JP2012165245A - Image processing apparatus, image forming apparatus and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an image processing apparatus, image forming apparatus and program which reduce the loss of image quality caused by the processing for suppressing the white spots resulting from misregistration for an image where a plurality of colors are mixed.SOLUTION: A mixed color image 30C obtained by binarizing a mixed color image 30A is converted into a mixed color image 30D by multivaluing the pixels to be multivalued so that the density thereof exceeds a predetermined threshold when K pixels continue in the X direction for K pixels to be multivalued, otherwise multivaluing the pixels to be multivalued so that the density thereof is less than the predetermined threshold.

Description

  The present invention relates to an image processing apparatus, an image forming apparatus, and a program.

  Japanese Patent Application Laid-Open No. 2004-133830 discloses an input unit that inputs image data expressed in a plurality of colors including black, a black region detection unit that detects a black region in the image data, and a black color according to the black density in the black region. Color material amount determining means for determining the amount of color material other than black to be output to the area, edge part detecting means for detecting the edge part of the black area, and color other than black in an amount corresponding to the color around the edge part In addition to outputting the material in addition to the edge portion, for the black region other than the edge portion, the black color material in an amount corresponding to the black density in the black region is output, and the color material other than black is output. An image processing apparatus is disclosed that includes output means for outputting the amount determined by the color material amount determination means regardless of the content of the image data.

  Patent Document 2 discloses an image processing method in an image forming apparatus that forms a color image using a plurality of basic colors, the first step of acquiring color data of an adjacent region of an object included in the image, A second step of selecting either trapping or overprinting based on the acquired color data as processing to be performed on the object in order to reduce unnaturalness in the vicinity of the object boundary, and selection in the second step A third step of executing the processed processing is disclosed.

Japanese Patent No. 3852234 JP 2007-245657 A

  An object of the present invention is to perform processing for suppressing white spots caused by misregistration on an image in which a plurality of primary colors are mixed as compared with the case where the conversion unit and the replacement unit of the present invention are not provided. An object is to provide an image processing apparatus, an image forming apparatus, and a program for reducing the deterioration in image quality that occurs.

  In order to achieve the above-described object, the image processing apparatus according to claim 1, for a binarized image in which a mixed color image in which a plurality of primary colors are mixed is represented in binary, for a multi-value quantization target pixel of a specific primary color If the pixel of the specific primary color is continuous in a predetermined direction, the multi-value quantization target pixel is multi-valued so that the density of the multi-value quantization target pixel is equal to or higher than a predetermined threshold value. When the pixel of the specific primary color is not continuous in the direction with respect to the multi-value quantization target pixel, the multi-value quantization target pixel is multi-valued so that the density of the multi-value quantization target pixel is less than the threshold value. Conversion means for converting the binarized image into a multi-valued image by converting to a pixel value of the specific primary color having a density equal to or higher than the threshold in the multi-valued image obtained by conversion by the conversion means Is different from the target pixel in a predetermined region including the target pixel If it contains color pixels were constructed, including a replacement means for replacing the pixel colors of each pixel are mixed contained the target pixel to the area, the.

  The image processing apparatus according to claim 2, further comprising: binarizing means for binarizing the multi-valued image obtained by replacing the target pixel by the replacing means in the invention according to claim 1. It may be included.

  The image processing apparatus according to claim 3, wherein, in the invention according to claim 1 or claim 2, the conversion unit applies the pixel of the specific primary color that continues in the direction from the multi-value quantization target pixel. A weight value giving means for giving different weight values to each other, and a total value obtained by adding the weight values given by the weight value giving means as a value corresponding to the density of the multi-value quantization target pixel By applying this, the binarized image may be converted into the multi-valued image.

  The image processing apparatus according to claim 4, wherein the weight value assigning unit is further continued in a direction intersecting the direction starting from the multi-value quantization target pixel. A weight value different from each other is given to a pixel of a specific primary color, and the conversion means adds a weight value given to pixels continuous in the direction by the weight value giving means, and a total value obtained by adding The one that satisfies a predetermined condition among the total values obtained by adding the weight values assigned to the pixels of the specific primary color that are continuous in the intersecting direction by the weight value assigning means. The binarized image may be converted into the multi-valued image by applying as a value corresponding to the density of the pixel to be binarized.

  The image processing apparatus according to claim 5, wherein the weight value assigning unit further continues in a direction intersecting the direction starting from the multi-value quantization target pixel. A total value obtained by adding different weight values to pixels of a specific primary color and adding the weight values given to the pixels continuous in the direction by the weight value giving means and the weight value giving means The total value obtained by adding the weight values given to the pixels of the specific primary color that are continuous in the intersecting direction is designated as a value corresponding to the density of the multilevel pixel. Further comprising a designation unit, wherein the conversion unit applies the total value designated by the designation unit as a value corresponding to the density of the multi-valued pixel, thereby converting the binarized image into the multi-valued image. What to convert It may be.

  The image processing apparatus according to claim 6, further comprising changing means for changing the threshold value according to an input instruction in the invention according to any one of claims 3 to 5, wherein the weight value The weight value given to the pixel by the assigning unit may be a weight value predetermined for the threshold value changed by the changing unit.

  The image processing apparatus according to claim 7, wherein the conversion unit further includes image information indicating an image in which the mixed-color image is expressed in multiple values. Is input, the image indicated by the image information may be binarized, and an image obtained by binarization may be used as the binarized image.

  The image processing apparatus according to claim 8 may be the one in which the specific primary color is black in the invention according to any one of claims 1 to 7.

