JP2716447B2 - Image processing device - Google Patents

Description

Description: TECHNICAL FIELD The present invention relates to an image processing apparatus that performs gradation processing on input image data and outputs the result.

(Prior art) Shading image (halftone image) in digital copying machine
Is reproduced by the systematic dither method.

When a document as an image source is a halftone image expressed in area gradation, interference occurs between the halftone dot pattern and a dither pattern for dither processing, and as a result, moire occurs. To prevent the occurrence of moire, for example, as described in Japanese Patent Application Laid-Open No. 55-120025, a halftone image is subjected to a smoothing process to remove a periodic pattern of halftone dots, and There is one that performs processing.
However, by performing the above-described smoothing process, the sharpness (resolution) of an image is reduced. In particular, when a character exists in a halftone dot image, the character is blurred.
There is a disadvantage that it cannot be read.

Recently, with the advancement of printers, two types of white or black
Modulation of several levels, such as ternary, quaternary, etc., is possible. When such a printer is used, gradation reproduction can be performed by a multi-value dither method.

In the multi-value dither method, various dither processings are performed depending on how to use dots at an intermediate level.

FIG. 17 is an explanatory diagram of an example of a threshold matrix (dither matrix) pattern for dither processing. The figure shows a ternary dither method for the sake of simplicity.

The method using the threshold matrix shown in FIG.
First, the first threshold matrix is sequentially filled with lower thresholds,
Next, the second threshold is filled. On the other hand, in FIG. 2B, the first and second threshold matrices are alternately filled with low-level thresholds. Therefore,
FIG. 2 (b) is more excellent in resolving power since the level of each input pixel can be reproduced more faithfully.
Poor output stability (when the same level of exposure is given to adjacent pixels and all pixels (4 × 4 = 16) are assigned, and then the next exposure level is assigned sequentially, that is, the exposure luminance difference between adjacent pixels Is small (variance value)
Since the appearance rate of the dots at the intermediate level is high (the stability is poor), the tone reproducibility of the entire matrix is poor. vice versa,
In FIG. 11A, the appearance rate of the dots at the intermediate level is kept low, so that a smooth gradation characteristic can be obtained.

As described above, in the systematic dither method, since it is difficult to achieve both gradation and resolution, a method of adaptively changing the processing method according to the type of image has been proposed.

In other words, a pattern having good gradation characteristics as shown in FIG. 17A is used for a photographic image (density gradation image) where gradation is important, and resolution performance such as characters and line drawings is important. For the image to be obtained, a pattern having an excellent resolution as shown in FIG. 3B, or binarization or multi-value processing using a fixed threshold is used.

Among the images, the halftone image has a priority on the gradation as in the case of the photographic image, and therefore, a dither pattern having excellent gradation characteristics is used. However, in the halftone dot image, minute dots are regularly arranged, and tone reproduction is performed by changing the diameter of each dot.

In the gradation processing by the systematic dither method, interference occurs between the periodic pattern of the dither and the pattern of the halftone dot document, and moire occurs.

In order to avoid the occurrence of moire, conventionally, when processing a halftone original, a smoothing process is first performed to remove a periodic component of the halftone dot, and then a gradation process is performed by the dither method. As a result, an image without moiré and with good gradation reproducibility can be obtained. However, in a halftone image (such as a printed matter), characters are often mixed in a gradation image as compared with a photographic image. By using a smoothing process and a pattern with high gradation,
There was a problem that these characters could not be read.

(Object) It is an object of the present invention to provide an image processing apparatus which solves the above-mentioned problems of the prior art, does not generate moiré in a halftone dot image, and has good reproducibility of a photographic image.

(Structure) As described above, the multi-value dither method includes the method described with reference to FIGS. 17A and 17B depending on the arrangement of dots at the halftone level. In the case of FIG. 2B, the input level of each pixel can be relatively faithfully realized by the step of the output multi-valued number, and in the case of FIG. Because the bias of
It is difficult to faithfully reproduce the input level in pixel units.

