JP2010252184A - Image processing apparatus, image forming apparatus, image processing method, computer program and recording medium - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an image processing apparatus which can appropriately perform processing (trapping processing) for overlapping pixel data of a plurality of color components. <P>SOLUTION: A trapping processing unit 15 performs binarizing processing to input image data. Furthermore, the trapping processing unit 15 counts the number of pixels, having the same pixel value, continued in main scanning and sub scanning directions, respectively, for each block including each of pixels (pixel of interest) and peripheral pixels for the input image data converted into binary data. On the basis of a count value, the trapping processing unit 15 determines whether or not each block is included in a small-letter area and if it is determined that a block is included in the small-letter area, trapping overlap processing is not performed to the pixel of interest in the center of the block. If it is determined that each block is not included in the small-letter area. the trapping processing unit 15 performs trapping overlap processing on the pixel of interest in the center of the block. <P>COPYRIGHT: (C)2011,JPO&INPIT

Description

  The present invention relates to an image processing apparatus, an image forming apparatus, an image processing method, a computer program, and a recording medium that perform processing for superimposing pixel data of a plurality of color components.

  A trapping process or the like is performed to prevent image quality deterioration of an image formed on a paper medium by an image forming apparatus such as a copier or a printer. The trapping process is a process for overlapping pixel data of a plurality of color components, and is a process for preventing white spots at the time of misregistration. For example, an apparatus that analyzes image information included in a print job, determines a format (size) of an image element included in the image information, and performs a trapping process according to the determination result on the image information included in the print job Has been proposed (see Patent Document 1).

  For example, the apparatus of Patent Document 1 determines whether or not to perform a trapping process based on the number of character points included in a print job. Specifically, based on the number of points, when it is determined that the character included in the print job has a small size, the trapping process is not performed, and when it is determined that the character has a large size, trapping is performed. According to such an image forming apparatus, occurrence of color loss is suppressed even if plate misalignment occurs during printing of a color image.

JP 2006-137155 A

  However, since the apparatus of Patent Document 1 considers only the character size in determining whether or not to perform the trapping process, there is a problem in that it may erroneously determine whether or not to perform the trapping process. If the trapping process is mistakenly performed, the image quality may be deteriorated.

  The present invention has been made in view of such circumstances, and an object of the present invention is to provide an image processing apparatus, an image forming apparatus, an image processing method, and an image processing apparatus capable of more accurately determining whether or not to perform trapping processing. A computer program and a recording medium are provided.

  An image processing apparatus according to the present invention is an image processing apparatus that performs processing for superimposing pixels of a plurality of color components on edges extracted from input image data having a plurality of color components. A character detection unit that detects a character region, and whether or not the pixel of interest of the input image data is the edge and is included in the character region detected by the character detection unit. A process determination unit that determines whether or not to perform a process of superimposing pixels of color components, and a process of superimposing pixels of a plurality of color components on the target pixel when the process determination unit determines to perform the overlay process And an overlay processing unit for performing the above.

  An image processing apparatus according to the present invention intersects a binarization processing unit that converts the input image data into binary data based on a predetermined threshold, and binary data converted by the binarization processing unit. A counting unit that counts the number of pixels having the same pixel value continuous in each of the two directions, and the character detection unit detects the predetermined character region based on a counting result by the counting unit. It is characterized by being.

  An image processing apparatus according to the present invention is based on an average value calculation unit that calculates an average value of pixel values of a target pixel of the input image data and peripheral pixels of the target pixel, and an average value calculated by the average value calculation unit A threshold value calculation unit that calculates a threshold value, and the binarization processing unit converts the input image data into binary data based on the threshold value calculated by the threshold value calculation unit. To do.

  In the image processing apparatus according to the present invention, the counting unit is the same as the binary data converted by the binarization processing unit that is continuous in each of two intersecting directions and a direction obliquely intersecting the two directions. The number of pixels of the pixel value is counted.

  In the image processing apparatus according to the present invention, the character detection unit compares the count result of the count unit with a threshold set for each direction, and determines whether the character region is the predetermined character region based on the comparison result. It is made to do so.

  An image forming apparatus according to the present invention includes any one of the above-described image processing apparatuses and an image forming unit that forms an output image based on image data processed by the image processing apparatus.

  An image processing method according to the present invention is an image processing method for performing processing of superimposing pixels of a plurality of color components on edges extracted from input image data having a plurality of color components. A character detection step for detecting a character region; and a pixel of interest in the input image data based on whether the pixel of interest is included in the character region detected in the character detection step at the edge. A process determination step for determining whether or not to perform a process for superimposing pixels of color components, and a process for superimposing pixels of a plurality of color components on the target pixel when it is determined that the overlap process is performed in the process determination step And a superposition processing step.

  A computer program according to the present invention is a computer program for causing a computer to perform processing for superimposing pixels of a plurality of color components on edges extracted from input image data having a plurality of color components. A character detection step for detecting a predetermined character region included in the image, and based on whether the pixel of interest of the input image data is the edge and included in the character region detected in the character detection step, A process determination step for determining whether or not to perform a process for superimposing a pixel of a plurality of color components on a target pixel; and a determination process for performing a superimposition process in the process determination step; And a superimposing process step of performing a process of superimposing pixels.

  A recording medium according to the present invention stores the above-described computer program.

  In the present invention, a predetermined character area included in the input image data is detected. Further, based on whether or not each of the target pixels of the input image data is an edge extracted from the input image data and is included in the detected predetermined character area, each target pixel has a plurality of color component pixels. It is determined whether or not to perform a process of overlapping (trapping process). Then, a trapping process is performed according to the determination result. For example, the trapping process is not performed on edges included in a character region having a font size smaller than a predetermined size among edges extracted from input image data. This avoids degradation of image quality caused by performing trapping processing on a character region having a small font size. Further, by appropriately performing a trapping process in a necessary area, white spots that occur when misregistration occurs are prevented.

  In the present invention, the input image data is converted into binary data based on a predetermined threshold value, and the number of pixels having the same pixel value continuous in each of the two intersecting directions is counted for the obtained binary data. Based on the counting result, a predetermined character area included in the input image data is detected. Therefore, based on the number of consecutive pixels with the same pixel value, it is possible to accurately determine whether each pixel of interest belongs to a character area with a small font size, a thin line area, an area between characters, or the like. Is possible.

  In the present invention, the input image data is converted into binary data based on a threshold value based on an average value of pixel values of the target pixel of the input image data and the peripheral pixels of the target pixel. Then, in the binary data obtained by the conversion, a predetermined character area is detected based on the number of pixels having the same pixel value that is continuous in each of the two intersecting directions. Therefore, by suppressing the influence of the background color, it is possible to more accurately determine which region each pixel of interest belongs to.

  In the present invention, in the binary data converted from the input image data, the number of pixels having the same pixel value consecutive in each of the two intersecting directions and the direction obliquely intersecting the two directions is counted. Based on the counting result, a predetermined character area included in the input image data is detected. Therefore, it is possible to more accurately determine which region each pixel of interest belongs to based on the number of pixels having the same pixel value that is continuous in each of the two intersecting directions and the direction obliquely intersecting the two directions. Is possible.

  In the present invention, the predetermined number of pixels is determined based on the result of comparing the number of pixels having the same pixel value in each of the two intersecting directions and the direction obliquely intersecting the two directions with a threshold value set for each direction. It is determined whether it is a character area. Therefore, it is possible to more accurately determine which region each pixel of interest belongs to.

  The present invention can accurately determine whether each pixel of interest belongs to a character area having a small font size, a thin line area, a region between characters, or the like. Therefore, it is possible to accurately determine whether or not to perform the trapping process based on the determination result. That is, since it is determined whether or not the trapping process is performed in consideration of the line width of the character, the space between the characters, etc., it is possible to prevent an erroneous determination whether or not to perform the trapping process and to perform the trapping process with high accuracy. it can.

