JPH05145751A - Area discriminating signal processing circuit of color image processor - Google Patents

Abstract

PURPOSE:To eliminate a variance of an area discriminating signal generated at every scan, and to prevent a color variation from being generated in a black character and a line, etc. CONSTITUTION:In the color image processor for blocking plural picture elements, executing an area discrimination of a character/a halftone, switching a parameter by an area discriminating signal and executing a formation processing of a color image, the area discriminating signal of a first scan obtained by an area discriminating circuit 1 is stored in a memory 4 and used for a scan of a second time and thereafter. By collating the area discriminating signal of the scan of a second time and thereafter with the area discriminating signal stored in the memory and deciding it, for instance, in the case of a black character by a first scan, a black character is obtained in a second time and thereafter, as well, and in the case the area discriminating signal of a black character is obtained by the area discriminating circuit 1 in a second time and thereafter, although it is not a black character by a first scan, as well, a halftone is obtained. In such a way, a variance of the area discriminating signal is eliminated and generation of a color variation in the black character and the line, etc., is prevented. Also, by storing the area discriminating signal in a memory by one bit, and storing it by a two-block unit, the memory capacity can be reduced.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to area identification signal processing of a color image processing apparatus for performing character / halftone area identification by dividing a plurality of pixels into blocks and switching a parameter according to the area identification signal to form a color image. Regarding the circuit.

[0002]

2. Description of the Related Art In a color image processing apparatus such as a color copying machine, Y (yellow), M (magenta), C (cyan),
A four-color toner developing device of K (black) is used, and these images are superposed to reproduce a full-color image. Therefore, scanning is repeated four times according to the developing process of each toner, and the full-color image data obtained by reading the original is processed each time.

FIG. 8 is a diagram showing a configuration example of a conventional color image processing device and a configuration example of an image area identification circuit.

Generally, in a color image processing apparatus, an original is optically read by using a line sensor, and B (blue) and G are read.
When the image data is fetched by the color separation signals of (green) and R (red), the image data is converted into EN as shown in FIG.
After the gray balance is adjusted by the D conversion 31, the color separation signal B is obtained by the color masking (color correction) 32.
The color material signal YMC is converted from GR. Then, UCR33 generates black plate (K) and removes undercolor,
The hue separation type non-linear filter section removes moire and halftone dots and enhances the edges, and turns on the color material signal X expressed in multiple gradations of the development color through TRC (tone adjustment) 40 and SG (screen generator) 41. The image data of each color is formed by exposing the charged photoconductor by controlling the laser light with this binary data.

In the color separation type non-linear filter unit, the UCR
In 33, the image data X of the development color is selected and input according to the development process from the YMCK signal generated by performing black plate generation and undercolor removal processing, and branched into two systems. A smoothing filter 34 is connected to one of them, and a γ conversion circuit 36, an edge detection filter 37, and an edge enhancement LUT 35 are connected to the other. The former system performs smoothing processing for removing moire and halftone dots on the halftone image, and the latter system performs edge enhancement processing on the character image. The adder 39 synthesizes these outputs, and the synthesized signal is output as a signal after the nonlinear filter processing. In this case, in the edge processing, the hue of the input image is detected by the hue detection circuit 35,
It is determined whether the development color at that time is a required color. Here, if the input image is a black area, Y, M, C
No edge enhancement of the chromatic color signal is performed, and only K is controlled to be enhanced according to the edge amount.

By introducing the non-linear filter processing as described above, binary images such as characters and line drawings of different types and binary images such as characters and line drawings for originals such as photographs and halftone dot prints are Non-linear filter processing to enhance the sharpness by emphasizing edges and smoothing halftone images such as photographs and halftone dot prints to remove moire and halftone dots to enhance image smoothness and graininess. It is carried out.

However, in the case of a binary image such as a character or a line drawing and a halftone image such as a photograph or a halftone dot printed matter, if it is easy to specify each original or area in advance, it is possible to specify each original or area. By specifying the image type for each area, it is possible to select the optimum parameters for each area and improve the reproducibility. However, in the case of these mixed images, it can be used as a binary image or a halftone image. Also, parameters that can be reproduced as such will be selected. In this case, the optimum processing is not performed on the binary image or the halftone image, so that it is difficult to obtain an image that is satisfactory for both.

For example, in a binary image, the edge emphasis is weak and blurred, so that the characters are not clear, and in the case of black characters,
There is a problem that turbidity occurs at edges and small letters. On the other hand, with respect to the halftone image, since the vicinity of the edge detection frequency is emphasized, the halftone image loses smoothness and becomes a rough image with strange moire and edges emphasized. Therefore, it is necessary to identify three types of image areas of black characters, color characters, and halftones, and switch the parameters of the filter unit, and several identification processing methods of this type have been proposed.