Moiré does not occur if the input data is faithfully reproduced for each pixel. However, as shown in FIG. 17 (a), moiré appears particularly remarkably when a pattern having a large bias in the threshold value for each pixel is used. Also, in the case of FIG. 17 (b), moire does not necessarily occur because the rule pattern is used, but since the input data is reproduced relatively faithfully even at the pixel level, the power of moire can be suppressed to a low level. . This moiré reduction effect increases as the number of multi-values increases, and at about eight values, moiré can be suppressed to a level at which almost no moiré is visually recognized. Further, since the halftone image is essentially a binary image, even if a pattern using a large number of intermediate levels as shown in FIG. 17B is used, the halftone dot pattern is a dot-concentrated dither signal. Since the effect is provided, unevenness (instability) of an image as in the case of using a photographic image is suppressed. As described above, the reproducibility of characters is good.

Accordingly, for a halftone image, a higher quality output can be obtained by using the pattern of FIG. 17B than by using the pattern of FIG. 17A.

The threshold layout is as shown in FIG.
If the dot concentration type is used, more stable detuning characteristics can be obtained.

Here, a case where the threshold value matrix shown in FIGS. 17A and 17B is expanded to four or more values will be described.

In the multi-value dither method, N threshold matrices are usually used to make (N + 1) values. Numbers 1 to N are assigned to this threshold matrix.

When the number of elements in the matrix is M, each element is numbered from 1 to M. If a matrix of size m × n is used, M = m × n. However, to be precise, M is the number of pixels constituting a unit of gradation expression. At this time, the threshold value of the i-th element of the j-th threshold matrix is set to thr
When (i, j) is set, thr (i, j) is represented by thr (i, j) = (i + 1) × N + j (1) in a matrix pattern of the type shown in FIG. 17 (a). In the matrix pattern of the type shown in FIG. 17B, thr (i, j) = M × (j−1) + i (2).

In the formulas (1) and (2), by changing the correspondence between the element numbers of the matrix and the positions in the matrix, a dot concentration type or dot distribution type pattern is obtained. here,
The case where the input data is a signal which is linear in density and quantized to M level is described.

Correction is necessary when the input data is not linear in density or when the output level is not linear in density.

In particular, when the number of expressible gradations (N × M + 1) is larger than the number of levels of the input data, the gradation characteristics can be set so that the output density value is linear with respect to the input density value. .

 Hereinafter, embodiments of the present invention will be described with reference to the drawings.

FIG. 1 is a system block diagram showing an embodiment of an image processing apparatus according to the present invention. FIG. 1 (a) classifies an image into a photographic part or a halftone / character part and switches the processing. In the configuration of the specific example, 1 is an input system, 2 is a photographic processing unit,
Reference numeral 3 denotes a dot / character processing unit, 4 denotes an area determination unit, 5 denotes a selector, and 6 denotes an output system.

FIG. 3B is a specific example in which the image is classified into three types, that is, a photograph portion, a halftone dot portion, and a character portion, and the processing is switched. -2 is a character part processing unit, and 5-1 is a selector.

FIG. 9C shows a specific example in which the edge is enhanced in the character portion and the edge enhancement is not performed in the halftone dot portion. Reference numeral 7 denotes an edge enhancement processor, and reference numeral 8 denotes a selector.
Note that in (b) and (c), the same reference numerals as (a) correspond to the same parts.

In each of the specific examples shown in FIG. 1, the processing results of the plurality of image processing units are selected according to the determination results of the region determining unit. As shown in FIG. In addition to selecting the processed result according to the type of the image, the dither threshold data of the processing unit for the photograph unit and the processing unit for the halftone / text unit is changed according to the area determination signal, and the edge enhancement processing unit The calculation of the edge emphasis filter may be changed.

