JP5122507B2 - Image processing apparatus, image forming apparatus, image processing method, program, and recording medium - Google Patents

Description

  The present invention relates to an image forming apparatus having a normal mode in which an image is printed using a color material, and a saving mode (save mode) in which the printing is performed while suppressing consumption of the color material as compared with the normal mode. The present invention relates to an image processing apparatus that processes image data handled by the apparatus.

  A printing system that prints an image of a document read by a scanner or the like or a document image created by a computer application such as document creation software has a normal print mode and a save mode, and the pixels are uniformly set in the save mode. It is known that the amount of color material (toner) used in printing can be saved more than in the normal mode. And, by saving the amount of color material used, the advantages of cost reduction and environmental protection promotion can be obtained.

  However, according to the method of thinning out pixels uniformly, there is a problem in that small characters and lines are interrupted and the legibility of small characters and lines is lowered. Also, according to this method, there is a problem that a large amount of text and solid portions leave room for further reduction in the amount of color material used, and the color material consumption cannot be sufficiently suppressed. And the following patent document 1 exists with respect to these problems.

  Japanese Patent Application Laid-Open No. 2004-151561 discloses a method of changing a dot pattern of an input image by a staggered lattice or a dither matrix when a printing material saving mode is instructed by a user. Further, Japanese Patent Laid-Open No. 2004-228561 shows that the presence / absence of pattern change is set according to the type of input image data. More specifically, in Patent Document 1, the presence / absence of pattern change is switched according to the image type such as a small character, a large character, an edge, a halftone dot, or line data.

Japanese Patent Laid-Open No. 7-314783 (released on December 05, 1995)

  According to the method of Patent Document 1, since the presence / absence of change of the dot pattern is switched according to the type of element constituting the image, it is necessary to accurately determine the type of element constituting the image. In this regard, there are few misjudgments with regard to discrimination between characters and photographic paper photographs, discrimination between characters and halftone dots, and the like. However, according to the method of Patent Document 1, since a staggered pattern is used for large characters and pattern change is not performed for small characters, large characters and small characters are accurately discriminated. There is a need. However, it is not uncommon for an erroneous determination to occur when determining a large character and a small character, and the time required for the determination process also increases.

  Here, when an error occurs in discrimination between a large character and a small character, a pattern change is not performed on the large character. As a result, the toner consumption cannot be reduced sufficiently for large characters. Therefore, it is not sufficient to use the technique of Patent Document 1 in order to obtain a sufficient toner consumption suppressing effect while maintaining the legibility of characters.

The present invention has been made in view of the above problems, and is provided with an image forming apparatus capable of sufficiently obtaining a color material consumption suppression effect while maintaining the legibility of characters, and the image forming apparatus. An image processing apparatus is provided.

  In order to solve the above problems, the present invention provides a normal mode for printing an image of image data using a color material, and a save mode for printing the image while suppressing the amount of color material used compared to the normal mode. An image processing apparatus that processes image data handled in an image forming apparatus having the image data, wherein the amount of the color material used in the save mode is smaller than that in the normal mode. A color material amount suppression unit that performs image processing; and when the image of the image data includes a solid part, the color material amount suppression unit moves the density of the part inward from the contour of the part It is characterized by being lowered step by step. According to the configuration of the present invention, when the image to be processed includes a solid portion such as a bold character (a thick character of a line), the density gradually decreases from the contour of the portion toward the inside of the contour. In this way, image processing is performed. Therefore, the density of the entire bold character can be reduced without impairing the shape of the outline of the bold character, so that the color material consumption can be sufficiently suppressed while maintaining the legibility of the bold character. .