  The image forming apparatus according to claim 9, wherein the multi-valued image obtained by replacing the target pixel by the image processing apparatus according to any one of claims 1 to 8 and the replacement unit. And a forming means for forming an image obtained by binarizing the image on a recording medium.

  The program according to claim 10, wherein a computer is used in a predetermined direction with respect to a multilevel binarization target pixel of a specific primary color in a binary image in which a mixed color image in which a plurality of primary colors are mixed is represented by a binary value. When the pixels of the specific primary color are continuous, the density is multi-valued so that the density of the multi-value quantization target pixel is equal to or higher than a predetermined threshold, and the direction with respect to the multi-value quantization target pixel is If the pixel of the specific primary color is not continuous, the binarized image is converted into a multi-valued image by converting the multi-valued pixel so that the density of the multi-valued pixel is less than the threshold. A conversion unit that converts the image into a digitized image, and a multi-valued image obtained by conversion by the conversion unit, includes a pixel of interest among the pixels of the specific primary color having a density equal to or higher than the threshold value. The area contains pixels of the primary color different from the pixel of interest If, was assumed to function as a replacement means for replacing the pixel colors of each pixel are mixed contained the target pixel in the region.

  According to the first, ninth, and tenth aspects of the present invention, it occurs due to a registration error in an image in which a plurality of primary colors are mixed, as compared with the case where the conversion unit and the replacement unit of the present invention are not provided. There is an effect that the deterioration of the image quality caused by the processing for suppressing the white spot is reduced.

  According to the second aspect of the present invention, the storage capacity required in the process of processing is reduced compared to the case where the multi-valued image obtained by replacing the target pixel by the replacement unit is not binarized. Is obtained.

  According to the third aspect of the present invention, an effect is obtained that the binarized image is easily multi-valued as compared with the case where the weight value assigning means of the present invention is not provided.

  According to the fourth aspect of the present invention, compared to the case where the conversion means of the present invention is not provided, an effect that the binarized image is multi-valued with high accuracy can be obtained.

  According to the fifth aspect of the present invention, there is an effect that convenience in multi-value binarization is improved.

  According to the invention which concerns on Claim 6, compared with the case where it does not have the change means of this invention, the effect that the precision of the process for suppressing a white spot is adjusted easily is acquired.

  According to the seventh aspect of the present invention, when image information indicating an image showing a multi-valued color image is input, the image obtained by binarizing the image indicated by the image information is not multi-valued As compared with the above, an effect that the storage capacity required in the process of processing is reduced can be obtained.

  According to the eighth aspect of the invention, it is possible to obtain an effect that the deterioration of the image quality is further reduced as compared with the case where the specific primary color is not black.

1 is a block diagram illustrating an example of a configuration of an image forming apparatus according to an embodiment. FIG. 6 is a schematic diagram illustrating an example of an image that is not trapped and an example of an image that is trapped. It is a state transition diagram which shows an example of the flow of a process when trapping is performed using the conventional method with respect to the color-mixed image (the 1) shown with multiple values. It is a state transition diagram which shows an example of the flow of a process when trapping is performed using the conventional method with respect to the color-mixed image (the 2) shown with multiple values. It is a flowchart which shows the flow of a process of the trapping process program which concerns on embodiment. It is a flowchart which shows the flow of a process of the multi-value process routine program which concerns on embodiment. It is a schematic diagram which shows an example of a structure of the one-dimensional filter which concerns on embodiment. It is the state transition diagram (the 1) which shows the specific example of the trapping process which concerns on embodiment. It is a state transition diagram (the 2) which shows the example of the trapping process concerning an embodiment. It is a schematic diagram which shows the modification of the one-dimensional filter which concerns on embodiment.

  Hereinafter, an example of an embodiment for carrying out the present invention will be described in detail with reference to the drawings. In the following, a pixel (image or image region) representing a pixel value with three or more levels of discrete values is referred to as a “multi-valued pixel (image or image region)” or “multi-valued pixel (image). Or image area) ”.

  FIG. 1 is a block diagram illustrating an example of a configuration of an image forming apparatus 10 according to the present embodiment. As shown in the figure, the image forming apparatus 10 includes a CPU (central processing unit) 12 that controls the entire image forming apparatus 10 by executing processing of various programs, and a control that controls the operation of the entire image forming apparatus 10. ROM (Read Only Memory) 14 which is a storage medium in which a program, a trapping processing program to be described later, various data and the like are stored in advance, and a RAM (Random Access Memory) which is a storage medium used as a work area when executing various programs ) 16, a secondary storage unit (for example, hard disk) 18 that is a non-volatile storage medium that stores various types of information such as various programs and parameters even when the power switch (not shown) of the image forming apparatus 10 is turned off, and a display It consists of a touch panel display etc. with a transmissive touch panel superimposed on it. Various information is exchanged with the UI panel 20 that receives various information and instructions when the user touches the touch panel and the terminal device 22 (for example, a personal computer) through the communication means while being displayed on the display screen of the play. And an interface (I / F) 24 for this purpose.

  The image forming apparatus 10 includes an image forming unit 26 that forms an image indicated by the input image information on a recording sheet when image information indicating the image is input from the outside. In this embodiment, a printer that forms an image with toner on recording paper by the xerographic method is applied as the image forming unit 26. However, the present invention is not limited to this, and a thermal printer or an inkjet printer is applied. May be.