FIG. 2 is a block diagram showing an example of the configuration of a dither processing circuit in the processing section for the photograph section and the halftone / character section processing section in FIG. 1; 10 is an x-ary counter which receives a pixel synchronization signal, 11
Is a ROM table, by storing the processing result in the address of the ROM addressed by the address of the threshold matrix having the image data and the outputs of the counters 9 and 10 as addresses,
Multi-value dither processing is performed on a table reference expression.
Here, a case where the dither matrix size is a rectangle of y × x is shown.

 Hereinafter, the configuration and operation of one embodiment of the present invention will be described.

First, a description will be given of a photograph / halftone / character separation algorithm for the area determination unit 4.

(1) Judgment Based on Colored Pixel Density This judgment is as follows: (1-1) When binarization is performed at a low level (background level + α), a pixel exceeding the background level (= colored pixel)
Can be extracted.

Therefore, it is desirable to perform MTF correction of the input system before the comparator 30 extracts a colored pixel. For this correction, an MTF correction circuit 20 is provided. The comparator 30 extracts a colored pixel when the input image data exceeds the background level (thr1) as a colored pixel.

The color pixel density filter 40 may have a size of about 4 × 4 to 8 × 8.

As described in the above (1-2), in the photographic area, almost all pixels in the scanning window are colored pixels.
The threshold (thr2) for the area determination of the comparator 50 may be set to about N to N-2 out of the number N of reference pixels in the scanning window. In addition, when the scanning window size is set to, for example, 7 × 7, the configuration can be simplified by using some pixels as shown below instead of all 49 pixels.

FIG. 4 is an explanatory diagram of a pixel arrangement example of a reference pixel.
(A) is all 7 × 7 pixels, (b) is a cross shape, (c)
Is X-shaped, (d) is rice-shaped, (e) is □ -shaped, (f) is Are shown.

In the above-described determination based on the color pixel density, as described with reference to FIG. 1, it is necessary to correct the deterioration of the MTF of the input system, particularly in the high-frequency region of the image data read by the scanner. Therefore, the MTF correction circuit 20 can be a digital filter having a high-frequency emphasis characteristic. High frequency emphasis
Usually, a method of subtracting Laplacian (second derivative) from an original image is generally used.

FIG. 5 is an explanatory view of a two-dimensional high-frequency emphasis filter used for MTF correction, wherein (a), (b) and (c) are 3 × 3 size filters, and (d) and (e) are 5 × It is a 5 size filter. Filter size is 5x3,5 rather than 3x3
More appropriate correction can be performed by using a large size such as × 5.

The filter coefficient is actually determined according to the MTF characteristics of the input system. Also, the MTF of the actual input system
According to the characteristics, the coefficient in the main scanning direction may be different from the coefficient in the sub-scanning direction.

In addition, as shown in FIG. 11B or 11C, if only pixels in four directions are used, the hardware configuration can be simplified.

FIG. 6 is a circuit block diagram showing an example of a 3 × 3 filter. In order to perform a 3 × 3 matrix operation, FIG.
Buffers 20-1 and 20-2 for 2 lines and 9 latches
20-3,20-4,20-5,20-6,20-7,20-8,20-9,20-10,2
The data of 9 pixels having a latch of 0-11 are added to adders 20-12, 20-13, 20-14, 20-15, 20-16, 20-17, 20-.
The operation shown in FIG. 5 is executed by using the multipliers 19, 20-20 and the multiplier 20-18. By using a ROM instead of the adder and the multiplier, a configuration in which a matrix operation of an arbitrary coefficient is easily performed can be adopted.

FIG. 7 is a circuit block diagram showing an example of a colored pixel density calculation circuit as a colored pixel density filter. Here, an example of counting the number of colored pixels in a 5.times.5 size scanning window is shown. In the figure, one bit of data that has been binarized to a low level is input to a shift register 40-1. The shift register 40-1 outputs binary data for five pixels (synthesized 5 bits) in the main scanning direction. Next stage counter 40-2
Then, the number of colored pixels per 5 pixels in the main scanning direction is counted.
That is, the number of "1" in the five bits is counted. Counter 40
-2 is realized by storing a value from 0 to 5 corresponding to the number of "1" in 5 bits at an address addressed by 5-bit data by using a ROM in a table reference system. it can.