1 is a block diagram illustrating a configuration of a color image forming apparatus according to Embodiment 1. FIG. It is a block diagram which shows the structure of a trapping process part. It is a block diagram which shows the structure of an input line buffer part. It is a schematic diagram for demonstrating the binarization process which a binarization process part performs. It is a block diagram which shows the structure of a pixel count part. It is a schematic diagram for demonstrating the pixel count process which a pixel count part performs. It is a block diagram which shows the structure of a character detection part. It is a block diagram which shows the structure of a trapping determination process part. It is a figure which shows an example of input image data typically. It is a figure which shows an example of a differential filter typically. FIG. 11 is a diagram illustrating a part of the result of calculating the edge amount for the input image data in FIG. 9 using the differential filter in FIG. 10. It is a schematic diagram for demonstrating an increment direction area | region and a decrement direction area | region. FIG. 10 is a diagram illustrating a part of the result of executing the similar color direction determination on the input image data of FIG. 9. It is a schematic diagram for demonstrating the area | region referred when calculating a representative color. It is a schematic diagram for demonstrating the area | region referred when calculating a representative color. It is a figure which shows a part of result of having calculated the representative color of the attention side and the opposite side. It is a figure which shows a part of luminance value computed based on the representative color of an attention side and an other side, and the result of trap determination. It is a figure which shows a part of result of having performed the trapping superimposition process. It is a figure which shows a part of result of having performed the trapping superimposition process. It is a flowchart which shows the trapping process by a color image processing apparatus. It is a flowchart which shows the procedure of a trapping determination process. It is a flowchart which shows the procedure of a trapping determination process. It is a flowchart which shows the procedure of a trapping determination process. It is a block diagram which shows the structure of the trapping process part of Embodiment 2. It is a block diagram which shows the structure of a threshold value calculation part. It is a flowchart which shows the trapping process by a color image processing apparatus. It is a schematic diagram for demonstrating the pixel count process which a pixel count part performs. It is a block diagram which shows the structure of the character detection part of Embodiment 3. It is a block diagram which shows the structure of the character detection part of Embodiment 4. 1 is a block diagram illustrating a configuration of a digital color multi-function peripheral including an image processing apparatus according to the present invention.

  Hereinafter, an image processing apparatus, an image forming apparatus, an image processing method, a computer program, and a recording medium according to the present invention will be described in detail with reference to the drawings illustrating embodiments thereof.

(Embodiment 1)
The color image forming apparatus according to Embodiment 1 will be described below. FIG. 1 is a block diagram illustrating a configuration of a color image forming apparatus according to the first embodiment. The color image forming apparatus according to the first embodiment performs image processing on input image data (hereinafter referred to as input image data), and a color image is formed on a sheet such as recording paper based on the processed image data. Form. The input image data is created using application software such as image editing software on a computer (not shown). The created input image data is converted into a page description language by a printer driver, and transmitted from the computer to the color image forming apparatus via a network or the like.

  As shown in FIG. 1, the color image forming apparatus includes a color image processing apparatus 1 that processes input image data, and a color image output apparatus that forms an image based on the image data processed by the color image processing apparatus 1 (image formation). Means) 2 and the like. The color image output device 2 is, for example, a printer such as an electrophotographic system or an inkjet system that forms an image on a sheet such as a recording sheet or an OHP sheet. The color image output device 2 may be a display device such as a display.

  The color image processing apparatus 1 includes a raster data generation unit 11, a color correction unit 12, a black generation background removal unit 13, a selector 14, a trapping processing unit 15, an output gradation correction unit 16, a gradation reproduction processing unit 17, and the like. Yes.

  The raster data generation unit 11 analyzes the input page description language, and RGB (R: red, G: green, B: blue) or CMYK (C: cyan, M: magenta, Y: yellow, K: black) Generate raster data. When the RGB raster data is generated, the raster data generation unit 11 outputs the generated raster data to the color correction unit 12. On the other hand, when the raster data of CMYK is generated, the raster data generation unit 11 outputs the generated raster data to the selector 14.

  Further, the raster data generation unit 11 acquires color space information of the input image data, and outputs the acquired color space information to the selector 14. Further, the raster data generation unit 11 generates tag information indicating whether each pixel of the raster data is a character region, a vector graphics region, a photographic region, or any other one, and a black generation background removal unit 13 and the gradation reproduction processing unit 17.

  The color correction unit 12 performs a process of removing color turbidity based on the spectral characteristics of the CMY color material including unnecessary absorption components in order to realize faithful color reproduction. The color correction unit 12 outputs the three-color CMY signals after color correction to the black generation background removal unit 13.

  The black generation background removal unit 13 performs black generation processing for generating a black (K) signal from the color-corrected CMY signal, and processing for generating a new CMY signal by subtracting the K signal from the original CMY signal. As a result, the CMY three-color signal is converted into a CMYK four-color signal. The black generation background removal unit 13 outputs the generated CMYK signal to the selector 14.

  Note that the black generation background removal unit 13 generates a black signal by, for example, skeleton black processing. In this method, the input / output characteristic of the skeleton curve is y = f (x), the input data is C, M, Y, the output data is C ′, M ′, Y ′, K ′, UCR (Under Color When the removal rate is α (0 <α <1), the data output by the black generation and under color removal processing is K ′ = f {min (C, M, Y)}, C ′ = C−. αK ′, M ′ = M−αK ′, Y ′ = Y−αK ′.

  The selector 14 receives CMYK signals from the raster data generation unit 11 and the black generation background removal unit 13, and outputs one of the signals based on the color space information output from the raster data generation unit 11. When the color space information is RGB, the selector 14 outputs the CMYK signal input from the black generation background removal unit 13 to the trapping processing unit 15. When the color space information is CMYK, the selector 14 outputs the CMYK signal directly input from the raster data generation unit 11 to the trapping processing unit 15. Therefore, when the color space information of the input image data is CMYK, the trapping processing unit 15 receives a CMYK signal that has not been processed by the color correction unit 12 and the black generation background removal unit 13.

  The trapping processing unit 15 performs a trapping process for preventing white spots at the time of misregistration on the input raster data. The trapping processing unit 15 then outputs the processed CMYK signal to the output tone correction unit 16. The configuration and processing contents of the trapping processing unit 15 will be described later.

  The output tone correction unit 16 performs output tone correction processing based on the characteristics of the color image output device 2, and the tone reproduction processing unit 17 can finally separate the image into pixels and reproduce each tone. In this way, gradation reproduction processing (halftone generation) is performed. The tone reproduction processing unit 17 performs binarization or multi-value processing on the screen with an emphasis on tone reproducibility for an area determined to be a photograph based on the tag information from the raster data generation unit 11. .

  Next, the trapping processing unit 15 will be described. FIG. 2 is a block diagram showing a configuration of the trapping processing unit 15. The trapping processing unit 15 includes an input line buffer unit 21, a binarization processing unit 22, a pixel count unit 23, a character detection unit 24, a trapping determination processing unit 25, a trapping overlap processing unit 26, a threshold storage unit 27, and the like. Yes. In FIG. 2, only one input and output signal line is drawn, but it is assumed that there is actually a signal line for every four color components of CMYK. The raster data (CMYK signal) output from the selector 14 and input to the trapping processing unit 15 is input to the input line buffer unit 21 and the trapping overlap processing unit 26.

  FIG. 3 is a block diagram showing the configuration of the input line buffer unit 21. The input line buffer unit 21 includes a plurality of line buffers 212 for temporarily storing the input image data (CMYK signal) output from the selector 14 for each plane (color component) in units of lines. The input line buffer unit 21 includes a buffer write control unit 211 that writes input image data to the line buffer 212 and a buffer read control unit 213 that reads image data from the line buffer 212. By the plurality of line buffers 212, the binarization processing unit 22 and the trapping determination processing unit 25 in the subsequent stage can refer to data of a plurality of lines when performing mask processing or the like.

  The buffer read control unit 213 sequentially reads image data (line data) stored in a predetermined area of the plurality of line buffers 212 and outputs the image data to the subsequent binarization processing unit 22 and the trapping determination processing unit 25. Note that image data (line data) sequentially read from a predetermined area of the line buffer 212 includes a pixel of interest and peripheral pixels within a predetermined mask size in the binarization processing unit 22 and the trapping determination processing unit 25 in the subsequent stage. Acquired as a pixel data group to be processed.

  FIG. 4 is a schematic diagram for explaining the binarization processing performed by the binarization processing unit 22. The threshold value stored in the threshold value storage unit 27 and the line data output from the input line buffer unit 21 are input to the binarization processing unit 22. In the first embodiment, the line data output from the input line buffer unit 21 is described as being processed in units of blocks with a 5 × 5 mask size as one block. However, the mask size is not limited to this, and may be an optimum size as necessary. In the block shown in FIG. 4, the horizontal direction is the main scanning direction of the image data, and the vertical direction is the sub-scanning direction.

  The binarization processing unit 22 includes a comparator, and compares the threshold value input from the threshold value storage unit 27 with each pixel data (pixel value) included in the line data input from the input line buffer unit 21. Then, the binarization processing unit 22 converts the input line data into binary data based on the comparison result. In the example shown in FIG. 4, the threshold value is 84 h (84 in hexadecimal), and the pixel value equal to or greater than the threshold value is converted to 1 and the pixel value less than the threshold value is converted to 0.