  The CPU 12, ROM 14, RAM 16, secondary storage unit 18, UI panel 20, I / F 24, and image forming unit 26 are connected to each other via a bus 28. Therefore, the CPU 12 accesses the ROM 14, RAM 16, and secondary storage unit 18, displays various information on the UI panel 20, grasps various information received by the UI panel 20, and performs various operations via the I / F 24. Information transmission / reception and operation control of the image forming unit 26 are performed.

  Next, the operation of the image forming apparatus 10 according to the present embodiment will be described.

  The image forming apparatus 10 receives image information indicating an image expressed in primary colors of black (K), yellow (Y), magenta (M), and cyan (C) from the outside (for example, the terminal device 22). Then, a toner image corresponding to the image information of each primary color is sequentially formed on the recording paper, and the formed toner image is fixed on the recording paper by heating and pressurizing, and the recording paper on which the toner image is fixed is externally provided. Discharge.

  By the way, in the image forming apparatus 10, the process of attaching the KYMC toner to the recording paper is performed independently for each primary color. Therefore, there may be a so-called “registration shift” in which the relative positional relationship of each primary color image is deviated by several pixels due to mechanical positional accuracy, unevenness in the conveyance speed of the recording paper, and the like. Thus, when a mixed color image in which a plurality of primary colors are mixed is formed on a recording sheet, for example, as shown in FIG. 2, a black character “A” formed on the recording sheet is formed with a K image area and a primary color other than K. A non-image forming area (hereinafter, referred to as “whiteout”) that does not partially exist at the boundary (outline of the K image area) with the peripheral image area (for example, the M image area) is generated. There is a case. In the example of FIG. 2, since the recording paper is white, a white outline is partially generated in the outline of the K image area. Therefore, in general, trapping is performed on the contour portion of the image, that is, the boundary region between the image regions of different primary colors, thereby suppressing white spots caused by misregistration.

  In the present embodiment, “trapping” refers to two image regions of different primary colors in which one image region has a predetermined density difference with respect to the other image region in a mixed-color image in which a plurality of primary colors are mixed. For example, it means that the region between the K image region and the M image region) is processed so that the different primary colors are mixed. Also, in the following, in order to avoid complications, a region sandwiched between the two image regions is set as a K image region, and a single pixel of K constituting the image region is set as a target pixel. An example in which trapping is performed by adding the pixel value of the pixel of interest to the pixel value of the K pixel and the pixel value of the M pixel (adding the pixel value of the M pixel to the K pixel) will be described. To do. Here, “adding” means not the addition of numerical values (gradation values) but the superposition of the layers of each color (for example, the superposition of the K layer and the M layer).

  Here, a conventional trapping method will be described with reference to FIG. FIG. 3 shows a process of trapping a mixed color image in which a K image area having a density of 50% and an M image area having a density of 50% are adjacent to each other and expressed in multiple values. An example is shown. As shown in FIG. 5A, the boundary area between the K image area and the M image area is determined using a 5 × 5 window indicating a window in which 5 pixels are arranged in each of the vertical and horizontal directions. Is done. That is, the pixel arranged in the center of the 5 × 5 window is set as a pixel of interest, and is moved in units of one pixel from left to right (in the X direction shown in the figure) in front view in FIG. The difference between the pixel value of the pixel of interest in the 5 × 5 window is greater than or equal to a predetermined value while moving in units of one line from the front view to the bottom (in the Y direction shown in FIG. 4A). By determining whether or not a pixel is included, a boundary region between the K image region and the M image region is determined. Note that the pixel value referred to here represents each color expressed by an 8-bit gradation value (for example, a CMYK gradation value).

  When the boundary area between the K image area and the M image area is determined by the 5 × 5 window, if the K pixel is the target pixel, the current pixel value of the target pixel is set to the 5 × 5 window. Is replaced with a pixel value obtained by adding the pixel values of pixels other than the pixel having a pixel value of 0. In the example shown in FIG. 5B, trapping is performed on pixels constituting an area of two pixels from the boundary with the M image area in the K image area. As a result, in the K image area, the area corresponding to two pixels from the boundary with the M image area is represented by a color in which K and M are mixed. The trapped mixed color image obtained by trapping the mixed color image expressed in multiple values in this way is binarized. FIG. 6C schematically shows an example of a mixed-color image obtained by binarizing a multi-valued mixed-color image after performing trapping without binarizing.

  On the other hand, when the trapping is performed after binarizing the multi-valued mixed color image, as an example, the mixed color image shown in FIG. 10A is binarized as shown in FIG. The current pixel value is replaced with a pixel value obtained by adding the pixel values of pixels other than the pixel having a pixel value of 0 among all the pixels included in the 5 × 5 window. FIG. 5E schematically shows an example of a mixed color image in the case where the multi-valued mixed color image is binarized and then trapped.

  FIG. 4 shows an example of a process of binarizing a multi-valued mixed color image that is configured by superimposing a 50% density K image area and a 50% density M image area. Has been. As shown in FIG. 9A, since the multi-valued K image region and the multi-valued M image region are overlapped, they are binarized without being trapped. Note that. FIG. 7C schematically shows an example of a color mixture image obtained by binarizing the color mixture image expressed in multiple values shown in FIG. In the examples shown in FIGS. 5A to 5C, the ratio of K in the binary image area to 50% of the density of the multi-value K image area is 50%. The ratio of M in the M image area indicated by the binary value to 50% of the density of the M image area indicated by is 50%. That is, there is no change in the ratio of K and the ratio of M with respect to the entire mixed color image before and after binarization.