  In the image processing apparatus of the present invention, in addition to the above configuration, the image data is data including a pixel value indicating a pixel density, and the pixel value is set so that the value decreases as the density decreases. The color material amount suppression unit weights the pixel values of each pixel in a block including a plurality of pixels including the target pixel using a weighting filter, and is a sum of the weighted pixel values. A pixel value that decreases in density as the product-sum value decreases is output as the pixel value of the target pixel, and the block surrounds the first region including the target pixel and the first region. And a second region that is a region including pixels adjacent to the pixels on the outer periphery of the block, and the weighting filter is a weight applied to a pixel value of each pixel in the block Person in charge The weighting coefficient applied to the pixel value of each pixel in the second area is a value less than or equal to zero, and the weighting coefficient applied to the pixel value of the pixel included in the first area and the second area The sum may be set to be zero or substantially zero. Further, in the image processing apparatus of the present invention, in addition to the above configuration, the image data is data including a pixel value indicating a pixel density, and the pixel value is set so that the value becomes larger as the density is lower. The color material amount suppression unit weights the pixel values of each pixel in a block including a plurality of pixels including the target pixel using a weighting filter, and is a sum of the weighted pixel values. A pixel value that decreases in density as the product-sum value decreases is output as the pixel value of the target pixel, and the block surrounds the first region including the target pixel and the first region. And a second region that is a region including pixels adjacent to the pixels on the outer periphery of the block, and the weighting filter is a weight applied to a pixel value of each pixel in the block The weighting coefficient applied to the pixel value of each pixel in the second area is a value greater than or equal to zero, and the weighting coefficient applied to the pixel value of the pixels included in the first area and the second area May be set to be zero or substantially zero.

  In the image processing apparatus according to the aspect of the invention, in addition to the configuration, the color material amount suppression unit may determine whether the color of the reference pixel other than the target pixel in the block is similar to the color of the target pixel. A similarity determination unit that determines a pixel value of a reference pixel having a color determined to be dissimilar to the color of the target pixel, and converts the pixel value to a pixel value indicating a minimum density. It is preferable to perform the weighting. According to the present invention, there is an effect that it is possible to avoid the disadvantage that a color that does not exist in the image before processing is generated.

In addition, since the character region and the graphic frequently include a solid portion, the processing by the weighting filter has an advantage that the toner consumption can be reduced while the legibility is maintained. On the other hand, a photographic region rarely includes the solid portion, and when the processing by the weighting filter is performed, the adverse effect of image quality deterioration is often greater than the merits. Therefore, in addition to the above configuration, the image processing apparatus of the present invention includes a determination processing unit that determines whether each image area included in the image of the image data corresponds to a character area, a graphic area, or a photographic area. And the color material amount suppression unit performs processing using the weighting filter on the image region determined as the character region or the graphic region by the determination processing unit, and determines the photographic region as the determination processing unit. A configuration in which the processing using the weighting filter is not performed on the image region that has been performed may be employed. Thereby, it is possible to suppress deterioration in image quality for a photographic region. Note that, for a photo area, if processing is performed using a filter in which a weighting coefficient is set so that the luminance increases substantially uniformly over the entire area, toner consumption is not caused in the photo area. An amount suppressing effect can be obtained.

  Further, since the character region frequently includes a solid portion, the processing by the weighting filter has an advantage that the toner consumption can be reduced while the legibility is maintained. On the other hand, the halftone dot region and the continuous tone region rarely include the solid portion, and when the processing by the weighting filter is performed, the adverse effect of the image quality deterioration is often larger than the merit. Therefore, in addition to the above configuration, the image processing apparatus of the present invention determines whether each image area included in the image of the image data corresponds to a character area, a dot area, or a continuous tone area. A processing unit, and the color material amount suppression unit performs processing using the weighting filter on the image region determined as the character region by the determination processing unit, and the determination processing unit performs a halftone region or A configuration in which processing using the weighting filter is not performed on an image region determined to be a continuous tone region may be employed. As a result, it is possible to suppress image quality deterioration in the halftone area or continuous tone area. Note that for a halftone dot area or continuous tone area, if processing is performed using a filter in which a weighting coefficient is set so that the luminance increases substantially uniformly throughout the whole area, the halftone dot area or continuous gradation area is obtained. The toner consumption amount suppressing effect can be obtained without causing a sense of incongruity in the tone area.

