward halftones. Will be selected.

  Although not shown in the graph as shown in FIG. 13, in the case where the image area of the input image is a steep portion, since the sharpness of a steep portion such as a thin line or an edge portion is emphasized in any gradation, dot overlap A threshold matrix set is selected such that the rate is smaller than the dot overlap rate in the halftone of the flat portion.

  The dot overlap rate with respect to the gradation described above is an example, and is not limited to the above example.

  In the present embodiment, the case of dividing the highlight, halftone, high density portion and gradation into three has been described, but a plurality of threshold matrix sets are prepared according to the number divided into four or more and input. A configuration may be adopted in which a threshold matrix set corresponding to the feature of the image is selected. The image area is also divided into two parts, a flat part and a steep part, but it may be divided into three or more parts.

  Furthermore, the threshold matrix set may be selected based on information on only one of the image area and the gradation based on the above-described concept.

  As described above, according to the present embodiment, when an image is formed using a recording head having a plurality of nozzle groups, a high density is suppressed while suppressing density fluctuations due to landing position deviation for each dot group. It is possible to reduce a lack of density at the portion and a reduction in sharpness at a steep portion such as a thin line or an edge portion.

[Example 2]
In the first embodiment, the characteristics of the input image are selected from N sets of threshold matrixes (i_ # 1) and threshold matrices (i_ # 2) corresponding to the first nozzle group and the second nozzle group, respectively. A mode of selecting a corresponding threshold matrix set has been described. Next, a mode in which some threshold value matrices are shared among N prepared threshold matrix groups will be described as a second embodiment. The description of the parts common to the first embodiment will be omitted or simplified, and the differences will be mainly described below.

[Halftone processing section]
FIG. 14 is a block diagram illustrating an internal configuration of the halftone processing unit 114 according to the present embodiment. Similar to the first embodiment, the halftone processing unit 114 according to this embodiment includes a threshold matrix selection unit 201, a memory 202, a comparison unit 203, and a halftone image generation unit 204. A characteristic part in the present embodiment is a threshold matrix stored in the memory 202, and the other parts are the same as those in FIG. As shown in FIG. 14, the memory 202 of this embodiment holds one common threshold value matrix and N non-common threshold value matrices. The threshold matrix selection unit 201 selects, for example, a common threshold matrix for an image formed by the first nozzle group, and selects N non-common threshold matrixes for an image formed by the second nozzle group. One threshold matrix is selected based on the image feature information.

[Threshold matrix creation method]
Here, a method for creating a threshold matrix set in the present embodiment will be described. FIG. 15 is a flowchart illustrating a flow of a threshold matrix creation method according to the present embodiment. The threshold matrix created by the following processing corresponds to 8-bit (0 to 255) gray scale, and outputs on dots when the pixel value of the pixel of interest in the input image data is equal to or greater than the threshold in the threshold matrix. Follow the rules. The size of the threshold matrix may be arbitrary, but it is more preferable to use a quadrangle (for example, 256 × 256) having sides with a length of power of 2. Eventually, one common threshold matrix and one non-common threshold matrix are created for the conditions indicated by the image feature information.

  In step 1501, a common threshold matrix is created. The method for creating the common threshold value matrix is not particularly limited, and a known method may be applied. Preferably, a dot arrangement having a high dispersion has better robustness, and therefore it is desirable to create the dot arrangement by a blue noise mask method or the like.

  In step 1502, a candidate for a non-common threshold matrix is created. At this time, the dot arrangement of the common threshold value matrix is considered. FIG. 16 is a flowchart showing details of the non-common threshold matrix candidate creation process. This will be described in detail below.