  On the other hand, when the multi-valued mixed-color image shown in FIG. 6A is binarized, the mixed-color image includes, as an example, as shown in FIG. It is composed of an area composed of pixels having a pixel value of 0 and an image area composed of pixels having pixel values obtained by adding the K pixel value and the M pixel value. Then, when the conventional method is used for trapping the binary color mixture image shown in FIG. 4D, the M image area is superimposed on the K image area, and the entire mixed color image is displayed. The proportion of M will be 75%. Therefore, as an example, a mixed color image different from the mixed color image shown in FIG. 4C is obtained as shown in FIG.

  As described above, when the conventional trapping technique is used, trapping may be performed on pixels that should not be trapped.

  In view of this, in the image forming apparatus 10 according to the present embodiment, processing for avoiding trapping of pixels that should not be trapped is executed.

  Next, the operation of the image forming apparatus 10 when the trapping process is executed will be described with reference to FIG. FIG. 5 is a flowchart showing a process flow of the trapping process program executed by the CPU 12 when image information is input. This trapping process program is stored in a predetermined area of the ROM 14 in advance. . Further, here, in order to avoid complication, a mixed color image formed by superimposing the K layer indicating the K image region and the M layer indicating the M image region, which is a plurality of images arranged in a matrix A case where trapping is performed on a mixed color image formed of pixels will be described. Further, here, in order to avoid complications, the description will be made on the assumption that the M pixels constituting the M image area in the mixed-color image are pixels that satisfy a condition for generating white spots. Further, here, a condition that a pixel value corresponding to a predetermined density as a density at which white spots are visually recognized is applied as a condition for generating white spots.

  In step 100 of the figure, it is determined whether or not the image indicated by the input image information is a multi-valued image indicated by multi-values. If a negative determination is made, the process proceeds to step 104. If the determination is made, the process proceeds to step 102, the multi-valued image is converted into a binary image represented by binary values, and then the process proceeds to step 104. In step 104, a multi-value processing routine program is executed.

  Here, with reference to FIG. 6, the multi-value processing routine program according to the present embodiment will be described. FIG. 6 is a flowchart showing the flow of processing of the multi-value processing routine program. This program is also stored in advance in a predetermined area of the ROM 14.

  In step 200 of the figure, a primary color layer (here, M layer) other than a specific primary color (here, K) is simply multi-valued, and then the process proceeds to step 204, where the K layer is illustrated as an example. By superimposing the one-dimensional filter α shown in FIG. 7, the pixels included in the one-dimensional filter α are designated as determination target pixels for the presence or absence of continuity. Here, simple multi-level conversion means that when binary input data is “0”, the output is “0”, and when the input is “1,” the output is the maximum value of multi-level conversion. In other words, 8-bit multilevel conversion means conversion to 0-> 0, 1-> 255, and the one-dimensional filter α according to the present embodiment is shown in the horizontal direction ( The weight values for 5 pixels in the X direction are also symmetrically arranged in the horizontal direction with the center pixel position as the center. In the example shown in the figure, “0.65” is assigned as a weight value to the pixel position A in the center of the one-dimensional filter α, and each pixel position B adjacent to the pixel position A has a weight value. As a weight value, “0.1” is assigned to each pixel position C adjacent to each pixel position B. .05 "is added. In the processing of step 204 above, the pixel arranged at the pixel position A of the one-dimensional filter α is treated as a multi-valued pixel, and each pixel constituting the K layer. When the pixel position A of the one-dimensional filter α is placed in the pixel, the pixels included in the one-dimensional filter α are designated as the determination target pixels for the presence or absence of continuity. If none of the existing pixels has yet been multi-valued, the one-dimensional filter α is arranged so that the pixel at the upper left corner of the K layer is treated as the pixel of interest.

  In the next step 206, it is determined whether or not the pixel arranged at the pixel position A of the one-dimensional filter α, that is, the multi-value quantization target pixel is a K pixel (is not a pixel having a pixel value of 0). When the determination is made, the process proceeds to step 216, while when the determination is affirmative, the process proceeds to step 208, and the multivalue conversion target pixel arranged at the pixel position A in the one-dimensional filter α is set as a starting point. It is determined whether or not the pixels are continuous (not isolated). If the determination is affirmative, the process proceeds to step 210 and the one-dimensional filter α continues from the multi-value quantization target pixel as a starting point. After assigning a corresponding weight value to each of the pixels, the process proceeds to step 212, and multi-value conversion of the multi-value conversion target pixel is performed by calculating the pixel value of the multi-value conversion target pixel. Migrate to

  In the above step 212, for example, when there are two consecutive K pixels including the multi-valued pixel, the weight value “0.15” at the pixel position A is added to the weight value “0.15” at the pixel position B. "0.75" obtained by adding "" is replaced with the current pixel value of the multi-valued pixel as a pixel value corresponding to the density of the multi-valued pixel (hereinafter referred to as "density equivalent value"). Thus, the multi-valued pixel is multi-valued. Further, when there are three consecutive K pixels including the multi-valued pixel, the weight value “0.65” at the pixel position A, the weight value “0.1” at the pixel position B, and the pixel position C The pixel value to be multivalued is converted to a multivalued pixel by replacing “0.8” obtained by adding the weight value of “0.05” with the current pixel value of the pixel to be multivalued as a density equivalent value.