In the image processing apparatus of the present invention, in addition to the above configuration, the image data is data including a pixel value indicating a pixel density, and the pixel value is set so that the value decreases as the density decreases. The color material amount suppression unit includes a small region processing unit that weights the pixel value of each pixel in a small region including a plurality of pixels including the target pixel, and includes the small region and the small region. A large area processing unit that weights the pixel values of each pixel in the large area having a larger number of pixels, and a first product sum value that is the sum of the pixel values weighted by the small area processing unit A pixel value output unit that outputs a pixel value having a lower density as a pixel value of the pixel of interest as a difference value obtained by subtracting a second product sum value that is a sum of pixel values weighted by the large region processing unit is smaller; And the small region processing unit belongs to the small region. Weighting is performed using a small region filter that defines each weighting factor to be applied to the pixel value of each pixel, and the large region processing unit is a large region that defines each weighting factor to be applied to the pixel value of each pixel belonging to the large region Weighting is performed using a filter, and in the small area filter and the large area filter, the sum of the weighting coefficients of the small area filter and the sum of the weighting coefficients of the large area filter are equal or substantially equal. It may be set as follows. Further, in the image processing apparatus of the present invention, in addition to the above configuration, the image data is data including a pixel value indicating a pixel density, and the pixel value is set so that the value becomes larger as the density is lower. The color material amount suppression unit includes a small region processing unit that weights the pixel value of each pixel in a small region including a plurality of pixels including the target pixel, and includes the small region and the small region. A large area processing unit that weights the pixel values of each pixel in the large area having a larger number of pixels, and a second product sum value that is the sum of the pixel values weighted by the large area processing unit. A pixel value output unit for outputting a pixel value having a lower density as the pixel value of the target pixel as the difference value obtained by subtracting the first product sum value that is the sum of the pixel values weighted by the small region processing unit is smaller; And the small region processing unit belongs to the small region. Weighting is performed using a small area filter that defines a weighting coefficient to be applied to the pixel value of each pixel, and the large area processing unit determines a weighting coefficient to be applied to the pixel value of each pixel belonging to the large area. Weighting is performed using an area filter, and in the small area filter and the large area filter, the sum of the weighting coefficients of the small area filter and the sum of the weighting coefficients of the large area filter are equal or substantially equal. Is set to be According to the above configuration, when a solid part is included in the image of the image data, the density of the solid part can be decreased stepwise as it goes inward from the outline of the solid part.

  Furthermore, in the image processing apparatus according to the aspect of the invention, in addition to the above configuration, the color material amount suppression unit may have similar colors of reference pixels other than the target pixel in the small region and the large region and the color of the target pixel. A similarity determination unit for determining whether or not the large region processing unit and the small region processing unit, the pixel value of the reference pixel having a color determined to be dissimilar to the color of the target pixel, It is preferable that the pixel value indicating the minimum density is converted, and the weighting is performed using the converted pixel value. According to the present invention, there is an effect that it is possible to avoid the disadvantage that a color that does not exist in the image before processing is generated.

  In addition, since the character region and the graphic frequently include a solid portion, when the processing by the weighting filter is performed, there is a merit that the toner consumption is suppressed while the legibility is maintained. On the other hand, a photographic region rarely includes the solid portion, and when the processing by the weighting filter is performed, the adverse effect of image quality deterioration is often greater than the merits. Therefore, in addition to the above configuration, the image processing apparatus of the present invention includes a determination processing unit that determines whether each image area included in the image of the image data corresponds to a character area, a graphic area, or a photographic area. And the color material amount suppression unit performs processing using the small region filter and the large region filter on the image region determined as the character region or the graphic region by the determination processing unit, and performs the determination processing. The image region determined to be a photographic region by the unit may not be processed using the small region filter and the large region filter. Thereby, it is possible to suppress deterioration in image quality for a photographic region. Note that, for a photo area, if processing is performed using a filter in which a weighting coefficient is set so that the luminance increases substantially uniformly over the entire area, toner consumption is not caused in the photo area. An amount suppressing effect can be obtained.