  In step 1601, the coefficient α is initialized (“0” is set as the value of the coefficient α). Here, the coefficient α represents a trade-off relationship in which the granularity is sacrificed when there is no positional deviation when the robustness with respect to the relative positional deviation between the dot patterns is increased. When the value is small, the dispersibility of the dot arrangement corresponding to each nozzle group is emphasized. When the value of the coefficient α is large, the dispersibility of the dot arrangement when they are superimposed without relative positional deviation is emphasized. In the subsequent processing, a plurality of threshold matrixes are created by gradually increasing the value of the coefficient α. In this case, the value of the coefficient α changes between “0” and “1”.

  In step 1602, a step size Δα for increasing the coefficient α is set. Since the coefficient α takes a value between “0” and “1” as described above, Δα is preferably less than “0.5”.

  In step 1603, initialization processing for creating a threshold matrix corresponding to the current coefficient α is performed. Specifically, “255” is set to all threshold values in the threshold value matrix. The coefficient α = “0” immediately after the start of processing, and thereafter, the value obtained by adding Δα determined in step 1602 becomes the next coefficient α (see step 1617 described later). Initialization processing is performed.

  In step 1604, dot arrangement (hereinafter referred to as common dot arrangement [i]) of all gradations (0 to 255 in the case of 8-bit format) is performed by the dither method from the common threshold value matrix created in step 1501. Indicates a gradation value). Here, the common dot arrangement is an array (dot pattern) having the same size as the threshold matrix, and the value is either on (= 255) or off (= 0).

  In step 1605, a potential map for each gradation is created. The specific procedure is as follows.

  First, a unit potential applied to one on dot is created. Then, a potential map “PotentialC [i]” corresponding to each common dot arrangement [i] of each gradation is created for the created unit potential. Specifically, first, the values of all pixels of PotentialC [i] are set to “0”. Next, paying attention to a certain on-dot in the dot pattern in the common dot arrangement [i], a unit potential centered on the position is considered, and the value is added to PotentialC [i] for each pixel. This is repeated for all on dots. At this time, the boundary conditions are set so that the left end and the right end, and the upper end and the lower end of the potential map are in contact and continuous. When the addition process is completed, the potential map corresponds to the common dot arrangement, and the value near the pixel with the on dot should be large, and the value near the pixel without the on dot should be small. When a new dot is added to the current dot arrangement, an arrangement with high dot dispersibility can be constructed by arranging the next dot in an area where the dot density is sparse with reference to the potential map described above. .

  In step 1606, the gradation weight kn (n: natural number) is determined. This gradation weight is a variable used in the subsequent step 1608, and is determined so as to satisfy the conditions of 0 ≦ k1, k2,..., Ki ≦ 1 and k1 + k2 +. Here, k1, k2,..., Ki should be set monotonically in a decreasing manner, for example, k1 = 0.5, k2 = 0.3, k3 = 0.2, k4 and later = 0, and so on. .

  In step 1607, the gradation value g of the non-common threshold matrix to be constructed is determined. At this time, starting from g = 1, which is the brightest gradation, up to g = 254, which is the darkest gradation, are sequentially determined as gradation values g to be processed.

