JP6186828B2 - Image processing apparatus, image processing apparatus control method, and image processing apparatus control program - Google Patents

Description

  The present invention relates to an image processing apparatus, an image processing apparatus control method, and an image processing apparatus control program. More specifically, the present invention relates to a trapping process for an image including first and second objects having different colors. The present invention relates to an image processing apparatus, a control method for the image processing apparatus, and a control program for the image processing apparatus.

  In general, an image forming apparatus superimposes toner (or ink) of four basic colors of C (cyan), M (magenta), Y (yellow), and K (black) on a sheet, thereby forming a color image. Print. The toner overlay position is shifted (printing) due to the expansion and contraction of the paper due to the pressure when the toner is applied on the paper, the positional deviation of the paper during conveyance, or the accuracy of the position adjustment device provided in the image forming apparatus. There is a possibility that white spots may occur due to deviation. The image forming apparatus performs a trapping process for correcting image data so that an area where one basic color toner is applied to an area where the other basic color toner is applied is expanded to an area where the other basic color toner is applied. Therefore, the occurrence of white spots is avoided.

  FIG. 27 is a diagram for explaining the principle of occurrence of white spots in an image. (A) is a diagram schematically showing an image IM101 in which white spots have not occurred, and (b) is a diagram schematically showing an image IM101 in which white spots have occurred. In the following drawings, the difference in image color is expressed by the difference in hatching.

  Referring to FIG. 27A, an image IM101 formed on a sheet includes a red background object and a black character object “A”. A magenta toner (or ink) TM and a cyan toner (or ink) TC are superimposed and applied to the background object area on the paper. Black toner (or ink) TK is applied to the character object area. In FIG. 27A, since the edges of the toners TC and TM are aligned with the edges of the toner TK, no white spots occur in the image IM101.

  Referring to FIG. 27B, in the image IM101, when the overlapping position of the toners TC and TM is shifted to the left in FIG. 27 from the original position, the edges of the toners TC and TM are two objects. Is shifted to the left in FIG. 27 from the original adjacent position BP. As a result, a region RG101 in which the white of the background of the paper is exposed without the toner being applied is generated between the toners TC and TM and the toner TK. The white spot means that the white background of the paper is exposed due to the deviation of the toner overlapping position.

  FIG. 28 is a diagram schematically illustrating an image on which the trapping process has been performed. (A) is a diagram showing an image when the toner overlapping position is aligned, and (b) is a diagram showing an image when the toner overlapping position is deviated.

  Referring to FIG. 28A, trapping processing is performed on an image IM102 formed on a sheet. That is, the edges of the toners TC and TM applied to the background object region on the paper are extended to the character side position from the original adjacent position BP of the two objects, and thereby the original adjacent position. An overlapping region OR where the toners TC and TM overlap with the toner TK is generated from the BP toward the character side. As a result, even when the overlapping positions of the toners TC and TM are shifted as indicated by the arrow AR1, the edges of the toners TC and TM are still located on the character side of the original adjacent position BP. The white background is not exposed and white spots do not occur.

  Techniques related to the trapping process are disclosed in Patent Documents 1 and 2 below, for example. In the following Patent Document 1, a boundary to be trapped is extracted from a color image to be printed, a trap area to be trapped is specified for each of two areas across the boundary, and a specified trap is specified. A technique for specifying a trap color for each of the regions is disclosed. In this technique, when any non-zero color component of the four color components of CMYK in one area is 0 in the other area, the value of 10% of the color component in one area is The color added to the color of the area is designated as the color of the trap area on the other area side.

  In Patent Document 2 below, a basic color used in a boundary portion between two objects included in an image is detected, and there is a common color that is a basic color commonly used in two objects in the boundary portion In addition, a technique for detecting the density of the common color and determining whether to perform trapping according to the density of the common color is disclosed.

JP 2002-165104 A JP 2007-184865 A

  FIG. 29 is a diagram schematically showing the color change of the edge of the object, which occurs in the conventional trapping process. (A) is a figure which shows image IM102 when the conventional trapping process is not performed, (b) is a figure which shows image IM102 when the conventional trapping process is performed.

  Referring to FIG. 29A, an image IM102 formed on a sheet includes, for example, a blue background object and a red character object “A”. When the conventional trapping process is performed, the image IM102 includes an overlap region OR at the edge of the object, as shown in FIG. For this reason, when no print misalignment occurs, there is a problem that the edge color of the object is likely to appear as a color changed from the original color (black in the case of the image IM102), and the image quality tends to deteriorate. For example, in the technique of Patent Document 1, since the trap color is determined by the combination of the colors of two regions straddling the boundary, depending on the trap color, the color of the edge of the object is likely to appear as a color changed from the original color.

  Regarding this problem, in the technique of Patent Document 2, when the density of the common color of the two objects in the boundary portion is equal to or higher than the threshold value, the trapping process is not performed, and thus the color change of the edge of the object is suppressed to some extent. Can do. However, even in the technique of Patent Document 2, trapping processing is performed when there is no common color between the two objects at the boundary portion or when the density of the common color is low, so that the color change of the edge of the object occurs. To do.

  There is a need for a trapping process that reduces the color change of the edge of an object when printout white spots are not noticeable and print deviation does not occur.

  SUMMARY An advantage of some aspects of the invention is that it provides an image processing device, a control method for the image processing device, and a control program for the image processing device that can suppress deterioration in image quality. That is.

An image processing apparatus according to one aspect of the present invention is an image processing apparatus that performs a trapping process on an image including first and second objects having different colors, and the first and second objects are adjacent to each other. And calculating a density value of the first object on the basis of the gradation value of each basic color constituting the first object existing in the boundary part, and a boundary part searching means for searching the boundary part which is an area including the adjacent position. Density calculating means for calculating the density value of the second object based on the gradation values of the respective basic colors constituting the second object existing at the boundary, and the density values of the first and second objects. Based on the correction target determining means for determining whether or not the boundary portion is to be corrected, and when the correction target determining means determines that the boundary portion is to be corrected, trapping is performed on at least a part of the boundary portion. And a trapping means for processing, correction target determination unit, when at least one of the density values of the first and second objects is equal to or less than the first threshold, no correction target boundary portion When the density values of the first and second objects are both greater than the first threshold value, it is determined that the boundary is a correction target, and the correction target determination unit determines that it is not a correction target. In this case, the trapping means does not perform the trapping process.
Preferably, in the image processing apparatus, when the correction target determining unit determines that the correction target is to be corrected, based on the density values of the first and second objects, the color of the first object existing at the boundary, and The apparatus further comprises extended color determining means for determining one of the colors of the second object existing at the boundary as an extended color and determining the other as an extended color, and the trapping means includes at least one basic component constituting the extended color. A trapping process for extending the color to the extended color area is performed.
An image processing apparatus according to another aspect of the present invention is an image processing apparatus that performs a trapping process on an image including first and second objects having different colors, and the first and second objects are adjacent to each other. And calculating a density value of the first object on the basis of the gradation value of each basic color constituting the first object existing in the boundary part, and a boundary part searching means for searching the boundary part which is an area including the adjacent position. Density calculating means for calculating the density value of the second object based on the gradation values of the respective basic colors constituting the second object existing at the boundary, and the density values of the first and second objects. Based on the correction target determining means for determining whether or not the boundary portion is to be corrected, and when the correction target determining means determines that the boundary portion is to be corrected, trapping is performed on at least a part of the boundary portion. A trapping unit for performing processing, and when the correction target determining unit determines that the correction target is not to be corrected, the trapping unit does not perform the trapping process, and the correction target determination unit determines that the correction target is to be corrected. Based on the density values of the first and second objects, one of the color of the first object existing at the boundary and the color of the second object existing at the boundary is determined as an extended color, and the other is covered. Extended color determining means for determining as an extended color is further provided, and the trapping means performs a trapping process for extending at least one basic color constituting the extended color into the extended color area, and is directed from the adjacent position toward the extended color. An extended area in which at least one basic color constituting the extended color and the extended color overlap with each other is determined. When it is determined that the correction target is determined by the extension area determination unit and the correction target determination unit, the gradation value of the first object existing at the boundary and the first value existing at the boundary are determined as the correction method of each basic color. And a correction method selection means for selecting one of a constant gradation correction and a stepped correction based on the gradation value of the second object. This is a correction method for adding to the gradation value of the entire extended area. Staircase correction is a correction method for adding a gradation value that decreases in a stepped manner to the gradation value of the extended area according to the distance from the adjacent position. .
Preferably, in the image processing apparatus, the correction method selection unit includes, for each basic color, a gradation value of the first object existing at the boundary portion and a gradation value of the second object existing at the boundary portion. When the smaller gradation value is equal to or smaller than the third threshold value, constant gradation correction is selected, and when the smaller gradation value exceeds the third threshold value, stepwise correction is selected.
Preferably, in the image processing apparatus, when a basic color having a gradation value smaller than the gradation value of the basic color forming the extended color exists among the basic colors forming the extended color, the trapping means The trapping process for the basic color is not performed.
Preferably, in the image processing apparatus, when the constant gradation correction is selected by the correction method selection unit, the trapping unit has a gradation corresponding to a value obtained by subtracting the gradation value of the extended color from the gradation value of the extended color. The value is added to the gradation value of the entire extended area.
Preferably, in the above image processing apparatus, when the staircase correction is selected by the correction method selection unit, the trapping unit has a value obtained by subtracting the gradation value of the extended color from the gradation value of the extended color for the basic color. Then, a gradation value corresponding to a value obtained by multiplying the second coefficient that decreases according to the distance from the adjacent position is added to the gradation value of the extension region.
Preferably, in the image processing apparatus, the second coefficient used when the basic color is black is smaller than the second coefficient used when the basic color is other than black.
An image processing apparatus according to still another aspect of the present invention is an image processing apparatus that performs a trapping process on an image including first and second objects having different colors, wherein the first and second objects are mutually connected. Boundary part searching means for searching for a boundary part that is an area including adjacent positions, and a density value of the first object based on a gradation value of each basic color constituting the first object existing in the boundary part Density calculation means for calculating and calculating the density value of the second object based on the gradation values of the respective basic colors constituting the second object existing at the boundary, and the density values of the first and second objects Based on the correction object determining means for determining whether or not the boundary part is to be corrected, and when the correction object determining means determines that the boundary is to be corrected, A trapping unit that performs a ping process, and when the correction target determination unit determines that the correction target is not a correction target, the trapping unit does not perform the trapping process, and the correction target determination unit determines that the correction target is a correction target. Based on the density values of the first and second objects, one of the color of the first object existing at the boundary and the color of the second object present at the boundary is determined as an extended color, and the other is Extended color determination means for determining as an extended color is further provided, and the trapping means performs a trapping process for extending at least one basic color constituting the extended color to the extended color area, and heads from the adjacent position to the extended color. An extension area provided in the direction, in which at least one basic color constituting the extension color and the extended color overlap. Further comprising an expansion area determining means for trapping means, depending on the amount of the gradation values of the basic colors other than black to be added to expand the area and reduce the tone value of black in the extended area.
Preferably, in the image processing apparatus, the extended color determining means determines the color of the object having the lower density value among the density values of the first and second objects as the extended color, and has the higher density value. The color of the object is determined as the extended color.
Preferably, in the image processing apparatus, an extended area provided in a direction from the adjacent position toward the extended color, wherein the extended area where at least one basic color constituting the extended color and the extended color overlap is determined. And an extended area determining means.