  Furthermore, since the character region frequently includes a solid portion, the processing by the weighting filter has a merit that the toner consumption is suppressed while the legibility is maintained. On the other hand, the halftone dot region and the continuous tone region rarely include the solid portion, and when the processing by the weighting filter is performed, the adverse effect of the image quality deterioration is often larger than the merit. Therefore, in addition to the above configuration, the image processing apparatus of the present invention determines whether each image area included in the image of the image data corresponds to a character area, a dot area, or a continuous tone area. A processing unit, and the color material amount suppression unit performs processing using the small region filter and the large region filter on the image region determined as the character region by the determination processing unit, and performs the determination processing. The image area determined to be a halftone dot area or a continuous tone area by the section may not be processed using the small area filter and the large area filter. As a result, it is possible to suppress image quality deterioration in the halftone area or continuous tone area. Note that for a halftone dot area or continuous tone area, if processing is performed using a filter in which a weighting coefficient is set so that the luminance increases substantially uniformly throughout the whole area, the halftone dot area or continuous gradation area is obtained. The toner consumption amount suppressing effect can be obtained without causing a sense of incongruity in the tone area.

The image processing apparatus of the present invention includes a normal mode for printing an image of image data using a color material, and a save mode for printing the image while suppressing the amount of the color material used compared to the normal mode. The image forming apparatus may be provided. Furthermore, the present invention provides an image forming apparatus having a normal mode for printing an image of image data using a color material, and a save mode for printing the image while suppressing the amount of the color material used compared to the normal mode. An image processing method for processing image data to be handled, the color material performing image processing on the image data in the save mode so that a use amount of the color material is suppressed as compared with the normal mode An amount suppressing step, and when the solid portion is included in the image of the image data, the color material amount suppressing step gradually decreases the density of the portion inward from the contour of the portion. It is a process.

  Furthermore, the image processing apparatus may be realized by a computer. In this case, a program that causes the computer to function as each unit of the image processing apparatus, and a computer-readable recording medium that records the program are also provided in the present invention. It falls into the category of the invention.

  According to the configuration of the present invention, when the image to be processed includes a solid part such as a bold character, the image processing is performed so that the density gradually decreases from the outline of the part toward the inside of the outline. Done. Therefore, the density of the entire bold character can be reduced without impairing the shape of the outline of the bold character, so that the color material consumption can be sufficiently suppressed while maintaining the legibility of the bold character. .

1 is a block diagram illustrating a schematic configuration of a printing system having an image processing apparatus according to an embodiment of the present invention. It is the block diagram which showed the example of an internal structure of the color material amount suppression part shown by FIG. 2 is a flowchart showing a flow of processing of a color material amount suppression unit shown in FIG. 1. It is the figure which showed an example of the large area filter used in one Embodiment of this invention, and an example of a small area filter. (A) is a figure which shows the image printed when a certain image data is processed in normal mode. (B) is a diagram showing an image to be printed when the image data is processed in the save mode. (A) is the figure which showed the condition where the whole area of a small area filter and the whole area of a large area filter are both facing the black solid area | region. (B) is the figure which showed the condition where the whole area | region of the small area | region filter has opposed the black solid area | region, while the large area filter has opposed the black solid area | region and the white solid area | region. (C) is the figure which showed the condition where the whole area | region of the small area | region filter has opposed the white solid area | region, while the large area filter has opposed the black solid area | region and the white solid area | region. (D) is the figure which showed the condition where the whole area of a large area filter and the whole area of a small area filter are facing the white solid area | region. It is the block diagram which showed the example of an internal structure of the color material amount suppression part which concerns on the 2nd Embodiment of this invention. It is the flowchart which showed the flow of the process of the color material amount suppression part which concerns on the 2nd Embodiment of this invention. (A) is a figure which shows the image in which the black character is formed on the red base area | region. (B) is a figure which shows the image after a process at the time of performing the process by a color material amount suppression part with respect to the image of (a), without performing the similarity determination process which concerns on the 3rd Embodiment of this invention. . (C) is a figure which shows the image after a process at the time of performing the process by a color material amount suppression part with respect to the image of (a) using the result of the said similarity determination process. It is the figure which showed an example of the 1st weighting filter used in the 2nd Embodiment of this invention, and an example of a 2nd weighting filter. It is a figure which shows the large region filter and small region filter for color channels with low resolution. It is the figure which showed the high brightness filter. 1 is a block diagram illustrating a multifunction machine having an image processing apparatus to which a color material amount suppression unit according to an embodiment of the present invention is applied. 1 is a block diagram illustrating a color printer having an image processing apparatus to which a color material amount suppression unit of an embodiment of the present invention is applied, and a terminal device connected to the color printer. (A) is the figure which showed the example of the image produced with the terminal device of FIG. (B) is a diagram showing an example of raster data corresponding to the image of (a). It is the figure which showed the example of the structure of PDL data. (A) is the figure which expanded and showed the outline part of the black character in the image containing a black character and a white base area | region, Comprising: It is the figure which showed the state before performing the process by a color material amount suppression part. (B) is the figure which showed the part same as the outline part of the black character of (a), Comprising: It is the figure which showed the state after the process by a color material amount suppression part was performed. (C) is a table | surface which shows each value calculated when a color material amount suppression part processes with respect to the image data of a subtractive color mixture. (D) is a table | surface which shows each value calculated when a color material amount suppression part processes with respect to the image data of an additive color mixture. It is a figure which shows the brightening filter different from the brightening filter of FIG.