  FIG. 5 is a block diagram showing the configuration of the pixel count unit 23, and FIG. 6 is a schematic diagram for explaining pixel count processing performed by the pixel count unit 23. Line data converted into binary data by the binarization processing unit 22 is input to the pixel count unit 23 in units of 5 × 5 pixel blocks. As shown in FIG. 6A, the pixel count unit 23 is the same continuous pixel in each of the main scanning direction and the sub-scanning direction of the 5 × 5 pixel block output from the binarization processing unit 22. The number of pixels of value (1 or 0) is counted. In the first embodiment, the number of pixels in which pixels having a pixel value of 1 continue is counted.

  As shown in FIG. 5, the pixel count unit 23 calculates four AND circuits 231 and 231 that calculate the logical product of adjacent pixel values for the five pixel values arranged in the main scanning direction and the sub-scanning direction, respectively. Have Further, the pixel count unit 23 includes three AND circuits 232 and 232 that calculate the logical product of adjacent output values for the output values from the AND circuits 231 and 231, respectively. Further, the pixel count unit 23 includes two AND circuits 233 and 233 that calculate a logical product of adjacent output values for the output values from the AND circuits 232 and 232, respectively.

  In addition, the pixel count unit 23 includes an AND circuit 234 that calculates a logical product of output values from the AND circuits 233 and 233, and an OR circuit 235 that calculates a logical sum of output values from the AND circuits 233 and 233, respectively. Have. In addition, the pixel count unit 23 includes an OR circuit 236 that calculates a logical sum of output values from the three AND circuits 232 and 232, an OR circuit 237 that calculates a logical sum of output values from the four AND circuits 231 and 231, It has an OR circuit 238 for calculating the logical sum of the five input pixel values. Then, the pixel count unit 23 is based on the output value A from the AND circuit 234 and the output values B, C, D, and E from the OR circuits 235, 236, 237, and 238, and is in the main scanning direction (or sub-scanning direction). 1 includes a count result output unit 239 that specifies and outputs the number of pixels (count value) having the same pixel value (here, 1).

  FIG. 6B shows a correspondence relationship between the input values A, B, C, D, and E input to the count result output unit 239 and the count value output from the count result output unit 239. As shown in FIG. 6B, for example, if the input values A, B, C, D, and E are all 1, the count result output unit 239 has five consecutive pixels with a pixel value of 1. The count value “5” indicating this is output. If the input value A is 0 and the input values B, C, D, and E are 1, the count result output unit 239 counts the count value “4” indicating that four pixels having the pixel value 1 are consecutive. 4 "is output.

  With such a configuration, the pixel counting unit 23 is a pixel in which a pixel having a pixel value of 1 is continuous in each of the main scanning direction and the sub-scanning direction in the 5 × 5 pixel block acquired from the binarization processing unit 22. Count the number (count value). The pixel count unit 23 outputs ten types of count values counted in each of the main scanning direction and the sub-scanning direction to the character detection unit 24.

  FIG. 7 is a block diagram showing a configuration of the character detection unit 24. The character detection unit 24 includes a first comparator 241, a second comparator 242, a lower case determination unit 243, a character detection threshold storage unit 244, and the like. Ten types of count values output from the pixel count unit 23 are input to the character detection unit 24, and five count values in the main scanning direction are input to the first comparator 241 and five count values in the sub-scanning direction are input. The count value is input to the second comparator 242.

  Further, the threshold values (for example, 5) stored in the character detection threshold storage unit 244 are input to the comparators 241 and 242. The threshold value stored in the character detection threshold storage unit 244 is that a central pixel (target pixel) of a 5 × 5 pixel block has a character size, a fine line region, a character and a character whose font size is smaller than a predetermined size. It is a threshold value for determining whether or not it is included in the area between and the like. Therefore, an appropriate value is set in consideration of the discrimination accuracy.

  The comparators 241 and 242 compare each count value input from the pixel count unit 23 with the threshold value input from the character detection threshold storage unit 244, and output the comparison result to the lowercase determination unit 243. For example, the comparators 241 and 242 output 1 if each count value is greater than or equal to a threshold value, and outputs 0 if less than the threshold value.

  The lowercase letter determination unit 243 determines whether or not the 5 × 5 pixel block belongs to the lowercase area based on the comparison results output from the comparators 241 and 242, respectively. For example, the lowercase determination unit 243 determines that this block belongs to the lowercase area when any of the 10 types of comparison results output from the comparators 241 and 242 is not 1. That is, when all of the 10 types of comparison results are 1, it is determined that this block does not belong to the lowercase area.

  In this case, in a 5 × 5 pixel block, if the number of pixels having a continuous pixel value of 1 in each of the main scanning direction and the sub-scanning direction is not equal to or greater than a predetermined value (threshold value), it is determined that the region is a lowercase area. In addition, when determined in this way, each block is included not only in the case where the font size is smaller than the predetermined size but also in the region between the thin lines and between the characters. It can also be determined whether or not. Note that a character area, a fine line area, and an area between characters that have a font size smaller than a predetermined size are collectively referred to as a lowercase area.

  When the lowercase determination unit 243 determines that the block to be processed belongs to the lowercase area, the lowercase determination unit 243 determines that the center pixel (target pixel) of this block belongs to the lowercase area, and “1” as the lowercase determination result for the target pixel. Is output to the trapping determination processing unit 25. If the lowercase determination unit 243 determines that the block to be processed does not belong to the lowercase area, the lowercase determination unit 243 determines that the target pixel of this block does not belong to the lowercase area, and sets “0” as the lowercase determination result for the target pixel. Output to the trapping determination processing unit 25. Note that the threshold value stored in the character detection threshold value storage unit 244 is not limited to this value, and may be appropriately changed according to the mask size of the block when the trapping processing unit 15 processes the input image data.

  FIG. 8 is a block diagram illustrating a configuration of the trapping determination processing unit 25. The trapping determination processing unit 25 determines whether or not to perform trapping and superimposition processing on each pixel of the input image data (hereinafter referred to as trap determination), and further, a color to be superimposed when performing the superimposition processing (hereinafter referred to as trap color). Say).

  FIG. 9 is a diagram schematically illustrating an example of input image data. In the following description, it is assumed that processing is performed on the input image data of 15 × 15 pixels shown in FIG. In FIG. 9, the horizontal direction is the main scanning direction of the image data, the vertical direction is the sub-scanning direction, the shaded pixels are cyan (C) pure colors, and the white pixels are magenta (M) pure colors. . Therefore, the pixel value (M, C) in the pixel having only magenta (M) (for example, the pixel in the main scanning direction 1 and the sub-scanning direction 1) is (255, 0). Further, the pixel value (M, C) in a pixel of only cyan (C) (for example, a pixel in the main scanning direction 8 and the sub-scanning direction 8) is (0, 255). Note that there are no other color components (Y and K), and in the following description, only cyan (C) and magenta (M) will be described.

  As shown in FIG. 8, the trapping determination processing unit 25 includes main-scanning and sub-scanning edge amount calculation units 251 and 252, main-scanning and sub-scanning side similar color direction determination units 253 and 254, trap determination / trap color. A calculation unit 255, a selector 256, and the like are provided.

  The trapping determination processing unit 25 receives the line data (input image data) output from the input line buffer unit 21 and the lowercase determination result output from the character detection unit 24. The line data is input to the selector 256, and the lowercase determination result is input to the selector 256 and the trap determination / trap color calculation unit 255.

  The selector 256 does not transfer the line data to the edge amount calculation units 251 and 252 when “1” is input as the lowercase determination result from the character detection unit 24. That is, the trapping determination processing unit 25 does not perform trap determination for the target pixel determined to be included in the lowercase area by the character detection unit 24. Further, when “1” is input as the lowercase determination result, the trap determination / trap color calculation unit 255 outputs “0”, which invalidates the trap determination, to the trapping overlap processing unit 26 as the trap determination result. That is, the trapping and superimposing process unit 26 described later does not perform the trapping and superimposing process on the target pixel determined to be included in the lowercase area by the character detection unit 24.

  On the other hand, when “0” is input as the lowercase determination result from the character detection unit 24, the selector 256 transfers the input line data to the main scanning side and sub-scanning side edge amount calculation units 251 and 252. In other words, the trapping determination processing unit 25 performs trap determination for the pixel of interest that is determined not to be included in the lowercase area by the character detection unit 24. Further, when “0” is input as the lowercase determination result, the trap determination / trap color calculation unit 255 performs trap determination and determination of the trap color, which will be described later, and traps the processing results (trap determination result, trap color). The data is output to the matching processing unit 26.

  As described above, when “1” is input as the lowercase determination result from the character detection unit 24, that is, when the target pixel to be processed belongs to the lowercase area, the trapping determination processing unit 25 uses the trap determination as the trap determination result. Is output to the trapping and superposition processing unit 26. Accordingly, by not performing the trapping and superimposing process on the target pixel determined to belong to the lowercase area, the area of the character whose font size is smaller than the predetermined size, the area of the fine line, and the area between the characters It is possible to avoid degradation of image quality caused by performing trapping processing on the target pixel included in. On the other hand, white pixels that occur when misregistration occurs by performing trapping overlay processing on the target pixel that is determined not to belong to the character region, and by appropriately performing trapping processing on the necessary region. Prevent omissions.