  Preferably, in the image processing apparatus, the density calculation unit multiplies the gradation value of each basic color constituting the first object existing at the boundary by a first coefficient determined for each basic color. A first density calculating means for calculating a result of adding all the multiplication values as a density value of the first object, a gradation value of each basic color constituting the second object existing in the boundary portion, Second density calculating means for multiplying the first coefficient determined for the basic color and calculating the result of adding all the multiplied values as the density value of the second object.

  Preferably, in the above image processing apparatus, the boundary search means sets the position where the amount of change in the gradation value of each basic color exceeds the second threshold as the adjacent position when the image is scanned in an arbitrary direction. Extract the boundary.

  In the image processing apparatus, preferably, the gradation value of each basic color constituting the first object existing in the boundary portion and the gradation value of each basic color constituting the second object existing in the boundary portion are determined. Color extraction means for extracting is further provided.

  Preferably, in the image processing apparatus, the color extraction unit includes an average value of gradation values of the basic colors constituting a region of a certain size in the first object existing at the boundary portion and a first value existing at the boundary portion. The average value of the gradation values of the basic colors constituting the area of a certain size in the two objects is extracted.

An image processing apparatus according to still another aspect of the present invention is an image processing apparatus that processes an image including first and second objects having different colors, and adjacent positions at which the first and second objects are adjacent to each other. A boundary portion searching means for extracting a boundary portion that is an area including the first object, and calculating a density value of the first object based on a gradation value of each basic color constituting the first object existing in the boundary portion; Density calculating means for calculating the density value of the second object based on the gradation values of the respective basic colors constituting the second object existing in the section, and based on the density values of the first and second objects, Extended color determining means for determining one of the color of the first object existing at the boundary and the color of the second object existing at the boundary as the extended color and determining the other as the extended color Extension region determining means for determining an extension region provided in a direction from the adjacent position toward the extended color, wherein at least one basic color constituting the extended color overlaps the extended color; As a correction method for each basic color, constant gradation correction and stepped correction are performed based on the gradation value of the first object existing in the boundary portion and the gradation value of the second object existing in the boundary portion. A correction method selecting means for selecting one of the methods, and a trapping means for performing a trapping process, and the basic colors constituting the extended color are more than the gradation values of the basic colors constituting the extended color. When a basic color having a small gradation value exists, the trapping means does not perform the trapping process for the basic color, and if the constant gradation correction is selected by the correction method selection means, the trapping means The means adds a gradation value corresponding to a value obtained by subtracting the gradation value of the extended color from the gradation value of the extended color to the gradation value of the entire extended area, and selects the staircase correction by the correction method selection means. In this case, the trapping means corresponds to a value obtained by multiplying the basic color by a value obtained by subtracting the gradation value of the extended color from the gradation value of the extended color and a coefficient that decreases according to the distance from the adjacent position. The gradation value is added to the gradation value of the extended area.

An image processing device control method according to still another aspect of the present invention is a control method for an image processing device that performs a trapping process on an image including first and second objects having different colors. A boundary portion searching step for searching for a boundary portion that is an area including adjacent positions where the second object is adjacent to each other, and a first based on the gradation value of each basic color constituting the first object existing in the boundary portion A density calculation step of calculating a density value of the second object, and calculating a density value of the second object based on a gradation value of each basic color constituting the second object existing at the boundary; Based on the density value of the second object, the correction target determination step for determining whether or not the boundary portion is to be corrected, and the correction target determination step determines that the correction target is determined. The case, and a trapping step for trapping processing at least a part of a boundary portion, in the correction target determination step, at least one is below a first threshold value of the density values of the first and second objects In this case, it is determined that the boundary portion is not to be corrected, and when both the density values of the first and second objects are larger than the first threshold, it is determined that the boundary portion is to be corrected, and the correction target is determined. When it is determined in the determination step that the correction is not performed, the trapping process is not performed in the trapping step.
An image processing device control method according to still another aspect of the present invention is a control method for an image processing device that performs a trapping process on an image including first and second objects having different colors. A boundary portion searching step for searching for a boundary portion that is an area including adjacent positions where the second object is adjacent to each other, and a first based on the gradation value of each basic color constituting the first object existing in the boundary portion A density calculation step of calculating a density value of the second object, and calculating a density value of the second object based on a gradation value of each basic color constituting the second object existing at the boundary; Based on the density value of the second object, the correction target determination step for determining whether or not the boundary portion is to be corrected, and the correction target determination step determines that the correction target is determined. A trapping step for performing a trapping process on at least a part of the boundary portion, and when it is determined in the correction target determination step that the target is not a correction target, the trapping process is not performed in the trapping step and the correction target determination step is performed. Of the first object existing at the boundary and the color of the second object existing at the boundary based on the density values of the first and second objects. The method further comprises an extended color determining step of determining one as an extended color and determining the other as an extended color, and in the trapping step, a trapping process for expanding at least one basic color constituting the extended color into the extended color region. The extended area is provided in the direction from the adjacent position toward the extended color, and the extended color is configured. As a correction method for each basic color, it is determined that the correction target is an extension region determination step for determining an extension region where at least one basic color and the extended color overlap, and a correction target determination step. Correction that selects either one of the constant gradation correction and the stepped correction based on the gradation value of the first object existing in the portion and the gradation value of the second object existing in the boundary portion A constant gradation correction is a correction method for adding a constant gradation value to the gradation values of the entire extended region, and the staircase correction is stepwise according to the distance from the adjacent position. This is a correction method in which a gradation value that becomes smaller is added to the gradation value in the extended area.
An image processing device control method according to still another aspect of the present invention is a control method for an image processing device that performs a trapping process on an image including first and second objects having different colors. A boundary portion searching step for searching for a boundary portion that is an area including adjacent positions where the second object is adjacent to each other, and a first based on the gradation value of each basic color constituting the first object existing in the boundary portion A density calculation step of calculating a density value of the second object, and calculating a density value of the second object based on a gradation value of each basic color constituting the second object existing at the boundary; Based on the density value of the second object, the correction target determination step for determining whether or not the boundary portion is to be corrected, and the correction target determination step determines that the correction target is determined. A trapping step for performing a trapping process on at least a part of the boundary portion, and when it is determined in the correction target determination step that the target is not a correction target, the trapping process is not performed in the trapping step and the correction target determination step is performed. Of the first object existing at the boundary and the color of the second object existing at the boundary based on the density values of the first and second objects. The method further comprises an extended color determining step of determining one as an extended color and determining the other as an extended color, and in the trapping step, a trapping process for expanding at least one basic color constituting the extended color into the extended color region. The extended area is provided in the direction from the adjacent position toward the extended color, and the extended color is configured. And an extended area determining step for determining an extended area where at least one basic color and the extended color overlap, and in the trapping step, according to the amount of gradation values of basic colors other than black added to the extended area , Reducing the black tone value in the extended region.

  An image processing apparatus control method according to still another aspect of the present invention is an image processing apparatus control method for processing an image including first and second objects having different colors, and the first and second objects. A boundary portion searching step for extracting a boundary portion that is an area including adjacent positions adjacent to each other, and the density of the first object based on the gradation value of each basic color constituting the first object existing in the boundary portion A density calculating step for calculating a value and calculating a density value of the second object based on a gradation value of each basic color constituting the second object existing at the boundary; Based on the density value, one of the color of the first object existing at the boundary and the color of the second object existing at the boundary is determined as the extended color, and the other is the extended color. Extended color determination step determined in the above, and an extended area provided in a direction from the adjacent position toward the extended color, wherein the extended color overlaps at least one basic color constituting the extended color Based on the gradation value of the first object existing in the boundary part and the gradation value of the second object existing in the boundary part as an extended area determination step for determining A correction method selection step for selecting one of a constant gradation correction and a staircase correction and a trapping step for performing a trapping process are provided, and the extended color is configured in the basic colors forming the extended color. When there is a basic color having a gradation value smaller than the gradation value of each basic color, the trapping process is not performed for the basic color in the trapping step, and correction is performed. When constant gradation correction is selected in the method selection step, the gradation value corresponding to the value obtained by subtracting the gradation value of the extended color from the gradation value of the extended color is set to the gradation value of the entire extended area in the trapping step. In addition, when stepped correction is selected in the correction method selection step, the value obtained by subtracting the gradation value of the extended color from the gradation value of the extended color and the value from the adjacent position for the basic color in the trapping step. A gradation value corresponding to a value obtained by multiplying a coefficient that decreases in accordance with the distance is added to the gradation value of the extension area.

An image processing apparatus control program according to still another aspect of the present invention is for executing any one of the above-described image processing apparatus control methods.

  ADVANTAGE OF THE INVENTION According to this invention, the image processing apparatus which can suppress degradation of image quality, the control method of an image processing apparatus, and the control program of an image processing apparatus can be provided.

1 is a block diagram illustrating a configuration of an image forming apparatus 100 according to an embodiment of the present invention. This is a main routine of image processing executed by the image forming apparatus 100. It is a figure which shows an example of the input image in one embodiment of this invention. It is a figure explaining a boundary part search process. It is a figure which shows an example of the gradation value of each basic color which the boundary part search part 51 extracted along the main scanning direction of an input image. It is a subroutine of the boundary part search process of step S3 shown in FIG. It is a figure explaining a color extraction process. It is a subroutine of the color extraction process of step S5 shown in FIG. This is a subroutine of the density calculation process in step S7 shown in FIG. It is a table | surface which shows the relationship between the combination of the density value of an object, and the grade of generation | occurrence | production of a white spot. It is a table | surface which shows the relationship between each boundary part extracted from input image IM1, and the discrimination | determination result by the correction object discrimination | determination part 57 of the boundary part. It is a figure which shows typically the change of the correction object before and behind the correction object discrimination | determination process in input image IM1. This is a subroutine for the correction target determination process in step S9 shown in FIG. This is a subroutine for extended color determination processing in step S11 shown in FIG. It is a figure explaining an expansion area | region determination process. This is a subroutine for the extended area determination process in step S13 shown in FIG. It is a figure explaining a correction method selection process. This is a subroutine of the correction method selection process in step S15 shown in FIG. It is a figure explaining fixed gradation correction. It is a figure explaining step-like correction. It is sectional drawing of the boundary part before a trapping process. It is sectional drawing after performing a fixed gradation correction | amendment with respect to the boundary part shown in FIG. FIG. 22 is a cross-sectional view after the staircase correction is performed on the boundary portion illustrated in FIG. 21. It is a figure explaining the additional correction method of an extended area in case an extended area contains black. This is the first half of the subroutine of the trapping process in step S17 shown in FIG. This is the second half of the subroutine of the trapping process in step S17 shown in FIG. It is a figure explaining the principle which a white spot generate | occur | produces in an image. It is a figure which shows typically the image in which the trapping process was performed. It is a figure which shows typically the color change of the edge of an object which arises by the conventional trapping process.