In step 1608, a potential map (hereinafter referred to as a comprehensive potential map) serving as a reference for determining the dot arrangement of the non-common threshold matrix is created. This total potential map can be obtained by adding the individual potential maps created for each gradation in step 1605. Here, a dot arrangement on the non-common threshold matrix side that is a pair of the common dot arrangement [i] is set as a non-common dot arrangement [i]. Note that i = 0 in the non-common dot arrangement [i] is a dot pattern in which all pixels are white pixels. The non-common dot arrangement [i] refers to the potential map PotentialN [i-1] created from the non-common dot arrangement [i-1], and the pixel with the lowest value (area where the dot density is sparse) It is created by repeating the process of adding a dot and reflecting the added dot on the potential map PotentialN [i-1] until the number of dots for one gradation is added. Here, referring only to PotentialN [i-1] means not considering the dot arrangement on the common dot arrangement side. Accordingly, the dispersibility when the non-common dot arrangement and the common dot arrangement are overlapped with each other is deteriorated. In order to prevent this, a total potential map obtained by weighting and adding the potential map on the common dot arrangement side and the potential map on the non-common dot arrangement side is used. In this case, the simplest method of creating the total potential map is a method of adding PotentialC [i] to PotentialN [i-1] with a coefficient α and adding each pixel. This is expressed by the following equation (2).
Total potential map = PotentialN [i-1] + α x PotentialC [i] (2)
In the above equation (2), α is a weight that determines how much the dot arrangement on the common dot arrangement side is to be considered, and is a value of 0 <α <1.0. FIG. 17 illustrates a process of creating a comprehensive potential map using the above equation (2). In FIG. 17, a dot pattern 1701 indicates a non-common dot arrangement, and a dot pattern 1702 indicates a common dot arrangement. The potential map 1703 corresponds to PotentialN [i-1], and the potential map 1704 corresponds to PotentialC [i]. In the completed total potential map 1705, a gray circle centered on two dots in the potential map 1704 becomes smaller according to the weight α (α = 0.5 in FIG. 17).

Thus, by using the above equation (2), when the value of the coefficient α is close to “0”, the dispersibility on the non-common dot arrangement side is emphasized, and when the value of the coefficient α is close to “1” It is possible to create a dot arrangement that emphasizes the dispersibility of the overlapping of the common dot arrangement and the non-common dot arrangement. By the way, according to the rules of the dither method, the dots in the i-th gradation dot arrangement must be present at the same position even in the next i + 1-gradation dot arrangement. In the above equation (2), only the i-th gradation is considered on the common dot arrangement side, and dots added in the common dot arrangement [i + 1] are not considered. In this case, there is a possibility that an additional dot in the non-common dot arrangement [i] is placed near the dot added in the common dot arrangement [i + 1]. Since the dots of the non-common dot arrangement [i] are inherited by the non-common dot arrangement [i + 1], in this case, the non-common dot arrangement [i + 1] and the common dot arrangement [i + 1] are overlapped. The dispersibility of the alignment becomes worse. In order to cope with this, as shown by the following expression (3), the gradations subsequent to the target gradation may be weighted and added.
Total potential map = PotentialN [i-1] + α x (k1 x PotentialC [i] + k2 x PotentialC [i + 1] + ... + k [255-i] x PotentialC [254]) (3)
In the above equation (3), k is the gradation weight determined in step 1606 described above. Α is as described in the above formula (2). As described above, the non-common dot arrangement [i] is determined with reference to the total potential map represented by the above formula (3), so that the combination of the non-common dot matrix and the common threshold value matrix has good granularity in all gradations. A common threshold matrix can be obtained.

  In step 1609, the number of newly added ON dots per gradation is determined. The on-dot number NA is most simply set to the number obtained by dividing the total number of pixels in the threshold matrix by the total number of gradations. The number of on dots NA is usually a constant value at each gradation value g. However, in consideration of effects such as dot gain at the time of image formation, a different NA may be used for each gradation. When the number of newly added ON dots NA is determined, on dots are added to the non-common dot arrangement [g-1] one by one in a loop process including subsequent steps 1610 to 1614. Specifically, it is as follows.

  First, in step 1610, a position (x, y) for adding one on dot is determined. The position is the position where the on-dot does not yet exist in the non-common dot arrangement [g-1] and the position having the smallest value in the above-described total potential map. If a plurality of positions where the potential has the minimum value is found, one of them may be selected at random.

  In step 1611, an on dot is placed at the determined position (x, y) in the non-common dot arrangement [g−1].

  In step 1612, the potential map is updated. Specifically, unit potential centered at position (x, y) is added to PotentialN (i-1), and the total potential map is recalculated accordingly.

  In step 1613, processing for replacing the value of the position (x, y) in the non-common threshold value matrix with the current gradation value g is performed. For example, when the gradation value g = 2, “2” is set as the value of the threshold value matrix at the position (x, y).