For example, the configuration shown in FIG. 8B (see Japanese Patent Application No. 2-2940) introduces a run-length identification method. The hue detection unit 41 detects any of the hues of eight colors (Y, M, C, K, W, B, G, and R) for each pixel, and the comparator 42 sets the maximum of YMC. It is for detecting whether or not an item is equal to or more than the threshold value th _max . Since the hue detecting unit 41 also detects low-density noise and the like, in this case, the run length described later becomes short, and there is a problem in that it is erroneously recognized as a character area. Therefore, in order to make a pixel having at least a certain density or more a character candidate, a comparison determination with the threshold th _max is performed to remove noise, thereby the comparator 42.
Is.

The blocking unit 43 has several pixels, for example, 4 × 4.
Each pixel is divided into blocks of up to 8 × 8, and the block determination unit 44 performs 7-color determination. In the 7-color determination, the maximum frequency color in the block is determined for 7 colors (Y, M, C, K, B, G, R) excluding W, and this is set as the block color. For example, the frequency of each color is counted with 4 × 4 pixels as one block, and K = 6 and M =
If 2, R = 1, C = 1, and W = 6, the color excluding W / the maximum color K among black pixels is adopted as the block color.

The main scan direction color run count section 46 is
The block color determination unit 44 receives 1 bit representing W (0) or black (1) other than that, and counts the run length of the color / black block in the main scanning direction. It is determined whether or not the count value (run length) of each block is shorter than the threshold value th _run . Here, if the run length of the color / black block is shorter than the threshold value th _run , it becomes a character candidate.

When viewed in terms of run length, the dot length in the pixel unit is short like the character region and it is difficult to separate from the character, but in the block unit the run length of the dot region is long, In the case of a character area, the block run length becomes shorter because the distance between characters is longer than the pitch of halftone dots. In this way, the block run length enables distinction between a character and a halftone dot area.

The sub-scanning direction edge detection unit 45 detects whether or not there is an edge within a range of several blocks in the sub-scanning direction, and if there is an edge, it is a character candidate. This is because the horizontal line used in the character area also has a long run length, and thus the run length in the main scanning direction is not a candidate for a character, and therefore, in such a case as well, it is to be detected as a candidate for a character. ..

The OR gate 48 and the AND gate 49 have character candidates in either the main scanning direction or the sub scanning direction based on the above detection results, and the max flag of the block is 1.
If so, this block is determined to be a character area, and the block color signal determined by the block color determination unit 44 is output. The max flag is set to Y in the comparator 42.
This is a signal indicating that the maximum number of MCs is 1 or more in the block, which is determined to be the threshold th _max or more.

The above example focuses on the short run length around the character portion. That is, the character part is composed of a block of characters and a block of the background, and the density changes sharply because it is in the background of the background, whereas the image part is in the image background and the density is gentle. .. Therefore, when the run length is observed, the run length is short in the character region and the run length is long in the halftone region. Moreover, it was difficult to distinguish between a halftone dot area and a character area on a pixel-by-pixel basis, but in the case of halftone dots, the run length becomes longer by blocking, so it is necessary to recognize in the halftone area instead of the character area. You can In other words, due to the block formation, halftone dot patches having a high frequency also tend to occur as color blocks with long run lengths,
It can be captured as a halftone area. Further, if the main scan direction color run count unit 46 and the comparator 47 only detect character candidates, a line with a long run length in the main scan direction will be mistakenly recognized. In some cases, the recognition accuracy is improved by using the character candidates.

The configuration shown in FIG. 8C (see Japanese Patent Application No. 2-136071) detects the maximum value and the minimum value from a plurality of pixels in block units, and the difference between them is larger than a predetermined value. Whether or not the character area is identified, error correction is performed based on the area determination result of the surrounding blocks, and the area identification circuit is roughly divided into primary identification and secondary identification. The primary identification is the 8 × 8 blocking circuit 61.
In order to identify the character area by dividing the block into 8 × 8 pixels, the maximum value detecting circuit 62 and the minimum value detecting circuit 63 determine the maximum value and the minimum value from the 8 × 8 pixel of the block. It is detected and the difference is obtained by the arithmetic circuit 64. Then, the comparator 65 compares the output of the arithmetic circuit 64, that is, the difference between the maximum value and the minimum value with the threshold value th, and when the difference is larger than the threshold value th, outputs a character region identification signal, for example, logic "1". .. The secondary identification further corrects the error in the identification area of the block by the primary identification in the 3 × 3 block.

For example, when the target block is identified as a character region by the primary identification, and most of the surrounding blocks are not the character region, the identification content of the target block is corrected to the non-character region. Similarly, when the target block is identified as a non-character region by the primary identification and most of the surrounding blocks are character regions, the identification content of the target block is corrected to the character region.