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

  In the following embodiments, a case where the image processing apparatus is an image forming apparatus will be described. The image forming apparatus has an image forming function, and may be, for example, an MFP (Multifunction Peripheral), a facsimile machine, a copier, or a printer. The image processing apparatus may be an apparatus that does not have an image forming function, such as a PC (Personal Computer), a mobile phone, and a tablet PC, in addition to an image forming apparatus.

  In this specification, cyan may be expressed as C, magenta as M, yellow as Y, and black as K.

  In the following embodiment, it is assumed that an input image to be trapped is composed of four basic colors of cyan, magenta, yellow, and black. The gradation values of cyan, magenta, yellow, and black constituting each pixel constituting the image may be indicated in the form (C, M, Y, K). In this case, each gradation value has a value of 256 steps from 0 to 255, and the density of the basic color increases as the gradation value increases.

  [Configuration of Image Forming Apparatus]

  FIG. 1 is a block diagram showing a configuration of an image forming apparatus 100 according to an embodiment of the present invention.

  Referring to FIG. 1, an image forming apparatus 100 according to the present embodiment is an MFP, and includes a scanner function, a facsimile function, a copying function, a function as a printer, a data communication function, and a server function. The image forming apparatus 100 includes a CPU (Central Processing Unit) 11, a ROM (Read Only Memory) 13, a RAM (Random Access Memory) 15, an auxiliary storage device 17, a network connection unit 19, an image processing unit 21, and the like. , An operation panel 23, an image forming unit 25, and a scanner 27 are provided. The CPU 11, the ROM 13, the RAM 15, the auxiliary storage device 17, the network connection unit 19, the image processing unit 21, the operation panel 23, the image forming unit 25, and the scanner 27 are connected to each other.

  The CPU 11 controls the entire image forming apparatus 100. The CPU 11 operates by executing various programs stored in the ROM 13.

  The ROM 13 stores a program for operating the CPU 11.

  The RAM 15 temporarily stores data and image data necessary for the CPU 11 to operate the program.

  The auxiliary storage device 17 is composed of, for example, an HDD (Hard Disk Drive) or the like, and stores various data such as image data.

  The network connection unit 19 communicates with an external device through Ethernet (registered trademark) or USB. The network connection unit 19 uses a communication device (not shown) when transmitting / receiving data to / from an external device on the WWW (World Wide Web) or the network.

  The image processing unit 21 processes image data to be printed when printing. The image processing unit 21 includes a boundary search unit 51, a color extraction unit 53, a density calculation unit 55, a correction target determination unit 57, an extended color determination unit 59, an extended region determination unit 61, and a correction method selection unit. 63 and a trapping unit 65.

  The operation panel 23 is a user interface that accepts an operation of the image forming apparatus 100 from a user and displays various information to the user.

  The image forming unit 25 is roughly composed of a toner image forming unit, a fixing device, a paper transport unit, and the like. The image forming unit 25 forms an image on a sheet by, for example, electrophotography. The toner image forming unit is configured to be able to form a color image on a sheet (recording medium) by combining four color images by a so-called tandem method. The toner image forming unit includes a photoconductor provided for each of the basic colors of cyan, magenta, yellow, and black, an intermediate transfer belt on which the toner image is transferred (primary transfer) from the photoconductor, and a sheet from the intermediate transfer belt to the sheet. The image forming apparatus includes a transfer unit that transfers an image (secondary transfer). The fixing device has a heating roller and a pressure roller. The fixing device conveys the sheet on which the toner image is formed between the heating roller and the pressure roller, and heats and presses the sheet. As a result, the fixing device melts the toner adhering to the paper and fixes it on the paper to form an image on the paper. The paper transport unit includes a paper feed roller, a transport roller, and a motor that drives them. The paper transport unit feeds paper from the paper feed cassette and transports the paper inside the housing of the image forming apparatus 100. Further, the paper transport unit discharges the paper on which the image is formed from the housing of the image forming apparatus 100 to a paper discharge tray or the like.

  The scanner 27 reads an image of a document and creates image data.

  [Image processing overview]

  When printing an input image input from the scanner 27 or an external device connected to the image forming apparatus 100, the image forming apparatus 100 performs the image processing described below on the input image, and after the image processing Print the image.

  FIG. 2 is a main routine of image processing executed by the image forming apparatus 100.

  Referring to FIG. 2, when image processing becomes necessary (for example, when a print execution instruction is received), CPU 11 of image forming apparatus 100 acquires input image IM1 (S1), and searches for a boundary portion. The boundary portion search process is performed using 51 (S3). Next, the CPU 11 performs color extraction processing using the color extraction unit 53 (S5), and performs density calculation processing using the density calculation unit 55 (S7). Subsequently, the CPU 11 performs a correction target determination process using the correction target determination unit 57 (S9), and performs an extended color determination process using the extended color determination unit 59 (S11). Next, the CPU 11 performs an extended area determination process using the extended area determination unit 61 (S13), and performs a correction method selection process using the correction method selection unit 63 (S15). Subsequently, the CPU 11 performs a trapping process using the trapping unit 65 (S17), performs an output process for printing the input image after the trapping process using the image forming unit 25 (S19), and ends the process.

  [Boundary part search processing]

  Next, the boundary part search process will be described.

  In the boundary part searching process, the boundary part searching part 51 searches for a boundary part that is an area including adjacent positions where two objects are adjacent to each other in an image including two objects having different colors.

  FIG. 3 is a diagram illustrating an example of an input image according to the embodiment of the present invention.

  Referring to FIG. 3, an input image IM1 includes objects OB1 and OB3 with black characters “A”, objects OB2 and OB4 with light blue characters “A”, and brown backgrounds of objects OB1 and OB2. A certain object OB5 and an object OB6 that is a yellow background of the objects OB3 and OB4 are included. The gradation values of the basic colors in each of the objects OB1 to OB6 are constant throughout (the objects OB1 to OB6 have the same color throughout). Here, description will be made assuming that the target of the boundary portion search process is the input image IM1.

  FIG. 4 is a diagram for explaining the boundary portion search processing.

  Referring to FIG. 4, boundary search unit 51, as shown in FIG. 4A, includes direction DR <b> 1 that is the main scanning direction of input image IM <b> 1, direction DR <b> 2 that is the sub-scanning direction of input image IM <b> 1, and diagonally. And the gradation value of each basic color in the scanned direction is extracted. The scanning direction when extracting gradation values is arbitrary. Then, as shown in FIG. 4B, the boundary searching unit 51 determines the position where the change amount of the gradation value of each basic color is larger than the change amount threshold value (an example of the second threshold value) as the adjacent position BP ( And an area including the adjacent position BP (here, an area within one dot from the adjacent position BP) is extracted as a boundary portion. From the input image IM1, a boundary part RG1A between the objects OB1 and OB5, a boundary part RG1B between the objects OB2 and OB5, a boundary part RG1C between the objects OB3 and OB6, and a boundary between the objects OB4 and OB6 The part RG1D and the boundary part RG1E between the objects OB5 and OB6 are extracted. The extracted boundary portion is a temporary correction target. Whether or not the provisional correction target is the correction target is determined in the correction target determination process.

  FIG. 5 is a diagram illustrating an example of the gradation values of each basic color extracted by the boundary search unit 51 along the main scanning direction of the input image. (A) is a cyan gradation value, (b) is a magenta gradation value, (c) is a yellow gradation value, and (d) is a black gradation value.

  Referring to FIG. 5, it is assumed here that the change amount threshold is 50. As shown in FIG. 5B, the magenta tone value changes by a change amount of 55 (= 70-15) at the position PO2. Since the change amount of the magenta tone value exceeds the change amount threshold value, the boundary portion search unit 51 determines the position PO2 as the adjacent position BP from the magenta tone value, and sets the region including the position PO2 as the boundary portion RG1 ( The boundary portion RG1 is extracted as a boundary portion RG1A, RG1B, RG1C, RG1D, and RG1E).

  On the other hand, as shown in FIG. 5A, the cyan tone value changes by a change amount of 10 (= 25-15) at the position PO1. Since the change amount of the cyan gradation value is less than the change amount threshold value, the boundary portion search unit 51 does not extract the boundary portion from the cyan gradation value. Since the yellow gradation value is constant in the main scanning direction as shown in FIG. 5C, the boundary portion search unit 51 does not extract the boundary portion from the yellow gradation value. The black tone value changes by a change amount of 5 (= 20-15) at the position PO3. Since the change amount of the black gradation value is less than the change amount threshold value, the boundary portion search unit 51 does not extract the boundary portion from the black gradation value.

  The boundary searching unit 51 preferably extracts a region having a large gradation change as the boundary, but the boundary searching method performed by the boundary searching unit 51 is arbitrary.

  FIG. 6 is a subroutine of the boundary portion search process in step S3 shown in FIG.

  Referring to FIG. 6, in the boundary portion search process, CPU 11 has a change amount of the gradation value extracted along an arbitrary scanning direction for each of the basic colors of cyan, magenta, yellow, and black equal to or greater than a threshold value. If it is determined that the position is equal to or greater than the threshold, the position is determined as an adjacent position (edge determination) (steps S101, S103, S105, and S107). Next, the CPU 11 determines whether or not the adjacent position is determined in any of cyan, magenta, yellow, and black (OR determination is performed) (S109). Next, when determining the adjacent position, the CPU 11 sets (masks) an area within one dot from the adjacent position as a boundary (S111), and returns.

  [Color extraction processing]

  Next, the color extraction process will be described.

  In the color extraction process, the color extraction unit 53 extracts the gradation value of each of the two objects present at the boundary.

  Here, it is assumed that the target of color extraction processing is the input image IM1, and the boundary portion RG1B between the object OB2 and the object OB5 will be described. Similar color extraction processing is performed for other boundary portions in the input image IM1.

  FIG. 7 is a diagram for explaining the color extraction processing.