  The main scanning side and sub scanning side edge amount calculation units 251 and 252 use a differential filter for each plane (image data for each color component) of input image data input via the selector 256 in the main scanning direction. And the edge amount in each sub-scanning direction is calculated. FIG. 10 is a diagram schematically showing an example of a differential filter. (A) is a differential filter used in the main scanning direction, and (b) is a differential filter used in the sub-scanning direction. Although FIG. 10 shows a 5 × 5 mask size, the present invention is not limited to this. By using such a differential filter, an edge amount indicating a color difference between each pixel and the surrounding pixels in the main scanning direction and the sub-scanning direction is calculated for each color component.

  The trap width indicating how much the trapping is performed from the color boundary of the plate (hereinafter referred to as the trapping boundary) depends on the mask size. Therefore, the differential filter can select an optimal mask size as necessary. In general, when the trap width is increased, the color superposition region becomes large and the region is conspicuous as a false color, so that the image quality is deteriorated. On the other hand, when the trap width is small, white spots are conspicuous when the amount of misregistration is large. Therefore, the optimum trap width and mask size can be determined based on the balance between the amount of misregistration and the deterioration in image quality due to false colors.

  FIG. 11 is a diagram illustrating a part of the result of calculating the edge amount for the input image data of FIG. 9 using the differential filter of FIG. In FIG. 11, the numbers displayed on the left side of the pixels are the edge amounts calculated for cyan (C), with the upper side showing the edge amount in the main scanning direction and the lower side showing the edge amount in the sub-scanning direction. The number displayed on the right side in the pixel is the edge amount calculated for magenta (M), the upper side indicates the edge amount in the main scanning direction, and the lower side indicates the edge amount in the sub-scanning direction.

  For example, in the case of pixels in the main scanning direction 8 and the sub scanning direction 8, the edge amount of cyan (C) is “765” in both the main scanning direction and the sub scanning direction, and magenta (M) is “−765”. It becomes. Further, although omitted in FIG. 11, in the pixels far from the edge (for example, pixels in the main scanning direction 1 and the sub scanning direction 1), the edge amount is “0” on both the main scanning side and the sub scanning side. Become. Thus, the edge amount has a non-zero value near the boundary (edge) between cyan (C) and magenta (M) in the input image data.

  The main scanning side and sub-scanning side similar color direction determination units 253 and 254 determine similar color directions for the main scanning direction and the sub-scanning direction with respect to the edge amounts calculated by the edge amount calculation units 251 and 252, respectively. The similar color direction is a direction in which there is a pixel similar to the color of the target pixel. First, the similar color direction determination units 253 and 254 have at least two planes (C and M color components in the present embodiment) of CMYK, the absolute value of the edge amount is a threshold value (for example, 240) or more, and the edge amount It is determined whether or not there is a pixel having a positive or negative value. Note that such a pixel becomes an edge where white spots occur when a misregistration occurs.

  When such a pixel exists, the similar color direction determination units 253 and 254 determine that an edge exists for this pixel. When such a pixel does not exist, the similar color direction determination units 253 and 254 output “0” as the determination result of the similar color direction to the trap determination / trap color calculation unit 255. Note that the threshold value can be changed as appropriate depending on how far the edge is detected.

  In the case of a pixel in the main scanning direction 4 and the sub-scanning direction 6 in FIG. 11, the edge amounts in the main scanning direction are 255 for cyan (C) and −255 for magenta (M). Is determined to exist. When it is determined that there is an edge, the similar color direction determination units 253 and 254 are based on the pixel (target pixel) determined to have an edge and the average value of the pixel values of the pixels in the increment direction area and the decrement direction area. To calculate the color difference (col_diff).

  FIG. 12 is a schematic diagram for explaining the increment direction area and the decrement direction area, where (a) shows the case in the main scanning direction and (b) shows the case in the sub scanning direction. In the main scanning direction, the left side from the center pixel of interest P is a decrement direction area, and the right side is an increment direction area. In the case of the sub-scanning direction, the upper side from the central target pixel P is a decrement direction area, and the lower side is an increment direction area.

The pixel values of cyan (C), magenta (M), yellow (Y), and black (K) of the target pixel P are set to C ₁ , M ₁ , Y ₁ , and K ₁ , respectively, in the increment direction area or the decrement direction area. When the average value of the pixel values of C ₂ , C ₂ , M ₂ , Y ₂ , and K ₂ is used, the color difference (col_diff) between the pixel of interest and the increment direction area or the decrement direction area is calculated by the following formula 1. Is done.

col_diff = | C ₁ −C ₂ | + | M ₁ −M ₂ | + | Y ₁ −Y ₂ | + | K ₁ −K ₂ | (Formula 1)

  The similar color direction determination units 253 and 254 calculate the color difference (col_diff) between the increment direction area and the decrement direction area by Equation 1 above, and as a result, the direction with a small color difference is set as the similar color direction. For example, when the color difference calculated based on the target pixel P and the increment direction area is smaller than the color difference calculated based on the target pixel P and the decrement direction area, the increment direction is set as the similar color direction.

  When the increment direction is determined to be the similar color direction, the similar color direction determination units 253 and 254 output “1” as the determination result to the trap determination / trap color calculation unit 255. Also, when the similar color direction determination units 253 and 254 determine that the decrement direction is the similar color direction, the determination result “−1” is output to the trap determination / trap color calculation unit 255. If the similar color direction determination units 253 and 254 determine that no edge exists, the similar color direction is set to “none”, and “0” is output to the trap determination / trap color calculation unit 255 as a determination result.

  FIG. 13 is a diagram illustrating a part of the result of executing the similar color direction determination on the input image data in FIG. 9. The numerical value in each pixel indicates the determination result of the similar color direction, the upper numerical value indicates the main scanning direction, and the lower numerical value indicates the sub-scanning direction. For example, in the case of pixels in the main scanning direction 6 and the sub-scanning direction 7, the similar color directions in the main scanning direction and the sub-scanning direction are both −1, that is, the decrement direction, and the target pixel is similar in color to the pixel in the decrement direction. Will be.

  The trap determination / trap color calculation unit 255 performs trap determination and trap color determination based on the processing results of the edge amount calculation units 251 and 252 and the similar color direction determination units 253 and 254. First, the trap determination / trap color calculation unit 255 calculates a representative color for pixels within the mask size.

  14 and 15 are schematic diagrams for explaining regions to be referred to when calculating representative colors. FIG. 14 shows a case where a representative color is calculated based on an average value of pixel values of a plurality of pixels, and FIG. 15 shows a case where a representative color is calculated based on the pixel value of one pixel. In the following description, the method of calculating the representative color using the region shown in FIG. 14 is referred to as an area type, and the method of FIG. 15 is referred to as a point type.

  The trap determination / trap color calculation unit 255 calculates the representative color on the attention side and the opposite side for each color component with respect to the determination results by the similar color direction determination units 253 and 254. For example, in FIG. 13, in the pixels in the main scanning direction 6 and the sub scanning direction 7, the similar color directions in the main scanning direction and the sub scanning direction are both “−1”. When the representative color is calculated based on the area type, the representative color (representative color pixel value) on the attention side is the average value of the pixel values in the region (−1, −1) shown in FIG. It becomes. At this time, the representative color on the opposite side is an average value of the pixel values in the area (1, 1). Further, when calculating the representative color based on the point type, the representative color on the attention side is the pixel value of (−1, −1) shown in FIG. 15, and the representative color on the opposite side is (1, 1). It becomes a pixel value. In the following description, the representative color is calculated based on the area type.

  FIG. 16 is a diagram illustrating a part of the result of calculating the representative color on the attention side and the opposite side. The numerical value in each pixel indicates the pixel value of the calculated representative color. The number displayed on the right side of the pixel is magenta (M), and the left number is the calculated representative color for cyan (C). The pixel value is shown. The upper numerical value indicates the pixel value of the representative color on the attention side, and the lower numerical value indicates the pixel value of the representative color on the opposite side. For example, in the case of pixels in the main scanning direction 6 and the sub-scanning direction 7, the representative color on the target side is magenta (M), and the representative color on the opposite side is cyan (C).

  The trap determination / trap color calculation unit 255 calculates the luminance value L based on the following Expressions 2 to 5 after calculating the representative color on the attention side and the opposite side. (Crep, Mrep, Yrep, Krep) in Expression 2 to Expression 4 are pixel values of representative colors on the attention side and the opposite side, and these expressions are expressions for converting CMYK to RGB. Expression 5 is an expression for calculating the luminance value L using the converted RGB.