FIG. 9 is a diagram showing a configuration example of the hue detection circuit. The hue detection circuit includes a maximum value circuit 71 and a minimum value circuit 7 for obtaining maximum and minimum values of Y, M and C as shown in (a).
2. Subtraction circuit 73, Y, for obtaining the difference between the maximum value and the minimum value
It has subtraction circuits 74 to 76 and comparators 77 to 81 for obtaining the difference between M and C and the minimum value. The comparator 77 outputs the output (max-min) of the subtraction circuit 73 and the threshold th1, and the comparator 78 outputs the minimum value (mi).
n) and the threshold value th2, the comparator 79 calculates the subtraction circuit 74
Output (Y-min) and the threshold value th3,
0 is the output (M-min) of the subtraction circuit 75 and the threshold value th4.
The comparator 81 outputs the output of the subtraction circuit 74 (C-mi
n) is compared with the threshold value th5, and each value is the threshold value t.
Signals r, m, c ', m', and y 'which are logic "1" when larger than h1 to th5 are output. And
From this output, the judgment hue is derived based on the judgment condition shown in FIG. 8B, and the development color is required color “1” or unnecessary color “0”.
To determine. As the judgment hue, W (white), Y, M, C, B, G, R, and K, which are used as the colors of ordinary characters, are used.
The determination ROM 82 performs the hue determination of the table shown in FIG.

In addition to the above, the average value and the standard deviation in a predetermined pixel block are used (for example, JP-A-63-205).
No. 783) or a method using binary output converted by a plurality of dither conversions having different phases (for example, Japanese Patent Laid-Open No. 63-1937).
No. 70), the maximum value and the minimum value in the block are obtained for each of the R, G, and B color separation signals, and at least 1
When the difference between two color components is a predetermined value or more, it is determined as a character area (for example, Japanese Patent Publication No. 63-51
Various systems have been proposed so far.

[0020]

However, even with the above-described conventional various area identification methods, it is possible to improve the identification performance by surely making the block determination, but in reality, the speed of the apparatus is increased and the high performance is achieved. In order to obtain a color copy with high image quality, it is necessary to operate the document reading at a high speed and process the read image data at a high speed. Therefore, for example, it is developed by vibration or noise due to mechanical operation of the image processing apparatus. There is a problem in that variations in area recognition occur in the process, and defects such as interruptions of black characters appear.

That is, in color copying, since a full-color image is reproduced by superposing toner images of Y, M, C, and K by four scans as described above, the difference between the maximum and minimum values and the run Even if area determination is performed in block units using each feature amount such as length, average value, standard deviation, etc., the same area determination result is obtained through four development processes of Y, M, C, and K. If it is not obtained, the image quality is rather deteriorated.

For example, if the black character area is determined in the M and C developing processes, but the black character area is not determined in the Y and K developing processes, the black character is interrupted in the block and output as Y. Will be done. That is, since M and C are the determination of the black character area,
Since K is also a determination other than the black character area, the output is suppressed, and only Y is output. In particular, if processing is performed such that the YMC is reproduced by reproducing only K in the black character identification area and the K signal is reset in the color character identification area,
If the area identification is wrong, the color characters may change to black characters, or color change due to color loss may occur.

Moreover, if YMC is reset in the case of a black character by performing area identification, the background color portion becomes blank, but if K is reset in the case of a color character, in the case of blue, not only MC but usually Due to YK, blue reproducibility is extremely reduced. Further, since the determination is made in blocks and the output is performed, the situation in which black characters are changed to colored characters becomes more conspicuous and the blocks are visible, as compared with the output in pixel units. Since such a defect also appears in the area of color characters and halftones, there is a problem that the image quality is significantly deteriorated.

Further, in the conventional method, the hardware configuration is complicated, and conversely, if it is simple, the identification performance is poor, and there is nothing to be satisfied. In particular, it is difficult to match the hardware for black character / color character identification to correspond to a color image, and it is unavoidable that the system is separated from the area identification.

An object of the present invention is to eliminate the variation in the area identification signal generated for each scan. further,
Another object of the present invention is to prevent the occurrence of color change in black characters and lines.

[0026]

To this end, the present invention provides a color image processing apparatus for dividing a plurality of pixels into blocks, performing character / halftone area identification, and switching a parameter according to an area identification signal to perform a color image forming process. A feature is that the area identification signal of the first scan is stored in the memory and is used for the second and subsequent scans, and the area identification signal of the second and subsequent scans is compared with the area identification signal stored in the memory for determination. To do. Further, it is characterized in that a black character / other 1-bit area identification signal is stored in a memory, and a logical sum or a logical product of the area identification signals is obtained and stored in units of two blocks.

[0027]

In the area identification signal processing circuit of the color image processing apparatus of the present invention, since the area identification signal of the first scan is stored in the memory and used for the second and subsequent scans, the area identification signal of the first scan is used. In particular, when processed as black characters, priority is given to this area identification signal even after the second time, whereby variations can be eliminated and color changes in black characters and lines can be prevented. Further, by storing the area identification signal in the memory in 1-bit units and in units of 2 blocks, the memory capacity can be reduced.

