JPH06205201A - Binary picture magnification/reduction device - Google Patents

Abstract

(57) [Abstract] [Purpose] A good image can be obtained even if a binarized image is reduced or enlarged. [Structure] Without directly reducing or enlarging the binary image,
The binary / multi-value conversion circuit 1 converts into multi-value. Then, the multi-valued image signal converted into the multi-valued image is reduced or enlarged by the reduction / enlargement circuit 2, and the reduced or enlarged multi-valued image signal is subjected to an error diffusion method or a dither method or the like. The tone expression binarization circuit 3 performs halftone processing, converts it into a binary value, and outputs it. As a result, black crushing and white crushing are less likely to occur, and a good binary image can be obtained.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a binary image enlarging / reducing apparatus suitable for use in an image scanner, a facsimile, a digital copy, etc., having a function of enlarging and reducing a binary image.

[0002]

2. Description of the Related Art Conventionally, the above-mentioned image scanner,
Equipment for digital image processing such as facsimile and digital copying has a device for enlarging and reducing an image. This conventional binary image enlarging / reducing device enlarges an image by using the same data several times (for example, twice), and reduces the image by thinning out the data. For example, when the image is reduced to 1/2, odd rows and columns of the image data are extracted. On the other hand, the halftone in the conventional binary image is represented by the gradation according to the dot density such as the well-known error diffusion method or the dither method.

[0003]

By the way, in the above-described conventional binary image enlarging / reducing device, the halftone is expressed by the gradation according to the dot density, but the binary image is enlarged and reduced. Then, the dot density changes,
There is a problem that an unclear binary image occurs due to black crushing and white crushing.

For example, as shown in FIG. 7 (a), diagonally shaded images ((0,7), (1,6),
Each of (2,5), (3,4), (4,3), (5,2), (6,1), (7,0) is "1" and the rest is "0" When the odd rows and the odd columns of the (images to be displayed) are extracted and reduced to 1/2, an image is formed by a matrix of 4 × 4 dots of “0” as shown in FIG. As shown in this figure (b), it becomes a meaningless binary image by reducing.

Therefore, an object of the present invention is to provide a binary image enlarging / reducing device in which black crushing and white crushing are unlikely to occur even when a binary image is enlarged or reduced, and thereby a good binary image can be obtained. There is.

[0006]

In order to achieve the above object, a binary image enlarging / reducing device according to the present invention comprises a multi-value converting means for converting a binary image into a multi-valued image, and the multi-value converting means. The image forming apparatus is characterized by comprising enlargement / reduction means for enlarging or reducing the multi-valued image signal converted into an image, and binarization means for binarizing the multi-valued image signal enlarged or reduced by the enlarging / reducing means. And

[0007]

According to the present invention, the binary image is once converted into a multi-value image before being enlarged or reduced. Then, after being converted into a multi-value, it is enlarged or reduced, and then returned to a binary value. Therefore, black crushing, white crushing, etc. are less likely to occur, and a good binary image can be obtained.

[0008]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment of the present invention will be described below with reference to the drawings. FIG. 1 is a block diagram showing a schematic configuration of a binary image scaling device according to the present invention. In this figure, reference numeral 1 is a binary / multi-value conversion circuit, which converts the supplied binary data into multi-value and outputs it. Here, as an example, FIG.
A case where the (a, b) point shown in (1) is converted into multi-value will be described.

When the halftone is expressed by the dot density, the density of the surrounding points including that point is considered to be the luminance at that point. Therefore, when the gradation at the point (a, b) is obtained by considering that point and surrounding 3 × 3 dots, the gradation Y _{a, b at the} point (a, b) is given by the following equation.

Y _{a, b} = n ₀ · Y _{a-1, b-1} + n ₁ · Y _{a-1, b} + n ₂ · Y _{a-1, b + 1} + n ₃ · Y _{a, b-1} + n ₄・ Y _{a, b} + n ₅・ Y _{a, b + 1} + n ₆・ Y _{a + 1, b-1} + n ₇・ Y _{a + 1, b} + n ₈・ Y _{a + 1, b + 1} (1) , N ₀ , n ₁ , ..., N ₈ are coefficients obtained empirically.

In this way, by performing similar calculations for each point other than the point (a, b), it is possible to multivalue. The matrix is not limited to 3 × 3 dots, and may be, for example, 4 × 3 dots or 4 × 4 dots.

Returning to FIG. 1, 2 is a reduction / enlargement circuit,
The multi-valued data output from the binary / multi-valued conversion circuit 1 is input, the number of data is converted and output. Reference numeral 3 denotes a halftone expression type binarization circuit, which performs halftone processing by a well-known error diffusion method or the like, converts it into a binary value, and outputs it.

The binary / multivalue conversion circuit 1 corresponds to multivalue conversion means, and the reduction / enlargement circuit 2 corresponds to enlargement / reduction means. Further, the halftone expression type binarizing circuit 3 corresponds to a binarizing means.