  Referring to FIG. 7, color extracting unit 53 includes a region RG2A (a preset matrix) having a certain size existing in object OB2 existing in boundary portion RG1B and an object OB5 existing in boundary portion RG1. An existing region RG2B having a certain size is extracted. Here, an area having a size of 1 bit × 3 bits is extracted. The positions where the regions RG2A and RG2A are extracted are arbitrary.

  Then, the color extraction unit 53 performs gradation values (C1, M1, Y1, K1), (C2, M2, Y2, K2), and (C3, M3) of the basic colors constituting each of the three pixels in the region RG2A. , Y3, K3). Here, since the inside of the object OB2 is the same color, C1, C2 and C3 have the same value, M1, M2 and M3 have the same value, Y1, Y2 and Y3 have the same value, and K1, K2 And K3 are the same value.

  Next, the color extraction unit 53 calculates the average gradation value (AC1, AM1, AY1, AK1) of the region RG2A from the gradation values of the basic colors constituting the three pixels ((C1 + C2 + C3) / 3, (M1 + M2 + M3)). / 3, (Y1 + Y2 + Y3) / 3, (K1 + K2 + K3) / 3).

  The color extraction unit 53 calculates the average gradation value (AC2, AM2, AY2, AK2) of the region RG2B by the same method.

  The average gradation value (AC1, AM1, AY1, AK1) of the region RG2A is used as the gradation value of the object OB2 existing in the boundary portion RG1B in the subsequent processing, and the average gradation value (AC1, AM1 of the region RG2B). , AY1, AK1) are representative colors of the object OB2 existing in the boundary portion RG1B. The average gradation value (AC2, AM2, AY2, AK2) of the region RG2B is used as the gradation value of the object OB5 existing in the boundary portion RG1B in the subsequent processing, and the average gradation value (AC2, AM2 of the region RG2B) , AY2, AK2) are representative colors of the object OB5 existing in the boundary portion RG1B.

  Note that the color extraction unit 53 may extract the gradation values of the respective basic colors constituting the two objects existing at the boundary, and the extraction method is arbitrary.

  FIG. 8 is a subroutine of the color extraction process in step S5 shown in FIG.

  Referring to FIG. 8, in the color extraction process, CPU 11 extracts a gradation value of a region of a certain size existing inside each of two objects existing at the boundary (reads a set matrix). (S201). Next, the CPU 11 calculates the average gradation value (average value in the set matrix) of the extracted area (S203). Next, the CPU 11 determines whether or not the average gradation value of the objects existing in all the boundary portions has been calculated (S205).

  If it is determined in step S205 that the average gradation values of the objects existing in all the boundary portions have been calculated (YES in S205), the CPU 11 returns. On the other hand, if it is determined in step S205 that the average gradation values of the objects existing in all the boundary portions have not been calculated (NO in S205), the CPU 11 proceeds to the processing in step S201 and exists in other boundary portions. The gradation values of the two objects to be extracted are extracted.

  [Density calculation processing]

  Next, the density calculation process will be described.

  In the density calculation process, the density calculation unit 55 calculates the density value of one object based on the gradation value of each basic color that constitutes one of the two objects existing at the boundary, and the other Based on the gradation value of each basic color constituting the object, the density value of the other object is calculated.

  Here, it is assumed that the target of the density calculation process is the input image IM1, and the boundary portion RG1B between the object OB2 and the object OB5 will be described. Similar density calculation processing is performed for other boundary portions in the input image IM1.

  The gradation value of the object OB2 existing in the boundary portion RG1B is (AC1, AM1, AY1, AK1), and the gradation value of the object OB5 existing in the boundary portion RG1B is (AC2, AM2, AY2, AK2). And The density calculation unit 55 calculates the density value D2 of the object OB2 existing in the boundary part RG1B by the following equation (1).

  Concentration value D2 = Wc × AC1 + Wm × AM1 + Wy × AY1 + Wk × AK1 (1)

  In the above equation (1), Wc, Wm, Wy, and Wk are cyan, magenta, yellow, and black density calculation coefficients (an example of a first coefficient), respectively. As the density calculation coefficient, for example, a fixed value in the range of 0 to 100 is set. The density calculation coefficient is preferably set so that the calculated density value is proportional to the reciprocal of the brightness.

  In other words, the density calculation unit 55 determines the gradation value (AC1, AM1, AY1, AK1) of each basic color constituting the object OB2 existing in the boundary part RG1B, and the density calculation coefficient ( Wc, Wm, Wy, Wk) and the result of adding all the multiplied values is calculated as the density value D2 of the object OB2 existing in the boundary portion RG1B.

  As an example, the gradation values of the basic colors constituting the object OB2 existing in the boundary part RG1B are (100, 20, 10, 5), and the density calculation coefficients (Wc, Wm, Wy, Wk) are (24, 44, 3, 66), the density value D2 is calculated by the following equation (2).

  Density value D2 = 100 × 24 + 20 × 44 + 10 × 3 + 5 × 66 = 3640 (2)

  Similarly, the density calculation unit 55 calculates the density value D5 of the object OB5 existing in the boundary part RG1B by the following equation (3).

  The density value D5 of the object OB5 existing in the boundary portion RG1B = Wc × AC2 + Wm × AM2 + Wy × AY2 + Wk × AK2 (3)

  In other words, the density calculation unit 55 determines the gradation value (AC2, AM2, AY2, AK2) of each basic color constituting the object OB5 existing in the boundary part RG1B and the density calculation coefficient ( Wc, Wm, Wy, Wk), and the result of adding all the multiplied values is calculated as the density value D5 of the object OB present in the boundary portion RG1B.

  The density calculation unit 55 calculates the density value of one object based on the gradation value of each basic color that constitutes one of the two objects existing at the boundary, and configures the other object. The density value of the other object may be calculated based on the gradation value of each basic color, and the density value calculation method is arbitrary.

  FIG. 9 is a subroutine of the density calculation process in step S7 shown in FIG.

  Referring to FIG. 9, in the density calculation process, CPU 11 reads the cyan gradation value constituting the object existing at the boundary (S301), and multiplies the cyan density calculation coefficient Wc by the cyan gradation value. Thus, the cyan density value CD is calculated (S303). Next, the CPU 11 reads the magenta gradation value constituting the object existing at the boundary (S305), and multiplies the magenta density calculation coefficient Wm by the magenta gradation value to obtain the magenta density value MD. Calculate (S307). Subsequently, the CPU 11 reads the yellow gradation value constituting the object existing at the boundary (S309), and multiplies the yellow density calculation coefficient Wy by the yellow gradation value to obtain the yellow density value YD. Calculate (S311). Next, the CPU 11 reads the black gradation value constituting the object existing at the boundary (S313), and multiplies the black density calculation coefficient Wk by the black gradation value to obtain the black density value KD. Calculate (S315). Subsequently, the CPU 11 adds the calculated density values CD, MD, YD, and KD of all the basic colors to calculate the density value of the object existing at the boundary (S317). Next, the CPU 11 determines whether or not the density values of all the boundary objects have been calculated (S319).

  If it is determined in step S319 that the density values of all the boundary objects have been calculated (YES in S319), the CPU 11 returns. On the other hand, if it is determined in step S319 that the density values of all the boundary objects have not been calculated (NO in S319), the CPU 11 proceeds to the process of step S301, and performs the cyan gradations constituting other objects. Read the value.

  [Correction target discrimination process]

  Next, the correction target determination process (correction cancellation process) will be described.

  In the correction target determination process, the correction target determination unit 57 determines whether or not the boundary portion is to be corrected based on the density values of the two objects existing at the boundary portion.

  The boundary portion determined as the correction target by the correction target determination unit 57 is the target of the trapping process by the trapping unit 65. On the other hand, the boundary portion that the correction target determination unit 57 determines not to be a correction target is not a target of the trapping process by the trapping unit 65.

  FIG. 10 is a table showing the relationship between combinations of density values of objects and the degree of occurrence of white spots.

  Referring to FIG. 10, image 1 includes a dark blue background object and a black character object, and both the background and character objects have a high density. In the case of the image 1, when white spots occur, the white spots become conspicuous.

  The image 2 includes a black background object and a yellow character object. The background object has a high density and the character object has a low density. In the case of the image 2, even if white spots occur, the white spots are hardly noticeable.

  The image 3 includes a yellow background object and a black character object. The background object has a low density and the character object has a high density. In the case of the image 3, even if white spots occur, the white spots are hardly noticeable.

  The image 4 includes a light blue background object and a yellow character object, and both the background and character objects have a low density. In the case of the image 4, even if white spots occur, the white spots are hardly noticeable.

  In consideration of the relationship illustrated in FIG. 10, the correction target determination unit 57 determines that at least one of the density values of two objects existing at the boundary is equal to or less than a density threshold value (an example of a first threshold value). Determines that white spots are not noticeable even when printing misalignment occurs at the boundary. In this case, it is determined that the boundary is not a correction target, and the boundary is excluded from the correction target.

  Here, it is assumed that the density threshold is 1000. An arbitrary value can be set as the density threshold, and for example, it may be set by the following method. First, a plurality of images including two objects having an arbitrary color selected from the sample color chart are printed in a state in which print misalignment is generated. Next, the user visually checks each printed image to determine whether or not white spots are conspicuous. Then, a boundary value between the density value of the object in the image determined to be conspicuous and the density value of the object in the image determined not to be conspicuous is set as a density threshold value.

  Here, description will be made assuming that the target of the correction target determination process is the input image IM1.

  FIG. 11 is a table showing the relationship between each boundary extracted from the input image IM1 and the determination result of the correction target determination unit 57 at the boundary.

  Referring to FIG. 11, regarding the boundary portion RG1A, the density value of the object OB1 is 16830 (> 1000), and the density value of the object OB5 is 8380 (> 1000). Since the density values of the two objects constituting the boundary part RG1A are both greater than the density threshold value, the correction target determination unit 57 determines that the boundary part RG1A is the correction target.

  Regarding the boundaries RG1B and RG1D, the density values of the objects OB2 and OB4 are 880 (≦ 1000). In the boundary portions RG1B and RGID, since the density value of at least one object existing in the boundary portion is equal to or less than the density threshold value, the correction target determination unit 57 determines that the boundary portions RG1B and RG1D are not correction targets, and the boundary portion RG1B And RG1D are excluded from correction targets.

  Regarding the boundary portions RG1C, RG1D, and RG1E, the density value of the object OB6 is 240 (≦ 1000). In the boundary portions RG1C, RG1D, and RG1E, since the density value of at least one object existing in the boundary portion is equal to or lower than the density threshold value, the correction target determination unit 57 does not require the boundary portions RG1C, RG1D, and RG1E to be corrected. The boundary portions RG1C, RG1D, and RG1E are excluded from correction targets.

  FIG. 12 is a diagram schematically illustrating a change in the correction target before and after the correction target determination process in the input image IM1. (A) shows the correction target before the correction target discrimination process, and (b) shows the correction target after the correction target discrimination process.