The pixel density data in the main scanning direction is obtained from the line buffer 40-
3,40-4,40-5,40-6 and latches 40-7,40-8,40-9,40-
The pixel density data of the five lines is held by adders 40-12, 40-13, 40-14 and 40.
By adding at −15, the number of colored pixels per 5 × 5 = 25 pixels is calculated. This colored pixel density and a predetermined threshold th
r (approximately 25 to 23) is compared by the comparator 40-16, and if the comparison result is larger than the threshold thr, an area determination signal of "0" (photo area; if smaller, "1" (dot / character area) is output. I do.

Next, a description will be given of a photo / halftone / character separation algorithm based on edge pixel density.

(2) Judgment by Edge Pixel Density This judgment is as follows: (2-1) Edge pixels are extracted by a Laplacian operator, a Roberts operator, or the like.

(2-2) In a photographic image (density gradation), since there is little sharp change in density, the number of pixels to be edge-extracted is small.

(2-3) Since a character image is basically a binary image, many pixels are edge-extracted.

(2-4) When the density of edge pixels is calculated,
According to 2) and (2-3), the density is low in the photographic portion, and high in the character portion.

 As described above, photos / halftone dots / characters are separated.

FIG. 8 is a block diagram showing a configuration example for executing the above-mentioned algorithm (2), wherein 60 is a differential value calculation circuit, 70 is a comparator, 80 is an edge pixel density filter, and 90 is a comparator. is there.

In the figure, as a first step, a method of performing a Laplacian (secondary differential) or gradient (first differential) value on input image data in a differential value calculation circuit 60 is generally used. . The result of the differential value calculation is compared with the threshold thr3 in the comparator 70. When the calculation result is larger than the threshold, it is determined to be an edge, and when it is smaller, it is determined to be a non-edge.

FIG. 9 is an explanatory view of an example of a differential filter, wherein (a)
(D) is a second derivative filter, and (e) to (n) are first derivative filters.

In the edge extraction, the magnitude of the absolute value of the differential value becomes a problem. However, since the first-order differential filters shown in FIGS. 7E to 7N have a strong directionality, (e)-(f), (e) g)-
(H), (i)-(j), (k)-(l), (m)-
As shown in (n), the square root of the sum of squares of the orthogonal differential values f _y and f _x It is desirable to use However, for simplicity (| f _x |
+ | F _y |) / 2, max (| f _x |, f _y ) may be used. Further, an increase value of the gradient in eight directions at the pixel position of interest may be used.

FIG. 10 is an explanatory diagram for obtaining the maximum value of the gradient in the eight directions. When the gradation levels of each pixel in the 3 × 3 scanning window are a to i as shown in FIG. The density gradient (first derivative) at the position (position e) is Is obtained.

The judgment level thr3 for edge extraction by the comparator 70 in FIG. 8 is a value to be determined according to the MTF characteristics of the input system and the characteristics of the image to be extracted.

Although the threshold value thr3 may be a fixed value, a floating threshold value in consideration of the background level of the document may be used.

When the output of the differential value calculation circuit 60 is greater than the threshold thr3, the edge is determined to be an edge.

After passing through the next-stage edge pixel density filter 80, the comparator
At 90, the area of the photograph part and the halftone / text part are determined using the threshold thr4.

Advantages of using the edge pixel density include the omission of extraction of halftone dots and character portions due to the influence of noise, and prevention of post-determination in a photographic portion. The size of the density filter may be about 3 × 3 to 8 × 8.

In the block diagram of FIG. 8, it is determined whether the pixel is an edge pixel by comparing the differential value output from the differential value calculation circuit 60 of the first stage with a predetermined threshold value (thr3). The differential value calculation can be realized by using the same one as the MTF correction circuit shown in FIG. At this time, the filter coefficients shown in FIG. 9 may be used.