Next, a series of processing contents will be described with reference to FIG. In this description, it is assumed that the binary / multi-value conversion circuit 1 is supplied with a shaded binary image represented by a matrix of 8 × 8 dots shown in FIG. First, when the binary data of the shaded binary image is supplied to the binary / multi-value conversion circuit 1, the 3 × 3 dots based on the equation (1) shown in FIG. It is converted into multi-value through a multi-value conversion table represented by a matrix. Figure 3
The 8 × 8 dot matrix shown in (c) is the result of multi-value conversion.

When the result of multi-value conversion is output from the binary / multi-value conversion circuit 1, it is input to the reduction / enlargement circuit 2, and odd-numbered rows and odd-numbered columns are extracted by the same circuit 2 to be halved. It is reduced. The matrix of 4 × 4 dots shown in FIG. 3D is the result of reduction. The reduced result is input to the halftone expression binarization circuit 3, and the circuit 3 performs error diffusion processing to convert it to binary. FIG. 3E shows a matrix of 4 × 4 dots which has been binary-converted. As can be seen from FIG. 3E, an image obtained by reducing the hatched image in FIG.

In this way, after the binary / multi-value conversion, the image is enlarged / reduced and then binarized. By this processing, black crushing and white crushing hardly occur even if the binary image is enlarged or reduced, and a good binary image can be obtained. Therefore,
It is possible to improve image quality in digital image processing devices such as image scanners, facsimiles, and digital copies.

In the above embodiment, binary / multivalue conversion,
Although the enlargement / reduction and the binarization processing are performed by hardware, it is also possible to perform the processing by software using a microcomputer. Hereinafter, an example of the case of processing by software will be described with reference to the flowchart shown in FIG.

First, in step S1, binary image data is read. Next, the binary image data read in step S2 is multivalued. That is, for each multivalued point, the sum of the binary data with each point in the adjacent eight directions is calculated. This is given by

[0019] However, b _ij : multi-valued data at the position (i, j) a _ij : binarized data at the position (i, j) w _kl : weight for multi-valued conversion at the position (k, l) The value of the

After the multi-value conversion process is completed, the process proceeds to the enlargement / reduction process. First, in step S3, the image is reduced or expanded by 1 / α times in the y direction. This is given by y ′ _n = [y ′ _n−1 + α] (3) Next, in step S4, the image data of y ′ _n rows is read. After performing this reading, x in step S5
Direction is reduced or expanded by 1 / α times. This is given by _{x'n = [x'n-1} + α] ... (4)

[0021] Next, reading of multilevel image data of _x'n rows in step S6. Then, in step S7, the end of the enlargement / reduction in the x direction is determined. If not completed, the process returns to step S5. When the enlargement / reduction in the y direction is not completed, the process returns to step S4, and when it is completed, the process proceeds to step S9.

In step S9, binarization is performed by the error diffusion method. After the binarization process is completed, the enlarged or reduced image is displayed. Then save it if necessary.

Next, FIG. 5 is a flowchart showing the binarization processing by the error diffusion method. First, in step S20, the maximum value and the minimum value of data are detected. Next, in step S21, an AGC (automatic gain control) value is determined, and then in step S22, halftone pixel data is read. After reading this data, step S23
Then, the read halftone pixel data is binarized. In this case, the intermediate value is compared with the threshold value and binary conversion is performed. Next, in step S24, binary value × a from the intermediate value (original value)
(Output value) is subtracted to obtain the error. In this case, “a” is the maximum value that the halftone pixel data can take. For example, in the case of 4 bits, “7” of 0 to 7 is the maximum value.

Then, error diffusion is performed by the error diffusion filter. FIG. 6 shows an example of the error diffusion filter. This error diffusion filter diffuses the error in the "●" part to adjacent places at a rate indicated by a numerical value (correctly, a value obtained by dividing these numerical values by 1/16). In other words, the error in the "●" part is diffused. It is to distribute to the surroundings. After this error diffusion processing is completed, data is read in step S26.
After the error is collected, the process returns to step S23 and steps S23 to S27 are repeated.

[0025]

According to the present invention, after the binary / multi-value conversion, the image is reduced / enlarged and then binarized. It is possible to obtain the effect that white crushing is less likely to occur and a good binary image is obtained.

[Brief description of drawings]

FIG. 1 is a block diagram showing a schematic configuration of a binary image scaling device according to the present invention.

FIG. 2 is a diagram for explaining the principle of binary / multivalue conversion of the same embodiment.

FIG. 3 is a diagram for explaining the operation of the embodiment.

FIG. 4 is a flowchart for explaining the operation of the embodiment.

FIG. 5 is a flowchart for explaining the operation of the embodiment.

FIG. 6 is a diagram for explaining the operation of the embodiment.

FIG. 7 is a diagram for explaining a problem in conventional binary image scaling.

[Explanation of reference numerals] 1 binary / multi-value conversion circuit (multi-value conversion means) 2 reduction / enlargement circuit (enlargement / reduction means) 3 halftone expression binarization circuit (binarization means)

Claims (1)

[Claims] 1. A multi-value converting means for converting a binary image into a multi-valued image, an enlarging / reducing means for enlarging or reducing the multi-valued image signal converted into the multi-valued image by the multi-valued converting means, A binary image enlarging / reducing device comprising: a binarizing unit that binarizes a multi-valued image signal that has been enlarged or reduced by the enlarging / reducing unit.