On the other hand, when a negative determination is made in step 208, the process proceeds to step 214, and the weight value “0.65” of the pixel position A is assigned to the multi-value quantization target pixel to thereby determine the multi-value quantization target pixel. After multi-value conversion is performed, the process proceeds to step 216. Here, as an example of the processing of step 214, the weight value “0.65” at the pixel position A is replaced with the current pixel value of the multi-value target pixel as a density equivalent value, thereby converting the multi-value target pixel into a multi-value. Applying the process to convert.
In the present multi-value process routine program, for convenience of explanation, an example in which the process of step 208 branches to step 210 or step 214 has been described. However, this is only an example, and the above step 208, step 210 and step 214 are not necessarily provided. In this case, instead of the process in step 212, the multi-value quantization target pixel is used by properly using the processes in steps 210 and 214 described above depending on the situation (for example, depending on whether or not the multi-value quantization target pixel is isolated). A process for converting the pixel value into multi-values may be applied.

  In step 216, it is determined whether or not all the pixels constituting the K layer have been multi-valued. If the determination is negative, the process proceeds to step 218, and the pixel position A of the one-dimensional filter α is next. After moving the one-dimensional filter α so that the planned pixels are arranged, the process proceeds to step 204. In the present multi-value processing routine program, if the processing in step 204 is executed in a state where none of the pixels constituting the K layer has yet been multi-valued, the upper left corner of the K layer is displayed. The one-dimensional filter α is arranged so that the pixel is treated as a multilevel pixel. Then, by the processing in step 218, the one-dimensional filter α is moved in the horizontal direction of the K layer (from left to right) so that each pixel constituting the K layer is treated as a multi-valued pixel once. It is moved in units of one pixel and moved in units of one line in the vertical direction (from top to bottom) of the K layer.

  On the other hand, if the determination in step 216 is affirmative, the multi-value quantization processing routine program is terminated, and the process proceeds to step 106 of the trapping processing program.

  In step 106, the target pixel is designated by superimposing the 5 × 5 window described above on a layer of a specific primary color (here, K layer). That is, after the pixel arranged at the center pixel position of the 5 × 5 window is designated as the target pixel, the process proceeds to step 108.

  In step 108, it is determined whether or not the pixel arranged at the center pixel position of the 5 × 5 window, that is, the target pixel is a K pixel (whether the pixel value is not 0) or not. If YES in step 116, the flow advances to step 116, whereas if positive determination is made, the flow advances to step 110.

In step 110, it is determined whether or not the density equivalent value of the target pixel is equal to or greater than a predetermined threshold value. If the determination is negative, the process proceeds to step 116. If the determination is affirmative, step 110 is performed. 112. The predetermined threshold value means a value corresponding to the number of continuous pixels, and a large threshold means that the continuity of the number of pixels is high. For example, in the present embodiment, as an example, the threshold value used to determine whether or not two pixels are continuous is “0.75”, and is used to determine whether or not three pixels are continuous. The threshold value is “0.8”, and the threshold value used to determine whether or not four pixels are continuous is “0.9”. These combinations of threshold values are merely examples. For example, the threshold used to determine whether or not two pixels are continuous is “0.71”, and the threshold used to determine whether or not three pixels are continuous is “0”. .8 "and the threshold value used to determine whether or not four pixels are continuous may be set to 0.99. In this case, for example, if the weight value of the pixel position A of the one-dimensional filter α is “0.6”, the weight value of the pixel position B is “0.11”, and the weight value of the pixel position C is “0.09”. good.
Further, the threshold combinations need not be limited to one as described above, and a plurality of combinations may be prepared in advance. In this case, for example, a plurality of threshold combinations that can be used in step 110 may be stored in the ROM 14 in advance, and these combinations may be specified in advance by a user instruction. Further, a weight value uniquely determined as a weight value used in the one-dimensional filter α is associated with this combination, and is stored in advance in the ROM 14 in a state associated with the threshold combination. Therefore, the CPU 12 also reads out the weight value corresponding to the threshold combination specified by the user specifying the threshold combination via the UI panel 20 from the ROM 14, and the read threshold value is the processing in step 110. The read weight value is used as the weight value of the one-dimensional filter α.

  In step 112, it is determined whether or not a boundary between the K pixel and the M pixel exists in the 5 × 5 window. If the determination is negative, the process proceeds to step 116, but the determination is affirmative. In this case, the process proceeds to step 114 and trapping is performed. Trapping here means that the current pixel value of the pixel of interest is a pixel other than the pixel having a pixel value of 0 among all the pixels included in the 5 × 5 window (because it is simple multi-valued, other than “0” is “ If there is only 255 ", it means that it is replaced.

  In step 116, it is determined whether or not the processing in step 108 has been executed for all the pixels constituting the K layer. If the determination is negative, the process proceeds to step 118, and a 5 × 5 window is displayed. After the 5 × 5 window is moved so that the next scheduled pixel is arranged at the center pixel position, the process proceeds to step 106. In this trapping processing program, if the process of step 106 is executed without executing the process of step 108 for any of the pixels constituting the K layer, the upper left corner of the K layer A 5 × 5 window is arranged so that these pixels are treated as the target pixel. Then, by the processing in step 118, the 5 × 5 window is moved in units of one pixel in the horizontal direction (from left to right) so that each pixel constituting the K layer is treated as a target pixel once. And move in units of one line in the vertical direction (from top to bottom).

  On the other hand, if the determination in step 116 is affirmative, this trapping processing program is terminated. The mixed color image obtained by trapping by the trapping process is binarized by the CPU 12 and stored in a predetermined storage area in the RAM 16.