For the calculation of the edge pixel density and the area determination, the same one as the coloring pixel density calculation and determination circuit shown in FIG. 7 can be used. At this time, when the edge pixel density is larger than a predetermined threshold value (thr4), “1” (character area) is output, and when it is smaller, “0” (picture-photo area) is output.

Next, an area determination algorithm based on halftone dot detection will be described.

(3) Judgment by Halftone Detection This judgment is for extracting halftone dots and character areas. (3-1) Slicing and binarizing an input image.

(3-2) A halftone dot is detected from the binary image by the pattern matching method.

(3-3) For each unit block, it is determined whether or not it is a halftone dot area based on the presence or absence of a halftone dot.

(3-4) The judgment is corrected based on the judgment result of the adjacent block to reduce erroneous judgment due to noise. Perform by doing

FIG. 11 is a block diagram for an area determination algorithm based on halftone dot detection. 100 is an MTF correction circuit, 110 is a comparator, 120 is a halftone dot detection circuit, 130 is an area determination circuit, and 140 is a determination correction circuit. is there.

The halftone image is basically a binary image, and the dot diameter is modulated according to the density to be expressed. The algorithm detects this dot and
The vicinity of the area where the dot is detected is determined as a halftone dot image area. A pattern matching method is used for dot detection. However, since the dot diameter changes depending on the dot pitch and the dot area ratio, a plurality of types of templates are prepared.

FIG. 12 is an explanatory diagram of an example of a template used for the pattern matching method, in which each element (pixel) in the scanning window is shown.
_Expressed as M _ij . FIG. 3 shows three types of templates having different sizes indicated by ○, ×, and Δ.

The dot detection conditions based on the template of FIG. 12 are as follows. With respect to the pixel M ₄₄ Then, the block is divided into blocks having a size of about 8 × 8 to 16 × 16 pixels, and a block in which a halftone dot is detected is determined as a halftone dot area.

FIG. 13 is an explanatory diagram of the judgment correction processing performed after the area judgment in order to prevent an erroneous judgment due to noise or the like. For example, among adjacent blocks 1 to 4 of 8 × 8 pixels, three or more blocks are halftone dots. If it is determined that the area is an area, the remaining one block is also corrected to a halftone dot. Conversely, if the number of blocks determined as halftone dots is less than two blocks during four blocks, it is corrected that all four blocks are not halftone areas.

Hereinafter, a circuit configuration for executing the above-described algorithm of region determination by halftone dot detection will be described.

In the block diagram of FIG. 11, the area determination algorithm based on the halftone dot detection detects the dots of the halftone dots from their shapes as described above, and the performance of the detection is as follows.
Since it largely depends on the MTF characteristics of the input system, it is desirable to perform MTF correction. The image data MTF-corrected by the MTF correction circuit 100 is binarized in a comparator 110 at a normal binarization level (about 32 for 6-bit data) threshold thr5, and the template described in FIG. Is used to perform halftone dot detection. The details of the dot detection circuit 120 will be described.

FIG. 14 is a block diagram showing an example of a dot detection circuit.
FIG. 1A shows a circuit for aligning data of 49 pixels in a scanning window of 7 × 7 size.
0-1 to 120-6 and 7 × 7 = 49 bits of latch 120−
7 to 120-19. 49 pixels of the binary data M ₁₁
~M ₇₇ can be taken out simultaneously from latch group.

14 (b), (c) and (d) show halftone dot detection circuits by pattern matching.
These correspond to the three types of templates ○, ×, and に shown in FIG.

In the figure, three templates ○, ×, relative △, the judgment result n _o, n _x, and outputs the n _△.

Decision output n _o, n _x, n _△ when to match each pattern is "0", when no match "1".

FIG. 7E is a circuit diagram for obtaining a halftone dot detection signal n.
If a halftone dot is detected, “1” is output, and if not, “0” is output.