  Referring to FIG. 12A, before the correction target determination process, the boundary portions RG1A, RG1B, RG1C, RG1D, and RG1E extracted by the boundary search unit 51 are correction targets (temporary correction targets). . On the other hand, referring to FIG. 12B, after correction target determination processing, boundary portions RG1B, RG1C, RG1D, and RG1E are excluded from correction targets by correction target determination portion 57. As a result, only boundary portion RG1A is excluded. It becomes a correction target.

  FIG. 13 is a subroutine for the correction target determination process in step S9 shown in FIG.

  Referring to FIG. 13, in the correction target determination process, CPU 11 reads the density values of each of the two objects existing at the boundary (S401), and whether the density values of the two objects are both greater than or equal to the density threshold value. It is determined whether or not (S403).

  If it is determined in step S403 that the density values of the two objects are both greater than or equal to the density threshold (YES in S403), the CPU 11 proceeds to step S405 without excluding the boundary from the correction target. On the other hand, when it is determined in step S403 that at least one of the density values of the two objects is less than the density threshold (NO in S403), the CPU 11 excludes the boundary from the correction target (S407). Proceed to step S405.

  In step S405, the CPU 11 determines whether or not the determination processing in step S403 has been performed for all boundary portions (S405). If it is determined in step S405 that the determination process of step S403 has been performed for all the boundary portions (YES in S405), the CPU 11 returns. On the other hand, if it is determined in step S405 that the determination process of step S403 has not been performed for all the boundary parts (NO in S405), the CPU 11 proceeds to the process of step S401, and two objects existing in other boundary parts Read each density value.

  [Extended color determination processing]

  Next, extended color determination processing (extended direction determination processing) will be described.

  In the extended color determination process, the extended color determination unit 59 expands the color of one of the two objects existing in the boundary portion based on the density value of the two objects existing in the boundary portion to be corrected. And the color of the other object is determined as the extended color. At least one basic color constituting the extended color is extended toward the extended color area in the trapping process described later.

  Specifically, the extended color determination unit 59 determines the color of an object having a relatively low density value among the density values of two objects existing at the boundary as an extended color, and the relatively higher density The color of the object having a value is determined as the extended color.

  Here, it is assumed that the target of the extended color determination process is the boundary portion RG1A of the input image IM1.

  Referring to FIG. 11, extended color determination unit 59 compares the density value (16830) of object OB1 present at boundary portion RG1A of input image IM1 with the density value (8380) of object OB5. As a result, the color of the object OB5 having a relatively low density value is determined as the extended color, and the color of the object OB1 having a relatively high density is determined as the extended color.

  Note that the method for determining the extended color and the extended color is arbitrary, and may be based on a standard other than the density value (for example, brightness).

  FIG. 14 is a subroutine of extended color determination processing in step S11 shown in FIG.

  Referring to FIG. 14, in the extended color determination process, CPU 11 reads the density values of two objects existing at the boundary to be corrected (S501), and the density value of one object is the density of the other object. It is determined whether or not the value is larger than the value (S503).

  If it is determined in step S503 that the density value of one object is greater than the density value of the other object (YES in S503), the CPU 11 determines the color of one object as an extended color and determines the color of the other object. The color is determined as an extended color (S505), and the process proceeds to step S509.

  If it is determined in step S503 that the density value of one object is less than or equal to the density value of the other object (NO in S503), the CPU 11 determines the color of one object as an extended color and the color of the other object Is determined as an extended color (S507), and the process proceeds to step S509.

  In step S509, the CPU 11 determines whether or not the extended color and the extended color have been determined at all the correction target boundary portions (S509).

  If it is determined in step S509 that the extended color and the extended color have been determined at all the correction target boundaries (YES in S509), the CPU 11 ends the process. On the other hand, if it is determined in step S509 that the extended color and the extended color have not been determined in all the boundary portions to be corrected (NO in S509), the CPU 11 proceeds to the processing in step S501, and the boundary of another correction target is determined. The density value of each of the two objects existing in the part is read.

  [Extended area determination processing]

  Next, the extended area determination process will be described.

  In the extended area determination process, the extended area determination unit 61 determines an extended area at the boundary part to be corrected. The extended area is an area in which two objects existing in the boundary portion are provided in the direction from the adjacent positions adjacent to each other toward the extended color, and at least one basic color and the extended color constituting the extended color are included. It is an overlapping area.

  Here, description will be made assuming that the target of the extended region determination process is the boundary portion RG1A of the input image IM1.

  FIG. 15 is a diagram illustrating the extended area determination process. In FIG. 15, for convenience of explanation, hatching indicating the colors of the objects OB1 and OB5 is omitted.

  Referring to FIG. 15A, in the boundary portion RG1A, the color of the object OB1 is an extended color, and the color of the object OB5 is an extended color. In this case, as shown in FIG. 15B, the extension area determination unit 61, for example, within 3 dots in the direction from the adjacent position BP between the objects OB1 and OB5 toward the extended color (direction toward the object OB1). Is determined as the extension region RG3.

  The width of the extension region RG3 (the distance from the adjacent position BP to the boundary of the extension region RG3) can be set to an arbitrary value. As the width of the extended region RG3 is increased, the correction width (corresponding print displacement amount) in the trapping process is increased. Here, the width of the extension area is 3 dots.

  FIG. 16 is a subroutine of the extended area determination process in step S13 shown in FIG.

  Referring to FIG. 16, in the extended area determination process, CPU 11 reads the extended color and the extended color (S601), and reads the width of the extended area (S603). Subsequently, the CPU 11 determines an extension area in a direction from the adjacent position toward the extended color based on the width of the extension area (S605). Next, the CPU 11 determines whether or not an extension region has been determined at all the correction target boundary portions (S607).

  If it is determined in step S607 that the extended region has been determined at all the correction target boundaries (YES in S607), the CPU 11 ends the process. On the other hand, if it is determined in step S607 that the extension region has not been determined for all the correction target boundary portions (NO in S607), the CPU 11 proceeds to the processing in step S601, and the extended color of the other correction target boundary portions. And read the extended color.

  [Correction method selection process]

  Next, the correction method selection process will be described.

  In the correction method selection process, the correction method selection unit 63 performs a constant gradation correction and a step-like correction based on the gradation values of two objects existing at the boundary as a correction method for the boundary part to be corrected. Choose one of the methods. The correction method selection unit 63 selects one of a constant gradation correction and a stepped correction for each of the basic colors of cyan, magenta, yellow, and black.

  FIG. 17 is a diagram for explaining correction method selection processing. (A) is sectional drawing of the boundary part used as the correction | amendment method selection process object, (b) shows the gradation value of two objects which exist in the boundary part shown to (a), and the selection result of the correction method. It is a table | surface shown.

  Referring to FIG. 17A, the boundary to be corrected is composed of a character object and a background object. Referring to FIG. 17B, the character object existing at the boundary has a gradation value (C, M, Y, K) = (120, 120, 100, 0). The background object existing at the boundary portion has gradation values (C, M, Y, K) = (20, 140, 160, 0). The color of the background object is determined as the extended color, and the color of the background object is determined as the extended color.

  The correction method selection unit 63 extracts, for each of the basic colors of cyan, magenta, yellow, and black, the smaller one of the gradation values of the two objects existing at the boundary. Then, the correction method selection unit 63 selects fixed gradation correction when the extracted gradation value is equal to or less than the selection threshold (an example of the third threshold), and when the extracted gradation value exceeds the selection threshold. Selects staircase correction. Although the selection threshold can be set to an arbitrary value, it is assumed here that the selection threshold is 100.

  When the boundary shown in FIG. 17A is a correction target, the correction method selection unit 63 determines (C, M, and C) for the basic colors of cyan, magenta, yellow, and black from the tone values of the two objects. A gradation value of Y, K) = (20, 120, 100, 0) is extracted. Then, by comparing the extracted gradation value with the selection position, the constant gradation correction is selected as the cyan and magenta correction method, and the stepped correction is selected as the yellow and black correction method.

  FIG. 18 is a subroutine of the correction method selection process in step S15 shown in FIG.

Referring to FIG. 18, in the correction method selection process, CPU 11 extracts the smaller gradation value of the gradation values of the basic colors constituting the two objects existing at the boundary (S701). Next, the CPU 11 determines whether or not the extracted gradation value is larger than a selection threshold (S703).

  If it is determined in step S703 that it is larger than the selection threshold value (YES in S703), the CPU 11 selects stepped correction as the basic color correction method (S705), and proceeds to the process in step S709.

  If it is determined in step S703 that it is equal to or smaller than the selection threshold (NO in S703), the CPU 11 selects constant gradation correction as the basic color correction method (S707), and proceeds to the process of step S709.

  In step S709, the CPU 11 determines whether or not the correction method has been determined for all the correction target boundaries (S709).

  If it is determined in step S709 that the correction method has been determined for all the correction target boundaries (YES in step S709), the CPU 11 ends the process. On the other hand, if it is determined in step S709 that the correction method has not been determined for all the correction target boundary portions (NO in S709), the CPU 11 proceeds to the processing in step S701 and exists in another correction target boundary portion. Of the gradation values of the basic colors of the two objects, the smaller gradation value is extracted.

  [Trapping process]

  Next, the trapping process will be described.

  In the trapping process, the trapping unit 65 uses the correction method selected by the correction method selection unit 63 with respect to the extended region of the boundary part to be corrected, and determines the level of a specific basic color among the basic colors constituting the extended color. Add a key value to the extended area.

    (1) How to determine the basic color to be added to the extended area

  The trapping unit 65 compares the gradation value of each basic color constituting the extended color with the gradation value of each basic color constituting the extended color. The trapping unit 65 adds only a basic color having a gradation value larger than the gradation value of each basic color constituting the extended color among basic colors constituting the extended color to the extended region ( Basic color for trapping processing). In other words, the trapping unit 65 adds the basic color having a gradation value equal to or lower than the gradation value of each basic color constituting the extended color from the basic colors constituting the extended color from the basic colors constituting the extended color. exclude.

  Here, the description will be made assuming that the boundary shown in FIG. 17A is the target of the trapping process.

  Referring to FIGS. 17A and 17B, in this boundary portion, the color of the character object is the extended color, and the color of the background object is the extended color. The gradation values (C, M, Y, K) = (120, 120, 100, 0) of the basic colors constituting the extended color and the gradation values (C, M) of the basic colors constituting the extended color , Y, K) = (20, 140, 160, 0), among the basic colors constituting the extended color, the gradation value larger than the gradation value of each basic color constituting the extended color Only cyan has. Accordingly, the trapping unit 65 uses only cyan as a basic color to be added to the extended area (basic color for performing the trapping process), and excludes magenta, yellow, and black from the basic colors to be added to the extended area.