  Next, a specific example of the trapping process according to the present embodiment will be described with reference to FIGS. Here, in order to avoid complications, the threshold used for determining whether or not two pixels are continuous is set to “0.71” as the threshold used in the processing of step 110 above, and three pixels are consecutive. The threshold used to determine whether or not the pixel is “0.8” and the threshold used to determine whether or not four pixels are continuous is 0.99, and the pixel position A of the one-dimensional filter α The case where the weight value of “0.6” is set, the weight value of the pixel position B is “0.11”, and the weight value of the pixel position C is “0.09” will be described. Here, a case where a value of “0.6” or less is used as a threshold value used in binarization after trapping (simple binarization) in order to avoid complications will be described.

  First, a specific example shown in FIG. 8 will be described. FIG. 8 shows a process in which the image forming apparatus 10 according to the present embodiment binarizes the multi-valued mixed-color image 30A indicated by the multi-valued image in which the K image area and the M image area are adjacent to each other after trapping. It is a schematic diagram which shows an example. As shown in FIG. 5A, the mixed color image 30A is a multi-valued image in which an image area 32A having a K density of 80% and an image area 34A having an M density of 80% are adjacent to each other. Here, when trapping is performed without binarizing the mixed-color image 30A shown in FIG. 5A using the conventional trapping technique, an image area of K as shown in FIG. In 32A, trapping is performed on the pixels constituting the area corresponding to two pixels from the boundary with the M image area 34A. As a result, the mixed-color image 30A is represented by a color in which K and M are mixed in a region corresponding to two pixels from the boundary with the M image region 34A in the K image region 32A. When the trapped mixed color image 30A obtained in this way is binarized, as shown in FIG. 5C as an example, a trapped region (K image region 30A) is displayed in the mixed color image 30A. A mixed color image 30B indicated by a binary value obtained by trapping an area corresponding to a boundary area between the image area 30B and the M image area 30B is obtained.

  On the other hand, when trapping is performed after binarizing the mixed-color image 30A, first, as an example, the mixed-color image 30A is binarized and converted into a mixed-color image 30C as shown in FIGS. In the example of FIG. 4D, the K image area 32A shown in FIG. 4A is converted into the K image area 32B, and the M image area 34A shown in FIG. 4A is converted into the M image area 34B. Has been. The K image area 32B is configured by converting 80% of a plurality of pixels constituting the area corresponding to the K image area 32A into K pixels using a predetermined screen pattern. Yes. The M image area 34B is configured by converting 80% of the plurality of pixels constituting the area corresponding to the M image area 34A into M pixels using a predetermined screen pattern. Has been. Here, 63 degrees is applied as the screen angle of the screen pattern used when constructing the K image area 32B, and 117 degrees is applied as the screen angle of the screen pattern used when constructing the M image area 34B. is doing.

  Next, paying attention to the K pixel of the mixed color image 30C as shown in FIG. 5E, the K pixels constituting the K image region 32B are multi-valued using the one-dimensional filter α. In addition to the K pixel, each of the M pixels constituting the M image area 34B is multi-valued by simple multi-value quantization. As a result, the mixed color image 30C shown in FIG. 11D is converted into a mixed color image 30D shown in multiple values as shown in FIG. In the example shown in FIG. 5F, a density equivalent value of “0.8” (density = 80%) is assigned to each pixel in which three K pixels are continuous in the horizontal direction, and K is set in the horizontal direction. Each pixel having two consecutive pixels is assigned a density equivalent value of “0.71” (density = 71%), and “0.6” for a single K pixel that is not continuous in the horizontal direction. Concentration equivalent value (density = 60%) is given. A pixel to which a density equivalent value of “0.71” and a pixel to which a density equivalent value of “0.6” is assigned are defined as isolated pixels, and a pixel to which a density equivalent value of “0.8” is assigned. Is a non-isolated pixel, and when an isolated pixel is arranged in the target pixel using a 5 × 5 window, the target pixel is determined regardless of the presence or absence of M pixels in the 5 × 5 window. If no non-isolated pixel is arranged in the target pixel and M pixels exist in the 5 × 5 window, trapping is performed on the target pixel. As a result, the mixed color image 30D is trapped only in the non-isolated pixels in the region corresponding to two pixels from the boundary with the M image region 34B in the K image region 32B as shown in FIG. The isolated pixel is represented by a color in which K and M are mixed (a color expressed by adding the pixel value of the K pixel and the pixel value of the M pixel).

  When the trapped mixed color image 30D obtained in this way is binarized, as shown in FIG. 5H as an example, the trapped pixel (non-isolated pixel) in the mixed color image 30D is displayed. A binary color mixed image 30E obtained by trapping the corresponding pixel is obtained. The binarization here is simple binarization. The simple binarization is binarization in which a value smaller than a certain threshold is “0” and a larger value is “1”. By using a value equal to or smaller than the weight value of the pixel position A of the one-dimensional filter α, this threshold value is expressed without missing isolated dots.