FIG. 15 is a configuration diagram showing an example of an area determination circuit.
130-1 is an 8-bit serial / parallel converter.
2 is an OR, 130-3 is a latch, 130-4 is an OR, 130-5 is a line memory, 130-6 is a latch, and 130-7 is a latch.

In the figure, the presence or absence of a halftone dot is detected for each block of 8 × 8 size, and a halftone area signal P is output.

If at least one halftone dot is detected in the 8.times.8 block, P = "1" is output, and if no halftone dot is detected, P = "0" is output.

The dot detection signal n from the dot detection circuit 120 (FIG. 11)
Is input to an 8-bit serial / parallel converter 130-1, and every 8 pixels in the main scanning direction are output in parallel to the OR 130-2 for 8 bits. The OR 130-2 outputs "1" when there is at least one "1" (halftone dot detection) out of eight bits (eight pixels). That is, it is determined whether there is a halftone dot in the 8 × 1 block. The output from the OR 130-2 passes through the latch 130-3 and the OR 130-4, and passes through the line memory 130-5.
Is stored. The line memory 130-5 stores an area determination result for every eight pixels on the first line. When the halftone dot detection signal of the second line is input, the OR 130-2 outputs an area determination signal for every eight pixels of the second line. at the same time,
The line memory 130-5 outputs a region determination signal for every eight pixels on the first line, and the OR 130-4 outputs an 8 × 2 block region determination result. Line memory 130−
5 stores an area determination result of 8 × 7 blocks.
When the halftone dot detection signal of the eighth line is input, the area determination result of the 8 × 1 block of the eighth line is input to the OR 130-4 through the latch 130-3. At the same time, the area determination results of the 8 × 7 blocks for the first to seventh lines are the same as those of the latch 130-6.
Is input to OR130-4 through. From OR130-4, 8
An area determination result of × 8 blocks is output. Each time the judgment result P of 8 × 8 blocks is obtained, the judgment result is held in the latch 130-7. 8x8 block judgment result P
Is held in the latch 130-7, the outputs of the latches 130-3 and 130-6 are cleared, "0" is written in the line memory 130-5, and the block area of the 9th to 15th lines is written. Prepare for judgment.

FIG. 16 is a configuration diagram showing an example of a judgment correction circuit,
140-1 and 140-2 are line memories, 140-3 to 140-6 are latches, 140-7 to 140-10 are 3 inputs NAND, 140-11 are 4 inputs
NAND.

In the figure, the area signal P from the area determination circuit is stored in the line memory 140-1 every eight lines. The area signal P stored in the line memory 140-1 is output every eight pixels and is held in the latch 140-3. Line memory 140
-1 performs the same operation during 8 lines. That is, 8
The same signal is output during processing of the block of × 8. When the eighth (eighth line) data is output from the line memory 140-1, the data is stored in the line memory 140-2.
Is stored.

At the same time, the data of the next block (9th line) is stored in the line memory 140-1.

Thus, the line memories 140-1 and 140-2 store the area signals of the blocks adjacent to each other in the sub-scanning direction. 8 from the line memories 140-1 and 140-2
An area determination signal is output for each pixel, and latches 140-3, 140
−4. The outputs of the latches 140-3 and 140-4 are latched by the next-stage latches 140-5 and 140-6 every eight pixels.
These four latches have three as shown in FIG.
According to the input NANDs 140-7 to 140-10, when at least three of the four adjacent blocks are determined to be a halftone dot area, the block of interest is determined to be a halftone dot area. The area is determined. Here, "1" is output from the four-input NAND 140-11 when it is determined to be a halftone dot area, and "0" is output when it is determined to be a non-halftone dot area.

The three types of area determination methods (1), (2), and (3) have been described above.