[0028]

Embodiments of the present invention will be described below with reference to the drawings. FIG. 1 is a diagram showing an embodiment of an area identification signal processing circuit of a color image processing apparatus of the present invention.

In FIG. 1, input signals L ^* , a ^* , b ^*.
Is an 8-bit signal expressed as a system value, in which the L ^* axis represents lightness, and the a ^* axis and b ^* orthogonal to the lightness ^.
The two-dimensional plane of the axis represents saturation and hue. The area identification circuit 1 determines a pattern / background / character, color / black and white by dividing a plurality of pixels into blocks, and synthesizes these to generate an area identification signal of halftone / black character / color character. The decoder 2 decodes the 2-bit area identification signal of the area identification circuit 1 from the halftone / black character / color character to 1-bit black character information indicating whether it is a black character or a non-black character. Bit black character information 4
It is a serial / parallel converter that collects bits. The memory 4 stores the black character information obtained by the first scan, and the address generation circuit 5 generates the read / write address. P / S converter 6
Is for converting 4-bit unit black character information read from the memory 4 into a serial signal after the second scan, and the decoder 7 receives the second character from the black character information of the memory 4 and the area identification signal of the area identification circuit 1 for the second time. The area identification signal for the subsequent scans is generated. The selector 8 selects the area identification signal of the area identification circuit 1 in the first scan, and selects the area identification signal of the decoder 7 in the second and subsequent scans.

In the decoder 7, if the black character information of the memory 4 is "1", that is, if the area identification information of the first scan is a black character, the area identification information of the second and subsequent scans is a halftone or a color character. Even if the black character area identification information is output, and the black character information is “0”, halftones and color characters of the area identification information of the second and subsequent scans are output as they are, and even if the black character is a halftone Output. This means that, for example, if the developing process is in the order of Y, M, C, K,
If the area identification information of the first scan is black characters, Y is reset and is not output. Therefore, if the area identification information other than the black characters is output as it is in the second and subsequent scans,
This is because M and C are output and a color change occurs. Similarly, when the area identification information of the first scan is not a black character, if the area identification information of the black character is output as it is in the second and subsequent scans, M and C are reset and Y and K are output.

As described above, in the area identification signal processing circuit of the color image processing apparatus of the present invention, the area identification result of the first scan is stored in the memory, and in the second and subsequent scans, the area identification stored in the memory is stored. Although the final determination result is determined while collating the results, it goes without saying that the area identification result stored in the memory may be used as it is. Further, when the area identification result is stored in the memory, it is stored in black character / other 1 bit in the above example, but it may be stored in character / halftone, or by ORing two blocks. They may be integrated or may be configured to be integrated and stored by taking a logical product AND.

Next, the area identification circuit will be described. FIG. 2 is a diagram showing a configuration example of an area identification circuit applied to the present invention.

In FIG. 2, the non-linear quantizer 11 compresses the 8-bit signal L ^* of each pixel to 4 bits, and the quantizer 12 thresholds the 8-bit signal L ^* of each pixel. The 2-bit signal, which is divided into high level / intermediate level / low level by th1 and th2, is output, and the hue discriminator 13 outputs the 8-bit signal L ^* of each pixel.
It outputs a 2-bit hue signal that discriminates color, black or white from a ^* and b ^* .

The block FIFO 14 holds data of 4 lines in the sub-scanning direction and 8 pixels in the main scanning direction, and stores 4 ×.
8 blocks are formed, and one line is thinned from each of the 8 input lines to hold 4 lines, thereby forming a block corresponding to a size of 8 × 8. The data of one pixel held in the block FIFO 14 is 8 bits consisting of a compressed 4-bit signal L ^* , a 2-bit level division signal and a 2-bit hue signal, and each 4-bit signal L ^* is an average value. Calculation circuit 16
The 2-bit level division signal is distributed to the counters 17 and 18, and the 2-bit hue signal is distributed to the block hue discriminator 19.

The average value calculation circuit 16 calculates the average value Pa in the block by adding the signals L ^* of the pixels in the block. The counter 17 counts the high level pixel number Ph from the level division signal, and the counter 18 counts the intermediate level pixel number Pm. In the quantizer 12, the low level threshold is th1, the high level threshold is th2, and when the signal L ^* is between the thresholds th1 and th2, only the lower bit of the two bits is set to “1”, When exceeding the threshold th2, if only the upper bits are set to "1", the counter 17 counts the upper bits and the counter 18 counts the lower bits.

The non-linear quantizers 20 to 22 compress the data of the average value calculating circuit 16 and the counters 17 and 18, respectively, and the LUT 23,
The comparator 24 generates a character / halftone determination signal.
The LUT 23 is a Pa-in the three-dimensional space shown in FIG.
The threshold value of Pm in a block which is a character area on the Ph plane (left side plane in the drawing) is read out, and the comparator 24
If this threshold value is larger, the solid line block is entered in the three-dimensional space shown in FIG. 7, and the character region determination signal is output. The adder inserted between the LUT 23 and the comparator 24 is connected to the LUT2 by the bias TH _bias.
3 is to adjust the bias of the threshold value read out from No. 3, and to adjust the character area.