The trap determination / trap color calculation unit 255 compares the luminance values of the attention side and the opposite side calculated by the above formulas, and if the luminance value of the attention side is lower than the luminance value of the opposite side, the region having a bright luminance (color The trap determination is made effective in order to enlarge the thin area. By expanding the brighter region, it is possible to prevent the shape of the object from being deformed. When the trap determination is enabled, the trap determination / trap color calculation unit 255 determines the opposite side, that is, the representative color with the higher luminance as the trap color (C _trap , M _trap , Y _trap , K _trap ). To do. Further, when the luminance value on the attention side is higher than the luminance value on the opposite side, the trap determination / trap color calculation unit 255 invalidates the trap determination.

  FIG. 17 is a diagram illustrating a part of the luminance value calculated based on the representative color on the attention side and the opposite side and the result of the trap determination. The numerical value in each pixel indicates the calculated luminance value on the opposite side and the opposite side, and the trap determination result. As for the trap determination result, when “1” enables trap determination, “0” indicates trapping. This is a case where the determination is invalid. For example, in the case of pixels in the main scanning direction 6 and the sub-scanning direction 7, since the luminance value on the attention side is lower than the luminance value on the opposite side, the trap determination is valid and the trap determination is 1. The trap determination / trap color calculation unit 255 determines to perform superimposition processing on this pixel using the determined trap color, that is, cyan (C) as the trap color (see FIG. 16).

  The trapping determination processing unit 25 outputs the above processing result by the trap determination / trap color calculation unit 255 to the trapping superimposition processing unit 26. Note that input image data (CMYK signal) is input to the trapping and superimposing processing unit 26.

The trapping overlap processing unit 26 uses the trap determination result and the trap color (C _trap , M _trap , Y _trap , K _trap ) output from the trapping determination processing unit 25 to input image data (C _in , M _in , Trapping superposition processing is performed on Y _in , K _in ). When the trap determination result is 1, the trapping superimposing processing unit 26 sets the larger value of the input image data and the trap color as the pixel value of the output pixel for each color component. That is, when the output pixel is C _out , M _out , Y _out , K _out , C _out = MAX (C _in , C _trap ), M _out = MAX (M _in , M _trap ), Y _out = MAX ( Y _in , Y _trap ), K _out = MAX (K _in , K _trap ). MAX (A, B) indicates the larger value of A and B.

For black (K), the superimposed pixel values may be noticeable when they are superimposed, so that the same processing as other color components can be performed, or it can be selected not to perform the overlapping processing. It may be.
When the trap determination result is 0, the trapping and overlay processing unit 26 sets the pixel value of the input image data as the pixel value of the output pixel.

  18 and 19 are diagrams showing a part of the result of performing the trapping and superimposing process. FIG. 18 shows a case where the trap color is calculated with the area type as shown in FIG. 14, and FIG. The case where the trap color is calculated by the point type as shown in FIG.

When the trap color is calculated for the area type, as shown in FIG. 18, in the vicinity of the boundary between cyan (C) and magenta (M), an image in which the value of cyan (C) is trapped on the magenta (M) side Become. Further, when the trap color is calculated by the area type, the color becomes lighter as the distance from the boundary increases. This has an effect of making the overlapped portion (trapping portion) inconspicuous.
On the other hand, when the trap color is calculated for the point type, the color does not lighten as shown in FIG. For this reason, the overlapped portion is easily noticeable, but the degree of visual recognition of whitening at the time of plate displacement is low.

  Therefore, the trap determination / trap color calculation unit 255 determines the area depending on which problem is prioritized, such as image quality degradation due to false color when there is little misregistration or image quality degradation due to whiteout when the misregistration is large. The representative color may be calculated by switching to either the type or the point type.

  Next, the operation of the color image processing apparatus 1 according to the first embodiment will be described. FIG. 20 is a flowchart showing the trapping process performed by the color image processing apparatus 1. The following trapping process is a process performed by the trapping processing unit 15 of the color image processing apparatus 1.

  The trapping processing unit 15 of the color image processing apparatus 1 sequentially writes the input image data input from the selector 14 into the line buffer 212 of the input line buffer unit 21 (S1). The trapping processing unit 15 determines whether or not input image data (line data) has been written in a predetermined area of the line buffer 212 (S2). If it is determined that the writing has not been completed (S2: NO), the trapping processing unit 15 returns the process to step S1, and continues writing the input image data to the line buffer 212.

  When it is determined that the writing to the predetermined area of the line buffer 212 has been completed (S2: YES), the trapping processing unit 15 sequentially reads the line data written in each of the line buffers 212 (S3). The trapping processing unit 15 performs binarization processing on the line data read from the line buffer 212 (S4). Note that the trapping processing unit 15 uses line data read from a predetermined area of the line buffer 212 as a processing target pixel data group including a target pixel and peripheral pixels within a predetermined mask size (for example, a block of 5 × 5 pixels). ) Get as. Further, the trapping processing unit 15 converts the line data into binary data based on the threshold value stored in the threshold value storage unit 27.

  The trapping processing unit 15 counts the number of consecutive pixels having a pixel value of 1 in each of the main scanning direction and the sub-scanning direction for the line data converted into binary data (S5). The trapping processing unit 15 determines whether or not the central pixel (target pixel) of the block constituted by the line data belongs to the lowercase area based on the number of pixels counted in each of the main scanning direction and the sub-scanning direction. (S6).

  If the trapping processing unit 15 determines that the target pixel does not belong to the lowercase area (S6: NO), the trapping processing unit 15 performs a trapping determination process on the target pixel (S7). Details of the trapping determination process will be described later. The trapping processing unit 15 performs the trapping and superimposing process on the pixel of interest using the trap determination result in step S7 and the determined trap color (S8).

  Note that when the trapping processing unit 15 determines that the target pixel belongs to the lower case area (S6: YES), the process of steps S7 and S8 is skipped. That is, when the pixel of interest belongs to the lowercase area, the image quality degradation that occurs when the trapping process is performed on the lowercase area can be prevented by not performing the trapping process. In addition, when the pixel of interest does not belong to the lowercase area, whitening that occurs when misregistration can be prevented by performing trapping and superimposing processing.

  The trapping processing unit 15 determines whether or not processing has been performed for all the pixels included in the input image data (S9), and determines that processing has not been completed for all the pixels (S9: NO). Then, the process returns to step S1. When it is determined that the processing for all the pixels has been completed (S9: YES), the trapping processing unit 15 ends this processing.

  Next, the trapping determination process (step S7 in FIG. 20) in the trapping process described above will be described based on a flowchart. 21 to 23 are flowcharts showing the procedure of the trapping determination process. The following trapping determination process is a process performed by the trapping determination processing unit 25 of the trapping processing unit 15.

  The trapping processing unit 15 acquires a target pixel and peripheral pixels within a predetermined mask size as processing target pixels for each plane of the input image data (S11). The line data read from the predetermined area of the line buffer 212 is a pixel data group to be processed including the target pixel and peripheral pixels within a predetermined mask size. The trapping processing unit 15 calculates edge amounts in the main scanning direction and the sub-scanning direction for each pixel to be processed in each plane, using the differential filter shown in FIG. 10 (S12).

  Next, the trapping processing unit 15 selects an edge amount for one of the four planes in each of the main scanning direction and the sub-scanning direction (S13), and the absolute value of the selected edge amount is a threshold value (for example, 240) It is judged whether it is more than (S14). When it is determined that the absolute value of the selected edge amount is greater than or equal to the threshold (S14: YES), the trapping processing unit 15 determines whether or not the selected edge amount is a positive number (S15).

  When the trapping processing unit 15 determines that the selected edge amount is a positive number (S15: YES), the edge determination for the plane of the edge amount selected in step S13 is set to 1 (S16), and the selected edge amount is When it is determined that the number is negative (S15: NO), the edge determination for the plane of the edge amount selected in step S13 is set to -1 (S17). When it is determined that the absolute value of the selected edge amount is less than the threshold value (S14: NO), the trapping processing unit 15 sets the edge determination for the plane of the edge amount selected in step S13 to 0 (S18).

  The trapping processing unit 15 determines whether or not the determinations in steps S14 and S15 have been made for the edge amounts for all four planes (S19), and if not (S19: NO), the process proceeds to step S13. And the edge amount for the plane that has not yet been determined is selected (S13). The trapping processing unit 15 performs steps S14 to S18 for the selected edge amount, and performs steps S14 to S18 for the edge amounts for all planes.

  When the trapping processing unit 15 determines that the determinations in steps S14 and S15 have been made for the edge amounts for all the planes (S19: YES), 1 and −1 are included in the edge determination for each plane determined in steps S16 to S18. It is determined whether it is included (S20). If it is determined that 1 and −1 are not included in the edge determination for each plane (S20: NO), the trapping processing unit 15 sets the determination result of the similar color direction to 0 (S21), and the process proceeds to step S27. To do.