  (2) Constant gradation correction

  When the constant gradation correction is selected as the correction method, the trapping unit 65 adds the gradation value of the basic color constituting the extended color to the extended area by the following method.

  Here, description will be made assuming that the boundary portion shown in FIG. 17A is a target of constant gradation correction.

  FIG. 19 is a diagram for explaining constant gradation correction. (A) is a cross-sectional view of the boundary portion before the constant gradation correction is performed, and (b) is a cross-sectional view of the boundary portion after the constant gradation correction is performed.

  Referring to FIG. 19, the constant gradation correction is a correction method in which a constant gradation value is added to the gradation value of the entire extension region RG3 regardless of the distance from the adjacent position. The constant gradation correction has a greater effect of suppressing the deterioration of the image quality when the printing deviation occurs compared to the stepped correction. The gradation value added to the entire extended region RG3 is preferably a gradation value corresponding to a value obtained by subtracting the gradation value of the extended color from the gradation value of the extended color, for example.

  Specifically, the gradation value of each pixel existing in the extension region RG3 is calculated by the following equations (4) to (6).

  Tone value of pixels within 1 dot from adjacent position BP = {(tone value of extended color) − (tone value of extended color)} × CF1 + (tone value of extended color) (. 4)

  Tone value of pixel within 2 dots from adjacent position BP = {(tone value of extended color) − (tone value of extended color)} × CF1 + (tone value of extended color) (. 5)

  Tone value of pixels within 3 dots from adjacent position BP = {(tone value of extended color) − (tone value of extended color)} × CF1 + (tone value of extended color) (. 6)

  The calculation coefficient CF1 is a calculation coefficient in the case of constant gradation correction, and is set to an arbitrary value in the range of 0 <CF1 ≦ 1. The calculation coefficient CF1 is preferably 1 (100%).

  As a result of the constant gradation correction, as shown in FIG. 19B, the cyan gradation value in the extended region RG3 becomes the same value as the cyan gradation value in the character object.

  The calculation coefficient CF1 may be a constant value regardless of the basic color, or may be a different value for each basic color.

  (3) Staircase correction

  When the staircase correction is selected as the correction method, the trapping unit 65 adds the gradation value of the basic color constituting the extended color to the gradation value of the extended area by the following method.

  Here, description will be made assuming that the boundary portion shown in FIG. 17A is a target of constant gradation correction.

  FIG. 20 is a diagram for explaining the staircase correction. (A) is sectional drawing of the boundary part before performing staircase shape correction | amendment, (b) is sectional drawing of the boundary part after performing staircase shape correction | amendment.

  Referring to FIG. 20, the staircase correction is a correction method in which a gradation value that decreases in a staircase shape according to the distance from the adjacent position BP (distance from the edge) is added to the extension region RG3. The staircase correction has a greater effect of suppressing deterioration in image quality when there is no print misalignment, compared to the constant gradation correction. In the staircase correction, for the basic color, a value obtained by subtracting the gradation value of the extended color from the gradation value of the extended color, and arithmetic coefficients CF2, CF3, and CF4 (decrease according to the distance from the adjacent position BP). It is preferable that a gradation value corresponding to a value obtained by multiplying an example of the second coefficient) is added to the gradation value of the extension region RG3 (the gradation value of the extended color).

  Specifically, the gradation value of each pixel existing in the extension region RG3 is calculated by the following equations (7) to (9).

  Tone value of pixels within 1 dot from adjacent position BP = {(tone value of extended color) − (tone value of extended color)} × CF2 + (tone value of extended color) ( 7)

  Tone value of pixel within 2 dots from adjacent position BP = {(tone value of extended color) − (tone value of extended color)} × CF3 + (tone value of extended color) 8)

  Tone value of pixel within 3 dots from adjacent position BP = {(tone value of extended color) − (tone value of extended color)} × CF4 + (tone value of extended color) 9)

  Each of the operation coefficients CF2, CF3, and CF4 is set to an arbitrary value that satisfies 0 <CF4 <CF3 <CF2 ≦ 1. The calculation coefficient CF2 is preferably 0.75 (75%), the calculation coefficient CF3 is preferably 0.5 (50%), and the calculation coefficient CF4 is preferably 0.25 (25%).

  Each of the arithmetic coefficients CF2, CF3, and CF4 may be a constant value regardless of the basic color, or may be a value that is different for each basic color.

  (4) Correction method for adding black to the extended area

  In order to prevent the expansion area from becoming darker than necessary by adding black, the calculation coefficient when adding black to the expansion area is smaller than the calculation coefficient when adding cyan, magenta, or yellow to the expansion area. It is preferable.

  FIG. 21 is a cross-sectional view of the boundary portion before the trapping process.

  Referring to FIG. 21, here, the boundary portion shown in FIG. 21A is compared with the boundary portion shown in FIG. The boundary shown in FIG. 21A includes character objects having gradation values (C, M, Y, K) = (100, 0, 0, 0) and gradation values (C, M, Y, K) = (0,100,100,0) and the background object. The color of the character object (cyan) is the extended color, and the color of the background object (magenta and yellow) is the extended color. In the case of FIG. 21A, a cyan gradation value is added to the extended region.

  The boundary shown in FIG. 21B includes character objects having gradation values (C, M, Y, K) = (0, 0, 0, 100) and gradation values (C, M, Y, K) = consists of background objects having (100,100,0,0). The character object color (black) is an extended color, and the background object colors (cyan and magenta) are extended colors. In the case of FIG. 21B, the black gradation value is added to the extended region.

  Thereafter, in order to distinguish between the calculation coefficient when adding cyan, magenta, or yellow to the expansion area and the calculation coefficient when adding black to the expansion area, the calculation coefficient when adding black to the expansion area is the calculation coefficient CF1K. , CF2K, CF3K, and CF4K. Between each of the operation coefficients CF1, CF2, CF3, and CF4 and each of the operation coefficients CF1K, CF2K, CF3K, and CF4K, CF1K <CF1, CF2K <CF2, CF3K <CF3, and CF4K <CF4, respectively. A relationship is established. Each of the operation coefficients CF1K, CF2K, CF3K, and CF4K is half the value of each of the operation coefficients CF1, CF2, CF3, and CF4 (specifically, the operation coefficient CF1K is 0.5 (50%)). The calculation coefficient CF2K is preferably 0.375 (37.5%), the calculation coefficient CF3K is 0.25 (25%), and the calculation coefficient CF4K is 0.125 (12.5%)).

  FIG. 22 is a cross-sectional view after the constant gradation correction is performed on the boundary portion shown in FIG. FIG. 21A shows a state after the constant gradation correction of the boundary portion shown in FIG. 21A, and FIG. 21B shows a state after the constant gradation correction of the boundary portion shown in FIG.

  Referring to FIG. 22, in the case of the boundary portion shown in FIG. 21 (a), the cyan gradation value existing in the extension region RG3 is expressed by the equation (4) based on the cyan calculation coefficient CF1 by constant gradation correction. To the value calculated by (6). On the other hand, in the case of the boundary portion shown in FIG. 21B, the black tone value existing in the extension region RG3 is calculated by the formulas (4) to (6) based on the black calculation coefficient CF1K by constant tone correction. Set to the calculated value. In conclusion, when the difference between the gradation value of the extended color and the gradation value of the extended color is the same value, the black gradation value added to the extended area RG3 is the level other than black added to the extended area RG3. It becomes smaller than the key value.

  FIG. 23 is a cross-sectional view after the staircase correction is performed on the boundary portion shown in FIG. FIG. 21A shows the boundary portion after stepwise correction shown in FIG. 21A, and FIG. 21B shows the boundary portion after stepwise correction shown in FIG.

  Referring to FIG. 23, in the case of the boundary portion shown in FIG. 21A, the cyan gradation value existing in the extension region RG3 is calculated based on the cyan calculation coefficients CF2, CF3, and CF4 by the staircase correction. It is set to the value calculated by the equations (7) to (9). On the other hand, in the case of the boundary portion shown in FIG. 21B, the black tone value existing in the extension region RG3 is calculated by the formula (7) based on the black calculation coefficients CF2K, CF3K, and CF4K by constant tone correction. To the value calculated by (9). In conclusion, when the difference between the gradation value of the extended color and the gradation value of the extended color is the same value, the black gradation value added to the extended area RG3 is the level other than black added to the extended area RG3. It becomes smaller than the key value.

  Note that the calculation coefficient when black is added to the extended area with constant gradation correction and the calculation coefficient when cyan, magenta, or yellow is added to the extended area with constant gradation correction are set to the same value (that is, CF1K = CF1). The calculation coefficient when black is added to the expansion area by the staircase correction may be smaller than the calculation coefficient when cyan, magenta, or yellow is added to the expansion area by the staircase correction (that is, CF2K < CF2, CF3K <CF3, and CF4K <CF4).

  (5) Additional correction method for the extension area when the extension area includes black

  When cyan, magenta, or yellow is added to the extended area including black, the area is likely to undergo color change due to higher density. In order to suppress the color change due to the high density in the extended area including black, it is preferable to reduce the black gradation value in the extended area according to the amount of the gradation value of the basic color other than black added to the extended area. .

  FIG. 24 is a diagram for explaining an additional correction method for the extension region when the extension region includes black. (A) is a cross-sectional view of the boundary part before the trapping process, (b) is a cross-sectional view after performing the staircase correction on the boundary part shown in (a), (c), It is sectional drawing after performing a fixed gradation correction | amendment with respect to the boundary part shown to (a).

  Referring to FIG. 24A, the boundary includes character objects having gradation values (C, M, Y, K) = (100, 0, 0, 0) and gradation values (C, M , Y, K) = (100, 100, 0, 0). The background object colors (cyan and magenta) are extended colors, and the character object color (black) is an extended color. In the case of FIG. 24A, cyan and magenta tone values are added to the extended region.

  Referring to FIG. 24B, the gradation values of cyan and magenta existing in the extension region RG3 are expressed by the equations (4) to (4) based on the respective calculation coefficients CF1 of cyan and magenta by constant gradation correction. The value calculated by (6) is set. On the other hand, the black gradation value existing in the extension region RG3 is set to a value calculated by the following equations (10) to (14).

  Black tone value of each pixel in the extension region RG3 = (Black tone value before trapping processing of each pixel in the extension region RG3) − (Black tone value adjustment value of each pixel) (10)

  Black gradation value adjustment value = (cyan gradation value increased by trapping process) × cyan multiplication coefficient + (magenta gradation value increased by trapping process) × magenta multiplication coefficient + (yellow increased by trapping process) Gradation value) x yellow multiplication coefficient (11)

  Cyan multiplication coefficient = cyan density calculation coefficient Wc / black density calculation coefficient Wk (12)

  Magenta multiplication coefficient = Magenta density calculation coefficient Wm / Black density calculation coefficient Wk (13)

  Yellow multiplication coefficient = Yellow density calculation coefficient Wy / Black density calculation coefficient Wk (14)

  The multiplication coefficient is a ratio of gradation values of each basic color necessary for reproducing the same density, and is calculated from the density calculation coefficient.