  In step 1614, it is determined whether or not the on-dot number NA determined in step 1609 has been reached. That is, it is determined whether or not the processing from step 1610 to step 1613 has been repeated NA times. If it has been repeated NA times, the dot arrangement process for the current gradation value g is completed. The non-common dot arrangement [g-1] at this time is set as non-common dot arrangement [g], and PotentialN [g-1] is set as PotentialN [g]. As a result of the determination, if the on-dot number NA has been reached, the process proceeds to step 1615. On the other hand, if the on-dot number NA has not been reached, the process returns to step 1610 and the processing is repeated until the on-dot number NA is reached.

  In step 1615, it is determined whether there is an unprocessed gradation value g. In the case of the present embodiment in which all gradations are expressed in an 8-bit format, it is determined whether or not g = 254 has been reached. If g = 254 is reached as a result of the determination, the non-common threshold matrix for the current coefficient α is completed. The completed non-common threshold matrix is stored in the HDD or the like, and the process proceeds to step 1616. On the other hand, if g = 254 has not been reached, the process returns to step 1607 to determine the next processing target gradation value g and continue the processing.

  In step 1616, it is determined whether or not a non-common threshold matrix for all coefficients α has been created. Specifically, it is determined whether or not the value of the coefficient α is “1” which is the upper limit value. If α = 1 as a result of the determination, the non-common threshold matrix candidate creation process ends. At this point, a plurality of non-common threshold matrix candidates having different trade-off relation balances are created. On the other hand, if α = 1, the process proceeds to step 1617 to update the value of the coefficient α (that is, add Δα determined in step 1602 to the current coefficient α) to determine the coefficient α to be processed next, Returning to step 1603, the processing is continued.

  The above is the content of the non-common threshold matrix candidate creation process.

  Returning to the flowchart of FIG.

In step 1503, processing for selecting an optimal non-common threshold matrix from the non-threshold matrix candidates created in step 1502 is performed.
According to the method as described above, a part of a plurality of threshold value matrix sets can be shared as a common threshold value matrix, and memory saving can be realized. When the effect of sharing the threshold matrix is quantified, the capacity required for storing the threshold matrix is (n + 1) / 2n (n is the number of threshold matrices having different characteristics) as compared with the case where the sharing is not performed. Further, the use of the common threshold value matrix also has an effect of reducing unnaturalness in the switching portion of the threshold value matrix.

  In the present embodiment, a plurality of non-common threshold matrixes are created by the above-described method so that the dot pattern created by the non-common threshold matrix has a different overlapping rate than the dot patterns created by the common threshold matrix. . As in the first embodiment, a threshold matrix set that realizes dot patterns having different dot overlap rates is selected according to the image area and the gradation value that are the characteristics of the input image. When the highest density value of the input image (255 in the present embodiment) is input, a non-common threshold value matrix in which the common threshold value matrix is shifted by one pixel in the main scanning direction (printing medium conveyance direction) is used. Also good. As described above, since dots that can be output from one nozzle are every other pixel, a completely exclusive dot pattern can be generated by shifting the common threshold value matrix by one pixel in the main scanning direction. Also, in the case where input tone values having a predetermined density or more are completely excluded, a non-common threshold matrix that is obtained by shifting the common threshold matrix by one pixel in the main scanning direction may be selected.

(Modification)
As a method for forming an image on a recording medium, a case where a multi-pass printing method in which recording is performed by scanning a recording head a plurality of times in the same recording area will be described as a modification of the second embodiment.

  By the multi-pass printing method, it is possible to reduce the influence of variations in ink ejection characteristics between a plurality of ejection openings. Each of the multiple scans in the multi-pass printing method is called a pass, the first scan is called the first pass, the second scan is called the second pass, and so on.