  If it is determined that 1 and −1 are included in the edge determination for each plane (S20: YES), that is, if there is an edge in the target pixel to be processed, the trapping processing unit 15 The color difference from the increment direction area is calculated (S22). Further, the trapping processing unit 15 calculates a color difference between the target pixel and the decrement direction area (S23). The trapping processing unit 15 compares the color difference with the increment direction area and the color difference with the decrement direction area, and determines whether or not the color difference with the increment direction area is smaller (S24).

  When the trapping processing unit 15 determines that the color difference from the increment direction area is smaller (S24: YES), the determination result of the similar color direction is set to 1 (S25), and the color difference from the increment direction area is larger. If it is determined (S24: NO), the determination result of the similar color direction is set to -1 (S26). It should be noted that for each of the main scanning direction and the sub-scanning direction of the input image data, the processes in steps S12 to S26 described above are performed by the main-scanning side edge amount calculation unit 251, the main-scanning side similar color direction determination unit 253, and the sub-scanning side. The edge amount calculation unit 252 and the sub-scanning side similar color direction determination unit 254 can perform in parallel.

  In step S21, S25, or S26, the trapping processing unit 15 determines whether the determination result of the similar color direction determined for the main scanning direction and the determination result of the similar color direction determined for the sub-scanning direction are both 0. (S27). When it is determined that the determination results of the similar color direction are both 0 (S27: YES), the trapping processing unit 15 proceeds to step S35.

  When it is determined that at least one of the determination results of the similar color direction is not 0 (S27: NO), the trapping processing unit 15 calculates the representative color on the attention side (S28). For example, in FIG. 13, the pixels in the main scanning direction 6 and the sub-scanning direction 7 are both “−1” (decrement direction region) in the similar color direction in the main scanning direction and the sub-scanning direction. When the representative color is calculated based on FIG. 14, the representative color on the attention side is an average value of the pixel values in the region indicated by (−1, −1) in FIG.

  Further, the trapping processing unit 15 calculates a representative color on the opposite side (S29). For example, in FIG. 13, in the pixels in the main scanning direction 6 and the sub scanning direction 7, the similar color directions in the main scanning direction and the sub scanning direction are both “−1”. When the representative color is calculated based on FIG. 14, the representative color on the opposite side is an average value of the pixel values in the region indicated by (1, 1) in FIG.

  The trapping processing unit 15 calculates the target side and opposite side representative colors and then calculates the target side luminance value and the opposite side luminance value based on Equations 2 to 5 (S30 and S31). The trapping processing unit 15 may reverse the processing order in steps S28 to S32, or may perform them simultaneously.

  The trapping processing unit 15 compares the luminance value on the attention side with the luminance value on the opposite side, and determines whether the luminance value on the attention side is lower than the luminance value on the opposite side (S32). When it is determined that the luminance value on the target side is lower than the luminance value on the opposite side (S32: YES), the trapping processing unit 15 sets the trap determination result to 1 (S33) and determines the trap color (S33). S34). Here, the trap color is the representative color of the opposite region.

  Note that when it is determined that the determination results of the similar color directions are both 0 (S27: YES), or when it is determined that the luminance value on the attention side is not lower than the luminance value on the opposite side (S32: NO), trapping is performed. The processing unit 15 invalidates the trap determination and sets the trap determination result to 0 (S35).

  The trapping processing unit 15 determines whether or not the trap determination result determined in step S33 or S35 is 1 (S36). If it is determined that the trap determination result is 1 (S36: YES), the trapping processing unit 15 generates an output pixel in which the trap color determined in step S34 is superimposed on the target pixel acquired in step S11 (S37). ),Output. When it is determined that the trap determination result is 0 (S36: NO), the trapping processing unit 15 sets the target pixel acquired in step S11 as an output pixel (S38) and outputs it.

  The trapping processing unit 15 determines whether or not processing has been performed on all the pixels included in the input image data (S39), and determines that processing has not been completed for all the pixels (S39: NO). The process returns to step S11. When it is determined that the processing for all the pixels has been completed (S39: YES), the trapping processing unit 15 ends this processing.

(Embodiment 2)
The color image forming apparatus according to the second embodiment will be described below. Note that the color image forming apparatus according to the second embodiment has the same configuration as the color image forming apparatus according to the first embodiment described above, and the same reference numerals are given to the same configurations, and description thereof is omitted.

  FIG. 24 is a block diagram illustrating a configuration of the trapping processing unit 15 according to the second embodiment. The trapping processing unit 15 of the second embodiment includes a threshold value calculation unit 28 instead of the threshold value storage unit 27 in the trapping processing unit 15 of the first embodiment shown in FIG. FIG. 25 is a block diagram illustrating a configuration of the threshold value calculation unit 28. The input line buffer unit 21 of the second embodiment sequentially reads out image data (line data) stored in a predetermined area of the plurality of line buffers 212, and performs a subsequent binarization processing unit 22 and a trapping determination processing unit 25, In addition, the data is output to the threshold calculation unit 28.

  The threshold calculation unit 28 includes a data storage unit 281 and an average value calculation unit 282. The data storage unit 281 stores the image data acquired from the input line buffer unit 21 in units of blocks of 5 × 5 pixels, for example. The average value calculation unit 282 calculates the average value of each pixel value in the block stored in the data storage unit 281. The threshold calculation unit 28 outputs the average value of the pixel values for each block calculated by the average value calculation unit 282 to the binarization processing unit 22 as a threshold. The threshold calculation unit 28 may calculate the threshold by performing a predetermined calculation on the calculated average without using the calculated average as the threshold.

  The threshold value calculated by the threshold value calculation unit 28 and the line data output from the input line buffer unit 21 are input to the binarization processing unit 22 of the second embodiment. The binarization processing unit 22 compares the threshold value input from the threshold value calculation unit 28 with each pixel data (pixel value) included in the line data input from the input line buffer unit 21, and based on the comparison result. The input line data is converted into binary data.

  As described above, in the second embodiment, the binarization processing unit 22 converts the input image data into binary data using the average value of pixel values in a predetermined area in the input image data as a threshold value. Therefore, since the binarization process in which the influence of the background color in the input image data is suppressed can be executed, whether or not each pixel of interest belongs to the lowercase area based on the binary data obtained by the binarization process. Can be accurately determined.

  Next, the operation of the color image processing apparatus 1 according to the second embodiment will be described. FIG. 26 is a flowchart showing the trapping process by the color image processing apparatus 1. The following trapping process is a process performed by the trapping processing unit 15 of the color image processing apparatus 1.

  The trapping processing unit 15 of the color image processing apparatus 1 sequentially writes the input image data input from the selector 14 into the line buffer 212 of the input line buffer unit 21 (S41). The trapping processing unit 15 determines whether or not input image data (line data) has been written in a predetermined area of the line buffer 212 (S42). If it is determined that the writing has not been completed (S42: NO), the trapping processing unit 15 returns the process to step S41 and continues writing the input image data to the line buffer 212.

  When it is determined that the writing to the predetermined area of the line buffer 212 has been completed (S42: YES), the trapping processing unit 15 sequentially reads the line data written to each of the line buffers 212 (S43). The trapping processing unit 15 calculates a threshold for use in the binarization process based on the line data read from the line buffer 212 (S44). The trapping processing unit 15 calculates an average value of pixel data (pixel value) included in the line data read from the line buffer 212 and sets it as a threshold value.

  The trapping processing unit 15 performs binarization processing on the line data read from the line buffer 212 based on the calculated threshold value (S45). The trapping processing unit 15 counts the number of pixels in which the pixel value is 1 in the main scanning direction and the sub-scanning direction with respect to the line data converted into binary data (S46). The trapping processing unit 15 determines whether or not the central pixel (target pixel) of the block constituted by the line data belongs to the lowercase area based on the number of pixels counted in each of the main scanning direction and the sub-scanning direction. (S47).

  If the trapping processing unit 15 determines that the target pixel does not belong to the lowercase area (S47: NO), the trapping processing unit 15 performs a trapping determination process on the target pixel (S48). The trapping determination process is the same as the process described with reference to FIGS. 21 to 23 in the first embodiment. The trapping processing unit 15 performs the trapping and superimposing process on the pixel of interest using the trap determination result in step S48 and the determined trap color (S49).

  If the trapping processing unit 15 determines that the target pixel belongs to the lower case area (S47: YES), it skips the processes of steps S48 and S49. That is, when the pixel of interest belongs to the lowercase area, the image quality degradation that occurs when the trapping process is performed on the lowercase area can be prevented by not performing the trapping process. In addition, when the pixel of interest does not belong to the lowercase area, whitening that occurs when misregistration can be prevented by performing trapping and superimposing processing.