Since both of the area determination methods (1) and (2) perform determination of a photograph area / halftone dot / character area, either one may be used. However, in (1), the background is determined to be a character area, so that the highlighted portion of the photograph is easily determined to be a character area. Conversely, a low density character is determined to be a character area, which is convenient. In (2), the background portion is determined to be a photo region, which is convenient for a highlight portion of a photo, but has a feature that low-density (low-contrast) characters are easily extracted and omitted.

On the other hand, in the determination method (3), a halftone dot / character area is determined, and a photograph of continuous tone (density tone) is determined as a character area. As described above, by using the determination method of (1) or (2) and (3), an image can be separated into three types of photo / halftone / character or two types of photo / halftone / character. it can.

As described above, in the present embodiment, the photographic image (density gradation image) and the halftone / character image are separated, the centralized dither processing is applied to the photographic image area, and the halftone / character area is By applying distributed dithering, the photographic image is not unnecessarily smoothed, the sharpness is improved, and the halftone / character area is displayed, for example, as shown in FIG. 17 (b).
By performing the dither processing of the pattern as shown in (1), moiré can be suppressed, and an output image with good sharpness can be obtained. By applying distributed multi-value dither processing to halftone dots and character areas, density smoothing can be eliminated and good results can be obtained for characters.
Halftone dots and characters can be further separated.

Further, in the above, when an image is separated into two types of photos / dots / characters, only one of the determination methods (1) and (2) may be used, and the configuration is simplified.

(Effects) As described above, according to the present invention, an image is separated into a density gradation image (photograph) and an area gradation image (halftone image or text), and a dither pattern suitable for each image is obtained. By applying the gradation processing, the sharpness of any image can be improved, and the shaded characters can be realized in a sharp manner.

[Brief description of the drawings]

FIG. 1 is a system block diagram showing an embodiment of the present invention.
FIG. 2 is a block diagram showing a configuration example of a dither processing circuit, FIG. 3 is a block diagram for an area determination algorithm based on a colored image density, FIG. 4 is an explanatory diagram of a reference pixel arrangement column, and FIG.
FIG. 6 is an explanatory diagram of a two-dimensional high-frequency emphasis filter used for MTF correction, FIG. 6 is a circuit block diagram showing one row of a 3 × 3 filter, FIG. FIG. 8 is a block diagram for an area judging algorithm based on edge pixel density, FIG. 9 is an explanatory diagram of an example of a differential filter, FIG. 10 is an explanatory diagram for obtaining a maximum value of gradients in eight directions, and FIG. Is a block diagram for an area determination algorithm based on halftone dot detection, FIG. 12 is an explanatory diagram of an example of a template used for a pattern matching method, FIG. 13 is an explanatory diagram of a judgment correction process, and FIG. 14 is a halftone dot detection circuit. FIG. 15 is a configuration diagram illustrating an example of a region determination circuit,
FIG. 16 is a configuration diagram showing an example of a judgment correction circuit, and FIG. 17 is an explanatory diagram of an example of a threshold matrix pattern for dither processing. DESCRIPTION OF SYMBOLS 1 ... Input system, 2 ... Processing part for photography parts, 3 ... Processing part for halftone / character parts, 4 ... Area determination part, 5 ... Selector, 6
…… Output system.

 ──────────────────────────────────────────────────続 き Continuation of the front page (56) References JP-A-63-288565 (JP, A) JP-A-61-90068 (JP, A) JP-A-61-82577 (JP, A) JP-A-62 53072 (JP, A) JP-A-63-166543 (JP, A) JP-A-58-7796 (JP, A) JP-A-57-25771 (JP, A) JP-A-61-131682 (JP, A)

Claims (1)

(57) [Claims] 1. An image processing apparatus for performing gradation processing by inputting image data relating to one image and outputting image data subjected to gradation processing, wherein a region in the input image is a photographic image. And a first gradation processing means for performing dot concentration type dither processing on an area determined as a photographic image by the first judgment means. An image processing apparatus comprising: a second gradation processing unit that performs a dot dispersion type dithering process on an area determined by the first determination unit to be a halftone area.