The comparator 15 and the flag detector 25 detect whether or not the block is a background block. The 4-bit signal L ^* compressed by the comparator 15 is compared with a threshold value TH _av to detect the flag detector 25. It is for detecting whether or not there is a pixel exceeding the threshold value TH _av in the block. Therefore, here, when all the pixels in the block are smaller than the threshold value TH _av , it is determined to be the background. In other words, if there is at least one pixel that exceeds the threshold TH _av , it is not a character / halftone but a background. Error correction circuit 26
Is for inputting a character / halftone determination signal and a background detection signal and performing correction in larger blocks by comparing with the determination signals of surrounding blocks, for example, and outputting a character / halftone determination signal. To do.

The block hue discriminator 19 uses the block F
The hue signal of each pixel that has been blocked by the IFO 14 is used to discriminate a hue of color or black and white on a block basis, for example, by a majority decision, and the delay circuit 28 delays the color / black and white block hue signal to correct an error. This is to be synchronized with the character / halftone determination signal of the circuit 26. The final judgment circuit 27 finally outputs a color character / black character / halftone T / I (text image) area judgment signal from the character / halftone judgment signal and the color / monochrome block hue signal. is there.

FIG. 3 is a diagram showing a modification of the image area identification circuit, FIG. 4 is a diagram for explaining the distribution of color characters / halftone images, and FIG. 5 is a diagram for explaining an example of the distribution state of character areas. 6 and 6 are diagrams for explaining parameter optimization conditions.

In a document in which a binary image such as a line drawing or a character and a halftone image such as a photograph or a halftone dot are mixed, the characteristic amounts of the character and the halftone area are collected in a blocked area. However, they adopt a feature quantity limited to one such as a run length or a difference between the maximum value and the minimum value. On the other hand, according to the present invention, a predetermined number of pixels are divided into blocks, the average value Pa in the block, the number of high level pixels in the block Ph, and the number of intermediate level pixels in the block Pm are sampled, and their three-dimensional distribution state is obtained. FIG. 3 shows an example of the basic configuration for determining the area from
Is.

In the example shown in FIG. 3A, first, the 8-bit average value Pa in the block, the 6-bit in-block high-level pixel number Ph, and the 6-bit in-block intermediate-level pixel number P.
m is 3 bits, 4 bits, and 4 in quantizers 1 to 3, respectively.
After quantizing into bits, the threshold value TH is read from the average value Pa in the block and the number of high level pixels in the block Ph by the 7-bit LUT 4, and the threshold value is compared by the comparator 5 with the number of intermediate level pixels in the block Pm. / To obtain a halftone area determination signal.

On the other hand, the embodiment shown in (b) uses the quantized intra-block average value Pa, intra-block high level pixel number Ph, and intra-block intermediate level pixel number Pm to obtain 1
A 1-bit LUT 6 is used to obtain a character / halftone area determination signal. Further, in the embodiment shown in (c), the average value Pa within a block and the number of high-level pixels within a block remain as they are without quantization. By using Ph and the number Pm of intermediate level pixels in the block, a 20-bit LUT 7 is used to obtain a character / halftone area determination signal.

Considering a manuscript in which characters and halftones are mixed, as shown in FIG.
And a low level threshold th2 are set, the character sharply rises from a low level background such as A,
There are many high-level pixels that exceed the threshold th1 and low-level pixels that do not reach the threshold th2, and few intermediate-level pixels between the thresholds th1 and th2. That is, there are relatively more low-level backgrounds than high-level character parts. On the other hand, halftones are evenly distributed in each level as in B, but when viewed in a region, they are distributed in low level and intermediate level, in intermediate level, and in intermediate level and high level. If it is distributed, it will be distributed at a high level. Therefore, when viewed in terms of the average value (average value Pa within the block) and the frequency, the characters are distributed to the lower average value and the halftones are distributed to the higher average value, as shown in (b). .. Therefore, the respective feature quantities are as follows.

In the case of the character area, since there are more backgrounds than the high level of the character portion, the average value Pa in the block is low, there are at least one high-level pixel, and at least one low-level pixel. There are more than pixels. If this condition is not satisfied, for example, if all of the blocks are high-level pixels, the halftone area will be obtained. Therefore, when the above-mentioned three feature quantities are viewed three-dimensionally, the distribution state of the character area is as shown in FIG. That is, it can be seen that the range of characters can be considerably limited by combining the three types of characteristic values.

Now, assuming that the total number of all pixels in the block is Pt, the character area must satisfy at least the following conditions.