  The trapping processing unit 15 determines whether or not processing has been performed for all the pixels included in the input image data (S50), and determines that processing has not been completed for all the pixels (S50: NO). The process returns to step S41. When it is determined that the processing for all the pixels has been completed (S50: YES), the trapping processing unit 15 ends this processing.

(Embodiment 3)
The color image forming apparatus according to the third embodiment will be described below. Note that the color image forming apparatus according to the third embodiment has the same configuration as the color image forming apparatus according to the first embodiment described above, and the same components are denoted by the same reference numerals and description thereof is omitted.

  FIG. 27 is a schematic diagram for explaining pixel count processing performed by the pixel count unit 23. The pixel count unit 23 according to the third embodiment has the same configuration as that shown in FIG. 5, and a 5 × 5 pixel block output from the binarization processing unit 22 as shown in FIG. In addition to the main scanning direction and the sub-scanning direction, the number of consecutive pixels having the same pixel value (1 or 0) is counted not only in the diagonally upward left direction and diagonally upward right direction. Note that the third embodiment also counts the number of pixels in which pixels having a pixel value of 1 continue.

  Therefore, the pixel counting unit 23 of the third embodiment is configured to perform the main scanning direction and the sub scanning direction, the left diagonally upward direction, and the diagonally right upward direction in the 5 × 5 pixel block acquired from the binarization processing unit 22, respectively. , The number of pixels (count value) in which pixels having a pixel value of 1 are consecutive is counted. Therefore, the pixel count unit 23 according to the third embodiment outputs 12 types of count values counted in each of the main scanning direction, the sub-scanning direction, the upper left diagonal direction, and the upper right diagonal direction to the character detection unit 24.

  FIG. 28 is a block diagram illustrating a configuration of the character detection unit 24 according to the third embodiment. The character detection unit 24 of the third embodiment includes a third comparator 245, a fourth comparator 246, and the like in addition to the configuration shown in FIG. In the character detection unit 24 according to the third embodiment, among the 12 types of count values output from the pixel count unit 23, five count values in the main scanning direction are input to the first comparator 241 and the sub-scanning direction is detected. Five count values are input to the second comparator 242. Further, the count value for the upper right diagonal direction is input to the third comparator 245, and the count value for the upper left diagonal direction is input to the fourth comparator 246.

  The comparators 241, 242, 245, and 246 are input with the threshold value (for example, 5) stored in the character detection threshold storage unit 244, and the comparators 241, 242, 245, and 246 are input. Each count value is compared with the input threshold value, and the comparison result is output to the lowercase letter determination unit 243. The comparators 241, 242, 245, and 246 output 1 if each count value is equal to or greater than a threshold value, and outputs 0 if it is less than the threshold value.

  The lowercase determination unit 243 determines whether or not the 5 × 5 pixel block belongs to the lowercase area based on the comparison results output from the comparators 241, 242, 245, and 246, respectively. For example, the lowercase determination unit 243 determines that this block belongs to the lowercase area when any of the 12 types of comparison results output from the comparators 241, 242, 245, and 246 is not 1.

  When the lowercase determination unit 243 determines that the block to be processed belongs to the lowercase area, the lowercase determination unit 243 determines that the center pixel (target pixel) of this block belongs to the lowercase area, and “1” as the lowercase determination result for the target pixel. Is output to the trapping determination processing unit 25. If the lowercase determination unit 243 determines that the block to be processed does not belong to the lowercase area, the lowercase determination unit 243 determines that the target pixel of this block does not belong to the lowercase area, and sets “0” as the lowercase determination result for the target pixel. Output to the trapping determination processing unit 25.

  As described above, in the third embodiment, the number of pixels in which the same pixel value continues in not only the main scanning direction and the sub-scanning direction but also the diagonally upper left direction and the diagonally upper right direction in the processing target block. calculate. Then, based on the number of pixels calculated for each direction, by determining whether each target pixel belongs to the lower case area, the number of pixels having the same pixel value that is continuous in the upper left diagonal direction and the upper right diagonal direction Can also be considered. Therefore, not only when each pixel of interest is included in a character area whose font size is smaller than a predetermined size, but also whether each pixel of interest is included in a thin line region, a region between characters and characters. Can be distinguished well.

  In the color image processing apparatus 1 according to the third embodiment, the trapping process performed by the trapping processing unit 15 is the same as the process described with reference to FIG. Note that the trapping processing unit 15 of the third embodiment performs the main scanning direction and the sub-scanning direction, the left diagonally upward direction, and the diagonally right upward direction with respect to the line data converted into binary data in step S5 in FIG. The number of pixels in which pixels having a pixel value of 1 continue in each direction is counted. Further, the trapping processing unit 15 according to the third embodiment, based on the number of pixels counted in each of the main scanning direction and the sub-scanning direction, the left diagonally upward direction, and the diagonally right upward direction in step S6 in FIG. It is determined whether or not the central pixel (target pixel) of the block constituted by the line data belongs to the lowercase area.

(Embodiment 4)
The color image forming apparatus according to Embodiment 4 will be described below. Note that the color image forming apparatus according to the fourth embodiment has the same configuration as the color image forming apparatus according to the third embodiment described above, and the same components are denoted by the same reference numerals and description thereof is omitted.

  FIG. 29 is a block diagram illustrating a configuration of the character detection unit 24 according to the fourth embodiment. The character detection unit 24 according to the fourth embodiment has a configuration similar to that shown in FIG. In the character detection unit 24 according to the fourth embodiment, the character detection threshold storage unit 244 has character detection thresholds individually set for the main scanning direction, the sub-scanning direction, the upper left diagonal direction, and the upper right diagonal direction. A threshold value is stored. In the character detection unit 24 of the fourth embodiment, the main scanning direction threshold value stored in the character detection threshold value storage unit 244 is input to the first comparator 241, and the sub-scanning direction threshold value is the second comparator. 242 is input to the third comparator 245, and the upper left threshold is input to the fourth comparator 246.

  Comparators 241, 242, 245, and 246 compare the count values input from pixel count unit 23 with the threshold values input from character detection threshold storage unit 244, respectively, and compare the comparison results with lowercase letter determination unit 243. Output to. The comparators 241, 242, 245, and 246 output 1 if each count value is equal to or greater than a threshold value, and outputs 0 if it is less than the threshold value.

  The lowercase determination unit 243 determines whether or not the 5 × 5 pixel block belongs to the lowercase area based on the comparison results output from the comparators 241, 242, 245, and 246, respectively. When the lowercase determination unit 243 determines that the block to be processed belongs to the lowercase area, the lowercase determination unit 243 determines that the center pixel (target pixel) of this block belongs to the lowercase area, and “1” as the lowercase determination result for the target pixel. Is output to the trapping determination processing unit 25. If the lowercase determination unit 243 determines that the block to be processed does not belong to the lowercase area, the lowercase determination unit 243 determines that the target pixel of this block does not belong to the lowercase area, and sets “0” as the lowercase determination result for the target pixel. Output to the trapping determination processing unit 25.

  As described above, in the fourth embodiment, the block to be processed is a lower-case area based on the number of pixels having the same pixel value in the main scanning direction, the sub-scanning direction, the upper left diagonal direction, and the upper right diagonal direction. Threshold values for determining whether or not are individually set. Therefore, it is possible to more accurately determine whether or not each pixel of interest is included in a character region, a fine line region, a region between characters and the like whose font size is smaller than a predetermined size.

  In the above-described first to fourth embodiments, the case where the image processing apparatus according to the present invention is provided in a color image forming apparatus such as a printer has been described. FIG. 30 is a block diagram showing a configuration of a digital color multi-function peripheral including the image processing apparatus according to the present invention.

  The color image processing apparatus 50 includes an A / D conversion unit 51, a shading correction unit 52, an input tone correction unit 53, a region separation processing unit 54, a color correction unit 55, a black generation background removal unit 56, a spatial filter processing unit 57, It comprises a trapping processing unit 58, an output tone correction unit 59, a tone reproduction processing unit 60, and the like. The digital color multifunction peripheral is configured by connecting an operation panel 50a, a color image input device 40, a color image output device 70, and a transmission device 71 to a color image processing device 50. The operation panel 50a is configured by a display unit including a setting button and a numeric keypad for setting an operation mode of the digital color multifunction peripheral, and a liquid crystal display.

  The color image input device 40 is composed of, for example, a scanner unit equipped with a CCD (Charge Coupled Device), and the reflected light image from the original is converted into an CCD (R: red, G: green, B: blue) analog signal as a CCD. And input to the color image processing apparatus 50. The analog signal read by the color image input device 40 is converted into an A / D conversion unit 51, a shading correction unit 52, an input tone correction unit 53, a region separation processing unit 54, and a color correction unit in the color image processing device 50. 55, the black generation background removal unit 56, the spatial filter processing unit 57, the trapping processing unit 58, the output gradation correction unit 59, and the gradation reproduction processing unit 60 are sent in this order, and are output to the color image output device 70 as a stream. .