When “0.7” is applied as the threshold value used in the processing of step 110, a density equivalent value of “0.6” is assigned to the K image region 32B of the mixed color image 30D shown in FIG. 5 × 5 window with the isolated pixel as the isolated pixel, the pixel with the density equivalent value of “0.7” and the pixel with the density equivalent value of “0.8” as the non-isolated pixel When an isolated pixel is placed in the target pixel, trapping is not performed on the target pixel regardless of the presence or absence of M pixels in the 5 × 5 window, and a non-isolated pixel is placed in the target pixel. If there are M pixels in the 5 × 5 window, the pixel of interest is trapped. As a result, the mixed color image 30D is trapped only in the non-isolated pixels in the area corresponding to two pixels from the boundary with the M image area 34B in the K image area 32B. Represented in mixed colors. When the trapped mixed-color image 30D obtained in this way is simply binarized, as shown in FIG. 5 (i) as an example, the trapped pixels (non-isolated pixels) in the mixed-color image 30D. A mixed color image 30 </ b> F indicated by a binary value obtained by trapping the pixels corresponding to is obtained.
As described above, the conversion from the mixed color image 30A shown in FIG. 6A to the mixed color image 30C shown in FIG. 4D is realized by normal binarization (general screen processing). The conversion from the mixed color image 30D shown in (f) to the mixed color image 30F shown in (i) and the conversion from the mixed image 30D shown in (g) to the mixed color image 30E shown in (h). Is realized by simple binarization (binarization determined by whether or not a predetermined threshold value is exceeded in units of 1 × 1).

  Next, a specific example shown in FIG. 9 will be described. FIG. 9 shows a mixed color in which the image forming apparatus 10 according to the present embodiment is configured such that a K image area having a density of 50% and an M image area having a density of 50% are overlapped and expressed in multiple values. An example of the process of binarizing the image 40A is shown. As shown in FIG. 6A, the mixed color image 40A is binarized without being trapped because the multi-valued K image region and the multi-valued M image region are overlapped. The Note that. FIG. 2C shows an example of a color mixture image obtained by binarizing the color mixture image expressed in multiple values shown in FIG. In the examples shown in FIGS. 5A to 5C, the ratio of K in the binary image area to 50% of the density of the multi-value K image area is 50%. The ratio of M in the M image area indicated by the binary value to 50% of the density of the M image area indicated by is 50%. That is, there is no change in the ratio of K and the ratio of M with respect to the entire mixed color image before and after binarization.

  On the other hand, in the case of performing trapping after binarizing the mixed color image 40A shown in FIG. 10A, first, the mixed color image 40A shown in FIG. Convert. As an example, the mixed color image 40C includes an image area of only K, an image area of only M, an area composed of pixels having a pixel value of 0, and a pixel value of K and an M pixel value, as shown in FIG. It is composed of an image area composed of pixels (pixels obtained by superimposing K layer pixels and M layer pixels) having added pixel values.

  Next, as shown in FIG. 5E, paying attention to only the pixel of K, each pixel of K is multi-valued using a one-dimensional filter α. In addition to the K pixel, each M pixel constituting the M image area is simply multi-valued. As a result, the K-only pixel shown in FIG. 5E is converted into a multi-valued K-only pixel as shown in FIG. In the example shown in FIG. 5F, a density equivalent value of “0.71” (density = 71%) is assigned to each pixel in which two K pixels continue in the horizontal direction, and the pixels are continuously in the horizontal direction. A single equivalent K pixel is assigned a density equivalent value of “0.6” (density = 60%). Note that a density equivalent value of “0.8” is assigned to each pixel in which three K pixels are arranged in the horizontal direction, but in the example shown in FIG. Since there is no continuous pixel, a density equivalent value of “0.8” is not given to any of the K pixels shown in FIG.

  Then, after superimposing the multi-valued M image area on the K image area shown in FIG. 5F, the pixel to which the density equivalent value of “0.71” is assigned and “0.6”. A pixel to which a density equivalent value is assigned is an isolated pixel, a pixel to which a density equivalent value of “0.8” is assigned is a non-isolated pixel, and an isolated pixel is used as a target pixel using a 5 × 5 window. Is not trapped with respect to the target pixel regardless of the presence or absence of M pixels in the 5 × 5 window, a non-isolated pixel is disposed at the target pixel, and the 5 × 5 window When there are M pixels, trapping is performed on the target pixel. As a result, a mixed color image 40B shown in FIG. 10C is obtained as shown in FIG. That is, trapping is not performed because there are no non-isolated pixels in the pixels constituting the K image region shown in FIG.

  As described above in detail, according to the image forming apparatus 10 according to the present embodiment, trapping is performed on pixels that should be trapped, and trapping is not performed on pixels that should not be trapped. Therefore, a reduction in image quality of the image formed on the recording paper is reduced.

  In the above-described embodiment, an example of a case where multi-value conversion is performed using the one-dimensional filter α has been described. However, the present invention is not limited to this, and for example, the one-dimensional filter α is rotated by 90 degrees as illustrated in FIG. Multi-value conversion may be performed using the one-dimensional filter β. Which of the one-dimensional filters α and β is used may be determined according to the screen angle of the screen pattern of the input binarized data. For example, it is preferable to use the one-dimensional filter β when the screen angle θ is 0 degree or more and 45 degrees or less and when the screen angle θ is 135 degrees or more and less than 180 degrees. In this case, the one that satisfies the predetermined conditions of the density equivalent value given to the multilevel pixel by the one-dimensional filter α and the density equivalent value given to the multilevel pixel by the one-dimensional filter β is applied. By doing so, an example of performing multi-value conversion is given. Examples of the predetermined condition include a condition that a value corresponding to the density is larger than the other, and a condition that the value is equivalent to a density that is smaller than the other.

  In addition, the user designates in advance which one of the one-dimensional filters α and β is to be used via the UI panel 20 and applies the density-equivalent value given to the multilevel pixel by the designated one-dimensional filter. Pricing may be performed. Which one of the one-dimensional filters α and β is used may be determined according to the screen angle of the screen pattern used when binarizing the multi-valued image. For example, when the screen angle θ is larger than 45 degrees and smaller than 135 degrees, the one-dimensional filter α is used. When the screen angle θ is 0 degrees or more and 45 degrees or less and when the screen angle θ is 135 degrees or more and less than 180 degrees, it is one-dimensional. It is preferable to use the filter β.