Ph + Pm ≦ Pt−1 1 ≦ Ph ≦ Pt−1 That is, when viewed from the plane consisting of Ph and Pm, the character area is distributed in the black background area and the halftone area is distributed in the white background area. To do. Therefore, the character area becomes the first area when and is satisfied.

Further, the actual identification parameter is determined by statistically analyzing each image data and taking the above conditions into consideration. The configuration for realizing this is shown in FIG. 3 described above, and (c) stores the identification result in the three-dimensional LUT in advance, and Pa, Ph, and Pm are 8, 6, and 6 respectively. The configuration is such that 20 bits obtained by combining the bit results are input as the address of the LUT. On the other hand, in (b), since the capacity of the LUT is reduced, Pa, Ph, P
A quantizer is inserted in m and each data word length is compressed to reduce the capacity of the LUT. That is, LSI
In order to realize this, it is necessary to make the memory as small as possible internally, and in this case, reduction of up to 11 bits of 3, 4, 4 is realized. Of course, this quantization cannot be simply applied, but by making the distribution state of Pa, Ph, and Pm and the quantization non-linear, it can be confirmed that even this level of compression does not hinder the discrimination performance. It was And
In (a), the hardware scale in (b) is further reduced by paying attention to the characteristics of Pm, and the configuration uses a two-dimensional LUT and one comparator. This is because the distribution state of Pm in the character area is always Pm when looking at FIG. 5 and FIG.
It is noted that = 0 is set as the minimum value and Pm ≦ Pt−Ph−1 is set as the maximum value. From this, it can be seen that the determination method of the character area when the value of Pm is smaller than the threshold value of the maximum value of Pm which is predetermined by Pa and Ph and the halftone area when the value of Pm is large can be realized. As a result, the hardware feasibility can be improved without deteriorating the identification performance.

Next, a configuration example of the image processing apparatus applied to the present invention will be described. FIG. 7 is a diagram showing a configuration example of a signal processing system of the image processing apparatus.

In FIG. 7, the image input section 100 includes, for example, three CCs of B, G and R arranged at right angles in the sub-scanning direction.
A reduction type sensor including a D line sensor is provided, and an image is read by scanning in the main scanning direction in synchronization with a timing signal from the timing generation circuit 12 while moving in the sub-scanning direction at a speed according to the expansion / contraction ratio. IIT, which is analog image data and is converted into gradation-represented 8-bit digital image data, for example. The shading correction circuit 11 performs shading correction on the image data for variations between pixels due to various factors, and the gap correction circuit 13 performs gap correction between the line sensors. The gap correction is FIFO14
Is to delay the image data read by the amount corresponding to the gap of the CCD line sensor so that the B, G, and R image data at the same position can be obtained at the same time. An ENL (Equivalent Neutral Lightness) conversion circuit 15 performs gray balance processing of image data using a parameter according to a document type, and a negative / positive inversion signal from an editing processing unit 400 described later. This makes it possible to invert the way gray is taken for each pixel and invert the negative / positive, for example, to invert the negative / positive only in a certain designated area.

B, G, processed by the ENL conversion circuit 15
The R image data is converted into signals L ^* , a ^* , b ^* in the uniform color space, for example, by the matrix circuit 16a. In the uniform color space signals L ^* , a ^* , and b ^* , L ^* represents lightness on the coordinate axes orthogonal to each other, and a ^* and b ^* are chromaticity planes (hue,
Represents the saturation). Such a uniform color space signal L ^* ,
The memory system 20 is converted into a ^* and b ^*.
It is possible to easily interface with the outside such as a computer through 0, and to facilitate color conversion, edit processing, and detection of image information. The selector 17 is the matrix conversion circuit 1
The output of 6a or the image data from the memory system 200 which is an interface with the outside is selectively taken out, or both image data are taken in at the same time to perform the texture synthesizing process and the watermark synthesizing process. Therefore, the selector 17 has a function of performing the setting of the combining ratio, the calculation process, and the combining process for the combined image.

The background removal circuit 18 detects the background density by creating a histogram of the document density by pre-scanning, for example, and skips pixels below the background density to improve the copy quality for a fogged document such as a newspaper. It is for. The document detection circuit 19 detects and stores the document size by detecting the boundary between the back surface of the black platen and the document and determining the circumscribed rectangle. In the background removal circuit 18 and the original detection circuit 19, the lightness information of the signals L ^* , a ^* , and b ^{* in} the uniform color space is signal L ^*.
Is used.

The edit processing section 400 sets area commands for performing edit processing and switching of parameters etc. for each area, and generates area control signals based on the area commands to perform color editing and color editing on image data. Conversion, marker color detection, and other processing are performed. Then, the processed image data is input to the matrix conversion circuit 16a and the pictographic character separation circuit (TIS circuit) 20.