  The A / D converter 51 converts RGB analog signals into digital signals. The shading correction unit 52 performs a process for removing various distortions generated in the illumination system, the imaging system, and the imaging system of the color image input device 40 on the digital RGB signal sent from the A / D conversion unit 51. . The input tone correction unit 53 adjusts the color balance of the RGB signal (RGB reflectance signal) input from the shading correction unit 52, and at the same time, an image employed in the color image processing apparatus 50 such as a density signal. A process for converting the signal into an easy-to-handle signal of the processing system is performed. The input tone correction unit 53 performs image quality adjustment processing such as removal of background density and contrast.

  The region separation processing unit 54 separates each pixel in the input image into one of a character region, a halftone dot region, and a photograph region from the RGB signal. The region separation processing unit 54 outputs, to the black generation background removal unit 56, the spatial filter processing unit 57, and the gradation reproduction processing unit 60, a region identification signal indicating which region the pixel belongs to based on the separation result. In addition, the input signal output from the input tone correction unit 53 is output to the subsequent color correction unit 55 as it is. The processing contents of the color correction unit 55, the black generation background removal unit 56, and the trapping processing unit 58 are the same as those in the first to fourth embodiments.

  The spatial filter processing unit 57 performs spatial filter processing using a digital filter on the image data of the CMYK signal input from the black generation background removal unit 56 based on the region identification signal and corrects the spatial frequency characteristics for output. A process for preventing image blur or graininess deterioration is performed. Similar to the spatial filter processing unit 57, the gradation reproduction processing unit 60 performs predetermined processing on the image data of the CMYK signal based on the region identification signal. For example, a region separated into characters by the region separation processing unit 54 has a high frequency enhancement amount in the sharp enhancement processing in the spatial filter processing by the spatial filter processing unit 57 in order to improve the reproducibility of black characters or color characters in particular. Increased. At the same time, the gradation reproduction processing unit 60 selects binarization or multi-value processing on a high-resolution screen suitable for high-frequency reproduction.

  Further, with respect to the region separated into halftone dots by the region separation processing unit 54, the spatial filter processing unit 57 performs low-pass filter processing for removing the input halftone component.

  The output tone correction unit 59 performs output tone correction processing based on the characteristics of the color image output device 70, and then the tone reproduction processing unit 60 finally separates the image into pixels and sets each tone. A gradation reproduction process (halftone generation) is performed so that the reproduction is possible. With respect to the region separated into photographs by the region separation processing unit 60, binarization or multi-value processing on the screen is performed with emphasis on gradation reproducibility.

  The transmission device 71 includes a modem or a network card. When sending a facsimile, the modem sends the data to the other party and secures a state where transmission is possible, and then stores the image data compressed in a predetermined format (image data read by the scanner) in the memory. The data is read from the data, and the necessary processing such as changing the compression format is performed, and the data is sequentially transmitted to the other party via the communication line.

  When a facsimile is received, image data transmitted from the other party is received while performing a communication procedure and input to the color image processing apparatus 50. The color image processing apparatus 50 compresses / decompresses the received image data. A decompression process is performed at a section (not shown). The decompressed image data is subjected to rotation processing and resolution conversion processing as necessary, subjected to output tone correction and tone reproduction processing, and is output from the color image output device 70.

  In addition, data communication is performed with a computer or other digital multi-function peripheral connected to the network via a network card or a LAN cable. Although the digital color multifunction peripheral has been described, it may be a monochrome multifunction peripheral.

  Furthermore, the present invention may record the method for performing the trapping process on a computer-readable recording medium in which a program to be executed by a computer is recorded. As a result, it is possible to provide a portable recording medium on which the program code (execution format program, intermediate code program, source program) for performing the processing is recorded.

  As the recording medium, a memory (not shown) such as a ROM itself, which is processed by a microcomputer, may be a program medium. Further, a program reading device may be provided as an external storage device (not shown), and the program medium may be read by inserting a recording medium therein.

  In any case, the stored program may be configured to be accessed and executed by the microprocessor, or in any case, the program code is read and the read program code is stored in the microcomputer. It may be downloaded to a program storage area (not shown) and the program may be executed. It is assumed that this download program is stored in the main device in advance.

  Here, the program medium is a recording medium configured to be separable from the main body, a tape system such as a magnetic tape or a cassette tape, a magnetic disk such as a flexible disk or a hard disk, a CD-ROM / MO / MD / DVD, or the like. Semiconductors such as optical discs, IC cards (including memory cards) / optical cards, etc., or mask ROM, EPROM (Erasable Programmable Read Only Memory), EEPROM (Electrically Erasable Programmable Read Only Memory), flash ROM, etc. It may be a medium that carries a fixed program code including a memory.

  In the present embodiment, since the system configuration is such that a communication network including the Internet can be connected, a medium that dynamically carries the program code so as to download the program code from the communication network may be used. When the program is downloaded from the communication network as described above, the download program may be stored in the main device in advance, or may be installed from another recording medium. The present invention can also be realized in the form of a computer data signal embedded in a carrier wave in which the program code is embodied by electronic transmission.

  The recording medium is read by a program reading device provided in a digital color image forming apparatus or a computer system, whereby the above-described image processing method is executed.

  The preferred embodiments of the present invention have been specifically described above, but each configuration, operation, and the like can be changed as appropriate, and are not limited to the above-described embodiments.

DESCRIPTION OF SYMBOLS 15 Trapping process part 21 Input line buffer part 22 Binarization process part 23 Pixel count part 24 Character detection part 25 Trapping determination process part 26 Trapping superimposition process part

Claims (9)

In an image processing apparatus that performs processing for superimposing pixels of a plurality of color components on edges extracted from input image data having a plurality of color components,
A character detection unit for detecting a predetermined character region included in the input image data;
Based on whether the target pixel of the input image data is the edge and is included in the character area detected by the character detection unit, a process of superimposing pixels of a plurality of color components on the target pixel is performed. A process determination unit for determining whether or not
An image processing apparatus comprising: an overlay processing unit that performs a process of superimposing pixels of a plurality of color components on the target pixel when the process determination unit determines to perform overlay processing. A binarization processing unit that converts the input image data into binary data based on a predetermined threshold;
A counting unit that counts the number of pixels having the same pixel value continuous in each of two intersecting directions with respect to the binary data converted by the binarization processing unit;
The image processing apparatus according to claim 1, wherein the character detection unit is configured to detect the predetermined character region based on a counting result obtained by the counting unit. An average value calculating unit that calculates an average value of pixel values of the target pixel of the input image data and the peripheral pixels of the target pixel;
A threshold value calculation unit that calculates a threshold value based on the average value calculated by the average value calculation unit,
The image processing apparatus according to claim 2, wherein the binarization processing unit converts the input image data into binary data based on the threshold value calculated by the threshold value calculation unit.   The counting unit counts, for the binary data converted by the binarization processing unit, the number of pixels having the same pixel value that is continuous in two intersecting directions and in a direction obliquely intersecting the two directions. The image processing apparatus according to claim 2, wherein the image processing apparatus is configured as described above.   The character detection unit compares the count result of the count unit with a threshold value set for each direction, and determines whether the character region is the predetermined character region based on the comparison result. The image processing apparatus according to any one of claims 2 to 4. An image processing apparatus according to any one of claims 1 to 5,
An image forming apparatus comprising: an image forming unit that forms an output image based on image data processed by the image processing apparatus. In an image processing method for performing processing of superimposing pixels of a plurality of color components on edges extracted from input image data having a plurality of color components,
A character detection step of detecting a predetermined character region included in the input image data;
Based on whether or not the target pixel of the input image data is the edge and is included in the character region detected in the character detection step, a process of superimposing pixels of a plurality of color components on the target pixel is performed. A process determination step for determining whether or not,
An image processing method comprising: a superposition processing step of performing a process of superposing pixels of a plurality of color components on the target pixel when it is determined that superposition processing is performed in the processing determination step. In a computer program for causing a computer to superimpose pixels of a plurality of color components on edges extracted from input image data having a plurality of color components,
On the computer,
A character detection step of detecting a predetermined character region included in the input image data;
Based on whether or not the target pixel of the input image data is the edge and is included in the character region detected in the character detection step, a process of superimposing pixels of a plurality of color components on the target pixel is performed. A process determination step for determining whether or not,
A computer program for executing, when it is determined in the processing determination step that superimposition processing is performed, a superposition processing step of performing processing for superimposing pixels of a plurality of color components on the target pixel.   A computer-readable recording medium on which the computer program according to claim 8 is recorded.

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