  Even in the multi-pass printing method, the dot group formed by the first pass and the dot group formed by the second pass due to fluctuations in the landing position of the ink that forms the dots due to the transport amount of the recording medium and position fluctuations in the main scanning direction, etc. There may be misalignment between the two. Therefore, by assigning a different threshold matrix for each pass, such as generating a dot arrangement for the first pass with a common threshold matrix and generating a dot arrangement for the second pass with a non-common threshold matrix, the present invention can be used for multi-pass printing. The present invention can also be applied to system configurations. The number of passes is not particularly limited, and may be 3 passes or more. In this case, it is preferable to use N threshold matrixes for N passes. This is because, if the same threshold value matrix is used, many dots are arranged only at pixel positions having a low threshold value, and graininess is not improved. Therefore, for example, if N = 6, the common threshold matrix is 3 patterns (common_1 to common_3), and the non-common threshold matrix is 3 patterns (noncommon_1 to noncommon_3) for a total of 6 A threshold matrix is created. And 1st path: common_1, 2nd path: common_2, 3rd path: common_3, 4th path: non-common_1, 5th path: non-common_2, 6th path: non-common Each threshold matrix is assigned to each path such as _3. The ratio and order of common and non-common are arbitrary. Also, there is no particular limitation on how many passes the dot arrangement generated by the common threshold value matrix is used. However, it is more preferable that a common threshold value matrix is assigned to the preceding path and the common threshold value matrix has a high blue noise characteristic.

  As described above, also in the present embodiment, in the case of forming an image using a recording head having a plurality of nozzle groups, the high density portion is suppressed while suppressing the density fluctuation due to the landing position deviation for each dot group. Insufficient density and a reduction in sharpness at steep portions such as fine lines and edges can be reduced.

[Other Examples]
In addition, the present invention can be applied to various configurations such as recording heads and recording chips constituting a long head in interlace scanning and a full line system. The following is an overview of each.

<When applied to interlaced scanning>
Interlaced scanning is a method of multiple scanning in which a dot group is filled up so as to complement each other using a group of nozzles with a low nozzle resolution. This method is often used in printers that record with a piezo head. For example, when two scans are performed by interlace scanning, the first nozzle group can be replaced with the first scan in the interlace scan, and the second nozzle group can be replaced with the second scan in the interlace scan.

<When applied to each recording head and recording chip constituting a long head in the full line system>
In a full-line system in which a long head is configured by connecting a plurality of short recording heads, a plurality of nozzle groups are usually arranged in parallel on the short recording head. What is necessary is just to replace these several nozzle groups with the above-mentioned 1st nozzle group and 2nd nozzle group, and to apply.

  Further, in the above-described embodiment, the description has been made centering on an example in which the recording head is configured by two nozzle groups of the nozzle group 1 and the nozzle group 2. However, if the nozzle group generates a relative positional deviation, three nozzles are used. Even in the above case, the present invention can be suitably applied. For example, in the case of a recording head having three nozzle groups of nozzle group 1, nozzle group 2, and nozzle group 3, the dot arrangement between the dot patterns formed by each of nozzle group 1, nozzle group 2, and nozzle group 3 is changed. Control is sufficient. That is, a threshold matrix set with different dot overlap rates between the dot patterns corresponding to the three nozzle groups may be created, and an optimum threshold matrix set may be selected according to the image area and gradation of the input image. Alternatively, the present invention may be applied to the nozzle group 1 and the nozzle group 2, the nozzle group 1 and the nozzle group 3, and the nozzle group 2 and the nozzle group 3.

  The present invention supplies a program that realizes one or more functions of the above-described embodiments to a system or apparatus via a network or a storage medium, and one or more processors in a computer of the system or apparatus read and execute the program This process can be realized. It can also be realized by a circuit (for example, ASIC) that realizes one or more functions.