In the matrix conversion circuit 16a, L ^* , a ^* , b ^* to Y, and
After being converted into M and C toner colors, the picture character separation circuit 20 divides a plurality of pixels into blocks to identify areas of color character / black character / picture (character / halftone). In the under color removal circuit 21, Y converted by the matrix conversion circuit 16b,
The black (K) generation is performed from the M and C image data according to the mono-color / full-color signal, and the equal amounts of Y, M, and C are removed, and the process color image data is output. A judgment is made to generate a hue signal (Hue). When the pictogram separation circuit 20 performs the identification processing, the area identification signal is delayed by, for example, 12 lines due to the block formation. Therefore, a timing is taken to synchronize the hue signal and the image data with the delay. FIFO2
2a and 22b.

The scaling circuit 23b scales the image data according to the designated scaling ratio. In the sub-scanning direction, the image input unit 100 scales the scanning speed according to the scaling ratio. Since the image data is expanded, the image data is thinned out or interpolated in the main scanning direction. The expansion / contraction circuit 23a is for expanding / contracting the area command so that the execution area of the area control information does not shift in correspondence with the expansion / contraction processing on the image data. The area control information subjected to the reduction / expansion processing is the area decoder 24.
Are decoded by and processed by each processing block. The area decoder 24 uses an area command, an area identification signal,
The switching signal of the parameter 25 of the filter, the coefficient of the multiplier 26, and the parameter of the TRC circuit 27 is generated from the hue signal and distributed.

The filter 25 removes halftone moire and emphasizes edges of characters on the image data reduced or enlarged by the reduction / enlargement circuit 23b according to the spatial frequency. The TRC circuit 27 is for adjusting the density according to the characteristics of the IOT using the conversion table,
29 is TRC by the signal of the development process and area identification
It is a decoder that switches the parameters of the conversion table of the circuit 27. The multiplier 26 performs ax + b calculation on the image data x using the coefficients a and b, and the coefficient is switched between through in the case of halftone and high γ in the case of character. By appropriately selecting the coefficient and conversion table for each color component used in combination with the TRC circuit 27, data reset, color adjustment, and density adjustment for color characters, black characters, and patterns are performed. Further, the parameters of the filter 25 can be standardized, and the edge emphasis of the character can be adjusted by the coefficients a and b. The image data adjusted by these is stored in a memory system or RO
In the screen generation unit 28 of S300, dots are expanded and output as a halftone dot image.

The editing processing section 400 performs color conversion, color editing, generation of a region control signal, etc., and receives image data L ^* , a ^* , b ^* from the selector 17. Then, the LUT 415a converts the chromaticity information from a and b in the orthogonal coordinate system into C and H in the polar coordinate system so that the marker color and other colors can be easily detected, color edited, and converted. The color conversion & palette 413 has, for example, 32 kinds of colors used in color conversion and color editing, and the delay circuit 411.
The image data L, C, and H are subjected to marker color detection, color editing, color conversion, and other processing in accordance with area commands input through a. Then, only the image data of the area where the color conversion or the like is performed is performed by the color conversion & palette 41
After being processed by the LUT 415b and converted back from C, H to a, b, the image data of the other areas is directly output from the selector 416, and the matrix conversion circuit 16 described above is used.
sent to b.

The marker color (3 colors) detected from the image data by the color conversion & palette 413 and the 4-bit signal of the closed area are sent to the density conversion / area generation circuit 405. Density conversion
In the area generation circuit 405, the FIFOs 410a, 410
In the 4 × 4 window using b and 410c, the density conversion from 400 spi to 100 spi is performed by performing the binarization process of setting “1” when the number of black pixels is equal to or larger than the predetermined number in 16 pixels. The marker signal (closed loop or marker dot) generated in this way is written in the plane memory 403 from the density conversion / region generation circuit 405 through the DRAM controller 402.

As for the marker / dot signal, the FIF is set so that small dust or the like is not erroneously detected as a marker.
The coordinate value generation circuit 407 detects the marker dot and generates the coordinate value and stores it in the RAM 406 by delaying by 3 lines by O408 to form a 3 × 3 window. For the marker dot, the plain memory 40
3 is stored, but this process is performed to prevent erroneous detection.

The plane memory 403 is a memory for storing area commands for performing color conversion, color editing, and other area editing. For example, the area is designated from the edit pad and the area command is written in the area. be able to. That is, the area command of the area designated by the edit pad is transferred to the graphic controller 401 through the CPU bus and written from the graphic controller 401 to the plane memory 403 through the DRAM controller 402. The plane memory 403 is composed of four sides and has 16 numbers from 0 to 15.
Area commands of various types can be set.