  As an example, when the density calculation coefficient (Wc, Wm, Wy, Wk) is (24, 44, 3, 66), the black tone value of each pixel in the extended region RG3 is calculated by the following equation (15). Is done.

  Black tone value of each pixel in the extension region RG3 = (Black tone value of each pixel in the extension region RG3 before the trapping process) − {(Cyan tone value increased by the trapping process) × 24/66 + ( Magenta tone value increased by trapping process) × 44/66 + (Yellow tone value increased by trapping process) × 3/66} (15)

  (6) Trapping process subroutine

  25 and 26 are subroutines for the trapping process in step S17 shown in FIG.

  Referring to FIG. 25, in the trapping process, CPU 11 reads the gradation value of a specific basic color in each of the extended color and the extended color (S801). Subsequently, the CPU 11 determines whether or not the gradation value of the extended color is larger than the gradation value of the extended color (S803).

  If it is determined in step S803 that the gradation value of the extended color is equal to or smaller than the gradation value of the extended color (NO in S803), the CPU 11 does not perform the trapping process for the basic color (S807). The process proceeds to step S831 in step 26.

  If it is determined in step S803 that the gradation value of the extended color is larger than the gradation value of the extended color (YES in S803), the CPU 11 calculates the difference between the gradation values of the extended color and the extended color ( In step S805, the correction method selected by the correction method selection unit 63 is read (S809). Next, the CPU 11 determines whether or not the correction method is step correction (S811).

  If it is determined in step S811 that the correction method is constant gradation correction (NO in S811), the CPU 11 reads the constant gradation correction calculation coefficient CF1 (S819), and proceeds to the process of step S821 in FIG.

  If it is determined in step S811 that the correction method is step correction (YES in S811), the CPU 11 determines whether or not the extended color is black (S813).

  If it is determined in step S813 that the extended color is black (YES in S813), the black calculation coefficients CF2K, CF3K, and CF4K for staircase correction are read (S815), and the process proceeds to step S821 in FIG.

  If it is determined in step S813 that the extended color is black (YES in S813), the CPU 11 reads the cyan, magenta, and yellow calculation coefficients CF2, CF3, and CF4 for the staircase correction (S817), and FIG. The process proceeds to step S821.

  Referring to FIG. 26, in step S821, the CPU 11 performs a trapping process (S821). Subsequently, the CPU 11 determines whether or not the extended color includes black (S823).

  If it is determined in step S823 that the extended color does not include black (NO in S823), the CPU 11 proceeds to the process of step S831.

  If it is determined in step S823 that the extended color includes black (YES in S823), the CPU 11 calculates an increase amount of each gradation value of cyan, magenta, and yellow in the extended region RG3 (S825). A black tone value adjustment value is calculated (S827). Next, the CPU 11 adjusts the black tone value in the extended region based on the black tone value adjustment value (S829), and proceeds to the process of step S831.

  In step S831, the CPU 11 determines whether the gradation values of all basic colors have been read (S831). If it is determined in step S831 that the gradation values of all the basic colors have been read (YES in S831), the CPU 11 returns. On the other hand, if it is determined in step S831 that the gradation values of all the basic colors have not been read (NO in S831), the CPU 11 proceeds to the process of step S801 in FIG. 25, and in each of the extended color and the extended color. Read the gradation value of the basic color that has not yet been read.

  [Effect of the embodiment]

  In the above-described embodiment, when a color image is formed using a plurality of colors of toner, trapping processing is performed to correct white spots caused by printing misalignment of each basic color. Based on the density values of two objects adjacent to each other, it is determined whether or not white spots are easily noticeable, and the trapping process is performed only when white spots are easily noticeable. As a result, unnecessary trapping processing is eliminated, color change of the object can be reduced, and deterioration of image quality can be suppressed. In addition, since it is determined whether or not the staircase correction is performed based on the gradation values of the two objects, the staircase correction is performed when there is a concern that the color change becomes large. As a result, the two objects are corrected. The correction density can be gradually reduced according to the distance from the adjacent position (edge). As a result, white spots are less noticeable and the color change of the object can be reduced.

  [Others]

  In the above-described embodiment, the content of the trapping process is arbitrary, and the extended color and correction method used for the trapping process may be other than those described above.

  The basic color constituting each pixel may be RGB (red, green, and black), RGB + X (X is an arbitrary color), CMYK + X, or the like in addition to the case of CMYK.

  Only a part of the processes in the above-described embodiments may be selectively executed. For example, in the trapping process determined in step S9 shown in FIG. 2, the boundary portion determined to be a correction target in the trapping process in step S17 shown in FIG. Tone correction may be performed uniformly.

  Further, density values are calculated based on the gradation values of the two objects adjacent to each other, the extended color and the extended color are determined based on the calculated density values, and the gradation values of the two objects are determined. Based on this, either one of the constant gradation correction and the stepped correction may be selected, and the trapping process using the selected correction method may be performed.

  The processing in the above-described embodiment may be performed by software or may be performed using a hardware circuit. It is also possible to provide a program for executing the processing in the above-described embodiment, and record the program on a recording medium such as a CD-ROM, a flexible disk, a hard disk, a ROM, a RAM, or a memory card and provide it to the user. You may decide to do it. The program is executed by a computer such as a CPU. The program may be downloaded to the apparatus via a communication line such as the Internet.

  The above-described embodiment is to be considered as illustrative in all points and not restrictive. The scope of the present invention is defined by the terms of the claims, rather than the description above, and is intended to include any modifications within the scope and meaning equivalent to the terms of the claims.

11 CPU (Central Processing Unit)
13 ROM (Read Only Memory)
15 RAM (Random Access Memory)
DESCRIPTION OF SYMBOLS 17 Auxiliary storage device 19 Network connection part 21 Image processing part 23 Operation panel 25 Image formation part 27 Scanner 51 Boundary part search part 53 Color extraction part 55 Density calculation part 57 Correction object discrimination part 59 Extended color determination part 61 Extended area determination part 63 Correction method selection unit 65 Trapping unit 100 Image forming apparatus AR1 Arrow BP Adjacent position DR1, DR2, DR3 Direction IM1 Input image IM101, IM102 Image OB1 to OB6 Object OR Overlap area PO1 to PO3 Position in main scanning direction RG1, RG1A, RG1B , RG1C, RG1D, RG1E border RG2A, RG2B, RG101 area RG3 extended area TC, TK, TM, TY toner

Claims (21)