110 Image Processing Device 112 Image Feature Extraction Unit 114 Halftone Processing Unit 120 Image Forming Device 201 Threshold Matrix Selection Unit

Claims (15)

An image processing apparatus for generating a plurality of halftone image data for use in an image forming means for forming an image based on input image data on a recording medium by superimposing dots of different dot patterns on the same region Because
Halftone processing means for converting input image data into a plurality of halftone image data by halftone processing;
In the dot pattern represented by at least two halftone image data of the plurality of halftone image data by the halftone processing unit, some dots overlap,
The ratio of the overlapping dots in the dot pattern varies depending on the density in the input image data.   The image processing apparatus according to claim 1, wherein each of the plurality of halftone image data does not include dots that are continuous in the recording direction.   The ratio of the overlapping dots in the dot pattern in the steep portion where the density change in the input image data is large is lower than the ratio in which the overlapping dots occupy the dot pattern in the flat portion where the density change is small in the input image data. The image processing apparatus according to claim 1, wherein the image processing apparatus is an image processing apparatus.   The ratio of the overlapping dots in the halftone area in the input image data to the dot pattern is higher than the ratio of the overlapping dots in the dot pattern in the area other than the halftone in the input image data. The image processing apparatus according to claim 1, wherein the image processing apparatus is an image processing apparatus. Image feature extraction means for extracting image features of the input image data;
Selection means for selecting a threshold matrix corresponding to each of the different dot patterns based on the extracted image features;
Quantizing means for quantizing the input image data using the threshold matrix selected by the selecting means, and generating the plurality of halftone image data, and
The image processing apparatus according to claim 1, further comprising:   The image feature extraction unit extracts, as the image feature, either information obtained by performing an image area determination process on the input image data or gradation value information in the input image data. The image processing apparatus according to claim 5, wherein:   The image feature extraction means extracts both a result obtained by performing an image area determination process on the input image data and information on gradation values in the input image data as the image features. The image processing apparatus according to claim 5.   The image processing apparatus according to claim 6, wherein in the image area determination process, it is determined whether the image is a flat part with a small density change or a steep part with a large density change. The selection means includes
One threshold matrix set is selected from a plurality of threshold matrix sets each having a threshold matrix corresponding to each of the different dot patterns,
9. The image processing apparatus according to claim 5, wherein the degree of overlapping of the dot groups in the different dot patterns is different depending on each threshold matrix group of the plurality of threshold matrix groups.   9. The selection unit according to claim 5, wherein the selection unit selects a common threshold value matrix that does not depend on the image feature as at least one threshold value matrix among a plurality of threshold value matrices corresponding to the different dot patterns. The image processing apparatus according to any one of the above.   The image processing apparatus according to claim 10, wherein the common threshold value matrix is a threshold value matrix corresponding to a dot pattern used in preceding image formation among the different dot patterns. The image forming means is a full-line image forming means in which a plurality of nozzle groups covering the width direction of the recording medium are arranged at a constant distance in the transport direction,
The image processing apparatus according to claim 1, wherein the different dot patterns are associated with the plurality of nozzle groups, respectively. The image forming means is an image forming means of an interlaced scanning method that includes a group of nozzles in a row and performs a plurality of scans so as to complement each other for each scan.
The image processing apparatus according to claim 1, wherein the different dot patterns and the plurality of scans are associated with each other. Image processing method for generating a plurality of halftone image data for use in an image forming means for forming an image based on input image data on a recording medium by superimposing dots of different dot patterns on the same region Because
An image feature extraction step for extracting image features of the input image data;
A selection step of selecting a threshold matrix corresponding to each of the different dot patterns based on the extracted image features;
A quantization step of quantizing the input image data using each of the threshold matrixes selected in the selection step to generate the plurality of halftone image data;
Including
In the dot pattern represented by at least two halftone image data among the plurality of halftone image data, some dots overlap, and the overlapping dots occupy the dot pattern according to the density in the input image data. The proportion is different,
An image processing method.   The program for functioning a computer as an image processing apparatus of any one of Claims 1-13.