The 4-bit area command stored in the plane memory 403 is read in synchronism with the output of the image data, and is subjected to the color conversion & editing process in the palette, as shown in FIG.
Image data processing system, ENL conversion circuit 15, matrix conversion circuit 16, selector 17, undercolor removal circuit 21,
Further, it is used for switching parameters such as the filter 25, the multiplier 26, the TRC circuit 27, and the screen generation unit 28 via the area decoder 24. When this area command is read out from the plane memory 403 and used for color conversion & palette 413 editing processing, parameter switching in the image data processing system, etc., density conversion from 100 spi to 400 spi is necessary. The processing is performed by the density conversion area generation circuit 405. In the density conversion area generation circuit 405, 3 × 3 blocks are formed by using the FIFOs 409a and 409b, and data interpolation is performed from the pattern so that a boundary of a closed loop curve or an editing area does not become jagged, and 100 spi to 400 spi The density conversion to The delay circuits 411a, 411b, 1MFIFO 412 and the like are for adjusting the timing between the area command and the image data.

[0061]

As described above, according to the present invention,
Since the area identification signal of the second and subsequent scans is controlled by the area identification signal of the first scan, it is possible to eliminate the variation of the area identification signal in each scan and prevent the color change of black characters and lines. Further, since the area identification signal obtained by the first scan is stored in the memory in 1 bit and further in the memory in units of 2 blocks, the memory capacity can be reduced.

[Brief description of drawings]

FIG. 1 is a diagram showing an embodiment of an area identification signal processing circuit of a color image processing apparatus of the present invention.

FIG. 2 is a diagram showing a configuration example of an area identification circuit applied to the present invention.

FIG. 3 is a diagram showing a modified example of an image area identification circuit.

FIG. 4 is a diagram for explaining the distribution of color characters / halftone images.

FIG. 5 is a diagram for explaining an example of a distribution state of character areas.

FIG. 6 is a diagram for explaining parameter optimization conditions.

FIG. 7 is a diagram illustrating a configuration example of a signal processing system of the image processing apparatus.

FIG. 8 is a diagram illustrating a configuration example of a conventional color image processing device and a configuration example of an image area identification circuit.

FIG. 9 is a diagram showing a configuration example of a hue detection circuit.

[Explanation of symbols]

1 ... Region identification circuit, 2, 7 ... Decoder, 3 ... S / P converter, 4 ... Memory, 5 ... Address generation circuit, 6 ... P /
S converter, 8 ... selector

─────────────────────────────────────────────────── ───

[Procedure amendment]

[Submission date] November 17, 1992

[Procedure Amendment 1]

[Document name to be amended] Statement

[Name of item to be corrected] Brief description of the drawing

[Correction method] Change

[Correction content]

[Brief description of drawings]

FIG. 1 is a diagram showing an embodiment of an area identification signal processing circuit of a color image processing apparatus of the present invention.

FIG. 2 is a diagram showing a configuration example of an area identification circuit applied to the present invention.

FIG. 3 is a diagram showing a modified example of an image area identification circuit.

FIG. 4 is a diagram for explaining the distribution of color characters / halftone images.

FIG. 5 is a diagram for explaining an example of a distribution state of character areas.

FIG. 6 is a diagram for explaining parameter optimization conditions.

FIG. 7A is a diagram showing a configuration example of a signal processing system of the image processing apparatus.

FIG. 7B is a diagram showing a configuration example of a signal processing system of the image processing apparatus.

FIG. 8 is a diagram illustrating a configuration example of a conventional color image processing device and a configuration example of an image area identification circuit.

FIG. 9 is a diagram showing a configuration example of a hue detection circuit.

[Explanation of Codes] 1 ... Region identification circuit, 2, 7 ... Decoder, 3 ... S / P converter, 4 ... Memory, 5 ... Address generation circuit, 6 ... P /
S converter, 8 ... selector

[Procedure Amendment 2]

[Document name to be corrected] Drawing

[Correction target item name] All drawings

[Correction method] Change

[Correction content]

[Figure 1]

[Figure 5]

[Figure 6]

[Fig. 2]

[Figure 3]

[Figure 4]

[Figure 7a]

[Fig. 7B]

[Figure 8]

[Figure 9]

─────────────────────────────────────────────────── ─── Continuation of the front page (51) Int.Cl. ⁵ Identification code Office reference number FI technical display location H04N 1/46 9068-5C

Claims (5)

[Claims] 1. A color image processing apparatus that performs character / halftone area identification by dividing a plurality of pixels into blocks, and switches a parameter according to the area identification signal to perform a color image forming process. An area identification signal processing circuit of a color image processing apparatus, which is stored in a memory and used for the second and subsequent scans. 2. The area identification signal processing circuit of the color image processing apparatus according to claim 1, wherein the area identification signal of the second and subsequent scans is judged by collating with the area identification signal stored in the memory. 3. An area identification signal processing circuit for a color image processing apparatus according to claim 1, wherein a black character / other 1-bit area identification signal is stored in a memory. 4. The area identification signal processing circuit of a color image processing apparatus according to claim 3, wherein the area identification signal is ORed and stored in units of two blocks. 5. The area identification signal processing circuit of the color image processing apparatus according to claim 3, wherein a logical product of the area identification signals is obtained and stored in units of two blocks.