An image processing apparatus that performs a trapping process on an image including first and second objects having different colors,
Boundary part searching means for searching for a boundary part that is an area including adjacent positions where the first and second objects are adjacent to each other;
A density value of the first object is calculated based on a gradation value of each basic color constituting the first object existing in the boundary portion, and the second object existing in the boundary portion is configured. Density calculating means for calculating the density value of the second object based on the gradation value of each basic color;
Correction target determination means for determining whether or not the boundary portion is to be corrected based on the density values of the first and second objects;
A trapping unit that performs a trapping process on at least a part of the boundary when it is determined that the correction target is determined by the correction target determination unit;
The correction target determining unit determines that the boundary portion is not a correction target when at least one of the density values of the first and second objects is equal to or less than a first threshold value, and When both the density values of the first and second objects are larger than the first threshold, it is determined that the boundary portion is a correction target;
An image processing apparatus in which the trapping unit does not perform a trapping process when the correction target determining unit determines that the correction target is not to be corrected. Based on the density values of the first and second objects, the color of the first object existing in the boundary portion and the boundary portion are determined based on the density values of the first and second objects. Extended color determining means for determining one of the colors of the second object existing as an extended color and determining the other as an extended color;
The image processing apparatus according to claim 1, wherein the trapping unit performs a trapping process for extending at least one basic color constituting the extended color to the area of the extended color. An image processing apparatus that performs a trapping process on an image including first and second objects having different colors,
Boundary part searching means for searching for a boundary part that is an area including adjacent positions where the first and second objects are adjacent to each other;
A density value of the first object is calculated based on a gradation value of each basic color constituting the first object existing in the boundary portion, and the second object existing in the boundary portion is configured. Density calculating means for calculating the density value of the second object based on the gradation value of each basic color;
Correction target determination means for determining whether or not the boundary portion is to be corrected based on the density values of the first and second objects;
A trapping unit that performs a trapping process on at least a part of the boundary when it is determined that the correction target is determined by the correction target determination unit;
When the correction target determination unit determines that the correction target is not to be corrected, the trapping unit does not perform the trapping process,
Based on the density values of the first and second objects, the color of the first object existing in the boundary portion and the boundary portion are determined based on the density values of the first and second objects. Extended color determining means for determining one of the colors of the second object existing as an extended color and determining the other as an extended color;
The trapping means performs a trapping process for extending at least one basic color constituting the extended color into the extended color area;
Extension area determination that is an extension area provided in a direction from the adjacent position toward the extended color, and that determines an extended area where at least one basic color constituting the extended color and the extended color overlap. Means,
When it is determined that the correction target is determined as the correction target by the correction target determination unit, as the correction method for each basic color, the gradation value of the first object existing in the boundary portion and the second value existing in the boundary portion are used. based on the gradation value of the object, further comprising a correction method selecting means for selecting one of the methods of constant tone correction and stepped correction,
The constant gradation correction is a correction method for adding a constant gradation value to the gradation value of the entire extended region,
The stepped correction is a correction method of adding the tone value that becomes smaller stepwise in accordance with the distance from the adjacent positions to the tone value of the extended area, images processing device. For each basic color, the correction method selection means is the smaller one of the gradation value of the first object existing at the boundary and the gradation value of the second object existing at the boundary. The constant gradation correction is selected when the gradation value is equal to or smaller than a third threshold value, and the stepwise correction is selected when the smaller gradation value exceeds the third threshold value. The image processing apparatus according to claim 3 . When the basic color constituting the extended color includes a basic color having a gradation value smaller than the gradation value of the basic color constituting the extended color, the trapping means not perform trapping processing, the image processing apparatus according to claim 3 or 4. When the constant gradation correction is selected by the correction method selection means, the trapping means
The image processing apparatus according to claim 5 , wherein a gradation value corresponding to a value obtained by subtracting the gradation value of the extended color from the gradation value of the extended color is added to the gradation value of the entire extended area. When the correction method selection unit selects the stepped correction, the trapping unit, for the basic color, subtracts the gradation value of the extended color from the gradation value of the extended color, and the adjacent color the tone value corresponding to a value obtained by multiplying the second coefficient that decreases with the distance from the position, is added to the tone value of the extended area, the image processing apparatus according to claim 5 or 6. The image processing apparatus according to claim 7 , wherein the second coefficient used when the basic color is black is smaller than the second coefficient used when the basic color is other than black. An image processing apparatus that performs a trapping process on an image including first and second objects having different colors,
Boundary part searching means for searching for a boundary part that is an area including adjacent positions where the first and second objects are adjacent to each other;
A density value of the first object is calculated based on a gradation value of each basic color constituting the first object existing in the boundary portion, and the second object existing in the boundary portion is configured. Density calculating means for calculating the density value of the second object based on the gradation value of each basic color;
Correction target determination means for determining whether or not the boundary portion is to be corrected based on the density values of the first and second objects;
A trapping unit that performs a trapping process on at least a part of the boundary when it is determined that the correction target is determined by the correction target determination unit;
When the correction target determination unit determines that the correction target is not to be corrected, the trapping unit does not perform the trapping process,
Based on the density values of the first and second objects, the color of the first object existing in the boundary portion and the boundary portion are determined based on the density values of the first and second objects. Extended color determining means for determining one of the colors of the second object existing as an extended color and determining the other as an extended color;
The trapping means performs a trapping process for extending at least one basic color constituting the extended color into the extended color area;
Extension area determination that is an extension area provided in a direction from the adjacent position toward the extended color, and that determines an extended area where at least one basic color constituting the extended color and the extended color overlap. Further comprising means,
Said trapping means, said depending on the amount of the gradation values of the base color other than black is added to the extended area, reduce the tone value of black in the extended region, images processing device. The extended color determining means determines the color of an object having a lower density value among the density values of the first and second objects as the extended color, and determines the color of the object having a higher density value as the color of the object. The image processing device according to claim 2, wherein the image processing device is determined as an extended color. Extension area determination that is an extension area provided in a direction from the adjacent position toward the extended color, and that determines an extended area where at least one basic color constituting the extended color and the extended color overlap. The image processing apparatus according to claim 2 , further comprising means. The concentration calculating means includes
Multiplying the gradation value of each basic color constituting the first object existing in the boundary by the first coefficient determined for each basic color, and adding all the multiplication values First density calculating means for calculating the density value of the first object;
A result obtained by multiplying the gradation value of each basic color constituting the second object existing in the boundary by the first coefficient determined for each basic color, and adding all the multiplication values. and a second concentration calculating means for calculating a density value of the second object, an image processing apparatus according to any one of claims 1 to 11. The boundary search means, when scanning the image in an arbitrary direction, sets the boundary as a position where the change amount of the gradation value of each basic color exceeds a second threshold as the adjacent position. extraction is, the image processing apparatus according to any one of claims 1 to 12. Color extraction for extracting the gradation value of each basic color constituting the first object existing in the boundary portion and the gradation value of each basic color constituting the second object existing in the boundary portion further comprising means, image processing apparatus according to any one of claims 1 to 13. The color extracting means includes an average value of gradation values of basic colors constituting an area of a certain size in the first object existing in the boundary portion, and the second object existing in the boundary portion. The image processing apparatus according to claim 14 , wherein an average value of gradation values of each basic color constituting an area of a certain size is extracted. An image processing apparatus for processing an image including first and second objects having different colors,
Boundary search means for extracting a boundary that is an area including adjacent positions where the first and second objects are adjacent to each other;
A density value of the first object is calculated based on a gradation value of each basic color constituting the first object existing in the boundary portion, and the second object existing in the boundary portion is configured. Density calculating means for calculating the density value of the second object based on the gradation value of each basic color;
Based on the density values of the first and second objects, one of the color of the first object existing at the boundary and the color of the second object existing at the boundary is set as an extended color. Extended color determining means for determining and determining the other as the extended color;
Extension area determination that is an extension area provided in a direction from the adjacent position toward the extended color, and that determines an extended area where at least one basic color constituting the extended color and the extended color overlap. Means,
As a correction method for each basic color, a constant gradation correction and a gradation value of the first object existing in the boundary part and a gradation value of the second object existing in the boundary part are performed. Correction method selection means for selecting any one of the staircase corrections;
Trapping means for performing trapping processing,
When there is a basic color having a gradation value smaller than the gradation value of each basic color constituting the extended color among the basic colors constituting the extended color, the trapping means Without trapping for
When the constant gradation correction is selected by the correction method selection unit, the trapping unit calculates a gradation value corresponding to a value obtained by subtracting the gradation value of the extended color from the gradation value of the extended color. In addition to the gradation value of the entire extended area,
When the correction method selection unit selects the stepped correction, the trapping unit, for the basic color, subtracts the gradation value of the extended color from the gradation value of the extended color, and the adjacent color An image processing apparatus that adds a gradation value corresponding to a value obtained by multiplying a coefficient that decreases in accordance with a distance from a position to a gradation value of the extension area. A control method for an image processing apparatus that performs a trapping process on an image including first and second objects having different colors,
A boundary search step for searching for a boundary that is an area including adjacent positions where the first and second objects are adjacent to each other;
A density value of the first object is calculated based on a gradation value of each basic color constituting the first object existing in the boundary portion, and the second object existing in the boundary portion is configured. A density calculating step for calculating a density value of the second object based on a gradation value of each basic color;
A correction target determining step for determining whether or not the boundary portion is to be corrected based on the density values of the first and second objects;
A trapping step for performing a trapping process on at least a part of the boundary when it is determined that the correction target is determined in the correction target determination step;
In the correction target determination step, when at least one of the density values of the first and second objects is equal to or less than a first threshold, it is determined that the boundary portion is not a correction target, and the first When both the density values of the first and second objects are larger than the first threshold, it is determined that the boundary portion is a correction target;
A control method for an image processing apparatus, wherein a trapping process is not performed in the trapping step when it is determined that the correction target is not a correction target in the correction target determination step. A control method for an image processing apparatus that performs a trapping process on an image including first and second objects having different colors,
A boundary search step for searching for a boundary that is an area including adjacent positions where the first and second objects are adjacent to each other;
A density value of the first object is calculated based on a gradation value of each basic color constituting the first object existing in the boundary portion, and the second object existing in the boundary portion is configured. A density calculating step for calculating a density value of the second object based on a gradation value of each basic color;
A correction target determining step for determining whether or not the boundary portion is to be corrected based on the density values of the first and second objects;
A trapping step for performing a trapping process on at least a part of the boundary when it is determined that the correction target is determined in the correction target determination step;
When it is determined that the correction target is not a correction target in the correction target determination step, the trapping process is not performed in the trapping step,
When it is determined that the correction target is determined in the correction target determination step, based on the density values of the first and second objects, the color of the first object existing in the boundary and the boundary An extended color determining step of determining one of the colors of the second object existing as an extended color and determining the other as an extended color;
In the trapping step, a trapping process for extending at least one basic color constituting the extended color to the area of the extended color is performed,
Extension area determination that is an extension area provided in a direction from the adjacent position toward the extended color, and that determines an extended area where at least one basic color constituting the extended color and the extended color overlap. Steps,
When it is determined that the correction target is determined in the correction target determination step, as the correction method for each basic color, the gradation value of the first object existing in the boundary portion and the second value existing in the boundary portion are used. A correction method selection step of selecting one of a constant gradation correction and a stepped correction based on the gradation value of the object of
The constant gradation correction is a correction method for adding a constant gradation value to the gradation value of the entire extended region,
The stepwise correction is a control method for an image processing apparatus, which is a correction method for adding a gradation value that decreases in a stepped manner according to a distance from the adjacent position to a gradation value of the extension region. A control method for an image processing apparatus that performs a trapping process on an image including first and second objects having different colors,
A boundary search step for searching for a boundary that is an area including adjacent positions where the first and second objects are adjacent to each other;
A density value of the first object is calculated based on a gradation value of each basic color constituting the first object existing in the boundary portion, and the second object existing in the boundary portion is configured. A density calculating step for calculating a density value of the second object based on a gradation value of each basic color;
A correction target determining step for determining whether or not the boundary portion is to be corrected based on the density values of the first and second objects;
A trapping step for performing a trapping process on at least a part of the boundary when it is determined that the correction target is determined in the correction target determination step;
When it is determined that the correction target is not a correction target in the correction target determination step, the trapping process is not performed in the trapping step,
When it is determined that the correction target is determined in the correction target determination step, based on the density values of the first and second objects, the color of the first object existing in the boundary and the boundary An extended color determining step of determining one of the colors of the second object existing as an extended color and determining the other as an extended color;
In the trapping step, a trapping process for extending at least one basic color constituting the extended color to the area of the extended color is performed,
Extension area determination that is an extension area provided in a direction from the adjacent position toward the extended color, and that determines an extended area where at least one basic color constituting the extended color and the extended color overlap. Further comprising steps,
A control method for an image processing apparatus, wherein, in the trapping step, a black tone value in the extension region is reduced according to an amount of a tone value of a basic color other than black added to the extension region. A control method for an image processing apparatus for processing an image including first and second objects having different colors,
A boundary search step for extracting a boundary that is an area including adjacent positions where the first and second objects are adjacent to each other;
A density value of the first object is calculated based on a gradation value of each basic color constituting the first object existing in the boundary portion, and the second object existing in the boundary portion is configured. A density calculating step for calculating a density value of the second object based on a gradation value of each basic color;
Based on the density values of the first and second objects, one of the color of the first object existing at the boundary and the color of the second object existing at the boundary is set as an extended color. An extended color determining step for determining and determining the other as an extended color;
Extension area determination that is an extension area provided in a direction from the adjacent position toward the extended color, and that determines an extended area where at least one basic color constituting the extended color and the extended color overlap. Steps,
As a correction method for each basic color, a constant gradation correction and a gradation value of the first object existing in the boundary part and a gradation value of the second object existing in the boundary part are performed. A correction method selection step for selecting one of the staircase corrections;
A trapping step for performing a trapping process,
When a basic color having a gradation value smaller than the gradation value of each basic color constituting the extended color exists among the basic colors constituting the extended color, in the trapping step, the basic color Without trapping for
When the constant gradation correction is selected in the correction method selection step, a gradation value corresponding to a value obtained by subtracting the gradation value of the extended color from the gradation value of the extended color is selected in the trapping step. In addition to the gradation value of the entire extended area,
When the stepped correction is selected in the correction method selection step, in the trapping step, for the basic color, a value obtained by subtracting the gradation value of the extended color from the gradation value of the extended color, and the adjacent color A control method for an image processing apparatus, wherein a gradation value corresponding to a value obtained by multiplying a coefficient that decreases in accordance with a distance from a position is added to a gradation value of the extension area. An image processing apparatus control program for executing the image processing apparatus control method according to any one of claims 17 to 20 .

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