  Moreover, the filter used for multi-value conversion is not limited to a one-dimensional filter, and a two-dimensional filter may be used. In this case, for example, a form example using an N × M (N and M; natural numbers of 2 or more) in which weight values are arranged in a matrix, or a form example using a combination of the one-dimensional filters α and β. It is done.

  In the above-described embodiment, the software form for realizing each step of the trapping process program by executing the trapping process program by the CPU 12 is exemplified. However, the present invention is not limited to this, and various circuits (for example, ASIC (Application Specific integrated circuits)) are connected to each other in a hardware form, or a combination of a software form and a hardware form.

  In the above embodiment, the trapping processing program has been described as an example in the case where the ROM 14 is stored in advance. However, the present invention is not limited to this, and these programs are stored in a CD-ROM or DVD. A form that is provided in a state of being stored in a recording medium that is read by a computer such as a ROM or a USB memory may be applied, or a form that is distributed via wired or wireless communication means may be applied.

10 Image forming apparatus 12 CPU
20 UI panel 26 Image forming unit

Claims (10)

In a binarized image in which a mixed color image in which a plurality of primary colors are mixed is represented by binary values, pixels of the specific primary color are continuous in a predetermined direction with respect to the multi-value quantization target pixel of the specific primary color The multi-value quantization target pixel is multi-valued so that the density of the multi-value quantization target pixel is equal to or higher than a predetermined threshold, and the pixel of the specific primary color is in the direction with respect to the multi-value quantization target pixel. Conversion means for converting the binarized image into a multilevel image by multileveling the multilevel pixel so that the density of the multilevel pixel is less than the threshold when not continuous When,
In the multi-valued image obtained by conversion by the conversion means, a primary color different from the target pixel in a predetermined region including the target pixel among the pixels of the specific primary color having a density equal to or higher than the threshold value. When a pixel is included, replacement means for replacing the target pixel with a pixel in which the primary colors of the pixels included in the region are mixed;
An image processing apparatus.   The image processing apparatus according to claim 1, further comprising binarization means for binarizing the multilevel image obtained by replacing the target pixel by the replacement means.   The converting means includes weight value assigning means for assigning different weight values to the specific primary color pixels continuous in the direction starting from the multi-value quantization target pixel, and the weight value assigning means provides the weight value assigning means. The binarized image is converted into the multilevel image by applying a total value obtained by adding the weighted values as a value corresponding to the density of the multilevel binarization pixel. 2. The image processing apparatus according to 2. The weight value assigning unit further assigns different weight values to the pixels of the specific primary color that are continuous in the direction intersecting the direction starting from the multi-value pixel.
The converting means includes a total value obtained by adding the weight values given to the pixels that are continuous in the direction by the weight value giving means and the specific value that is continuous in the intersecting direction by the weight value giving means. By applying the one that satisfies a predetermined condition among the total values obtained by adding the weight values assigned to the primary color pixels as a value corresponding to the density of the multilevel pixel The image processing apparatus according to claim 3, wherein a binarized image is converted into the multilevel image. The weight value assigning unit further assigns different weight values to the pixels of the specific primary color that are continuous in the direction intersecting the direction starting from the multi-value pixel.
The total value obtained by adding the weight values given to the pixels continuous in the direction by the weight value giving means and the pixels of the specific primary color that are continuous in the intersecting direction by the weight value giving means And a specifying means for specifying any one of the total values obtained by adding the weight values given in the above as a value corresponding to the density of the multi-valued pixel,
The conversion unit converts the binarized image into the multilevel image by applying the total value specified by the specifying unit as a value corresponding to the density of the multilevel pixel. The image processing apparatus described. A change unit for changing the threshold value according to the input instruction;
The weight value given to the pixel by the weight value assigning unit is a weight value set in advance for the threshold value changed by the changing unit. Image processing apparatus.   The conversion means further binarizes an image indicated by the image information when the image information indicating an image in which the mixed color image is expressed in multiple values is input, and converts the binary image to the binary value. The image processing apparatus according to any one of claims 1 to 6, wherein the image processing apparatus is a converted image.   The image processing apparatus according to claim 1, wherein the specific primary color is black. The image processing apparatus according to any one of claims 1 to 8,
Forming means for forming, on a recording medium, an image obtained by binarizing the multi-valued image obtained by replacing the target pixel by the replacing means;
An image forming apparatus including: Computer
In a binarized image in which a mixed color image in which a plurality of primary colors are mixed is represented by binary values, pixels of the specific primary color are continuous in a predetermined direction with respect to the multi-value quantization target pixel of the specific primary color The multi-value quantization target pixel is multi-valued so that the density of the multi-value quantization target pixel is equal to or higher than a predetermined threshold, and the pixels of the specific primary color are not continuous in the direction with respect to the multi-value quantization target pixel. A conversion unit that converts the binarized image into a multilevel image by multileveling the multilevel binarization pixel so that the density of the multilevel binarization pixel is less than the threshold; and the conversion In the multi-valued image obtained by conversion by the means, a primary color pixel different from the target pixel is present in a predetermined region including the target pixel among the specific primary color pixels having a density equal to or higher than the threshold value. If included, the pixel of interest is the primary color of each pixel included in the region A program for functioning as a replacement means for replacing with a mixed pixel.

Images