[Embodiment 1]
An image processing apparatus according to an embodiment of the present invention will be described below with reference to the drawings. FIG. 1 is a block diagram showing a schematic configuration of a printing system having an image processing apparatus according to the present embodiment.

  The printing system 1 in FIG. 1 includes an image processing apparatus 10 and a printing unit 20. The image processing apparatus 10 is an apparatus that performs image processing on input image data and transmits the image data after the image processing to the printing unit 20. The printing unit 20 is an electrophotographic printing engine that prints an image of image data sent from the image processing apparatus 10 on a sheet. That is, the image processing apparatus 10 performs image processing on image data used for printing processing.

  The printing system 1 according to the present embodiment includes a normal mode in which an image of image data is printed using toner (coloring material), and a save mode (in which the printing is performed while suppressing toner consumption compared to the normal mode). Saving mode). In the printing system 1, switching between the normal mode and the save mode is performed in accordance with a command input from the user.

  When the image data input to the printing system 1 is PDL (page description language) format data created by an external terminal, a command statement specifying the normal mode or the save mode is described in the data, and printing is performed. The system 1 may be adapted to switch between the normal mode and the save mode in accordance with this command statement. That is, in this case, when the user inputs a command to the external terminal, the command statement is described in the image data in the PDL format created by the external terminal. Then, the image data is transmitted from the external terminal to the printing system 1, and the printing system 1 switches between the normal mode and the save mode according to the command statement described in the image data.

  As illustrated in FIG. 1, the image processing apparatus 10 includes a preprocessing unit 11, a color material amount suppression unit 12, and a postprocessing unit 13.

The pre-processing unit 11 is a block that performs pre-processing necessary for executing the processing of the post-processing unit 13 on the input image data. More specifically, the preprocessing unit 11 performs so-called shading correction and region separation processing when the input image data is image data read by a scanner (in the case of copying processing). Further, when the input image data is image data in the PDL format, the preprocessing unit 11 converts the image data in the PDL format into image data that can be handled by the post-processing unit 13 (an image indicating a pixel value for each pixel). Data) (image development processing)
I do.

  In the normal mode, the color material amount suppression unit 12 does not process the image data sent from the preprocessing unit 11 and transmits the image data to the postprocessing unit 13 as it is. On the other hand, the color material amount suppression unit 12 performs image processing on the image data so that the toner consumption amount in the printing unit 20 is suppressed more in the save mode than in the normal mode. Then, the color material amount suppression unit 12 sends the image data after the image processing to the post-processing unit 13. The color material amount suppression unit 12 will be described in detail later.

  The post-processing unit 13 is a block that performs image processing necessary for performing print processing on the image data sent from the color material amount suppressing unit 12. More specifically, the post-processing unit 13 performs gamma correction (output tone correction), halftone processing (for example, dither processing), and the like.

  Further, when the image data sent from the color material amount suppression unit 12 is RGB image data, the post-processing unit 13 performs processing to convert the RGB image data into CMYK image data, and further, this CMYK. The image data is subjected to halftone processing and the like, and the image data is sent to the printing unit 20. On the other hand, when the image data sent from the color material amount suppression unit 12 is CMYK image data, the post-processing unit 13 performs halftone processing on the CMYK image data and prints the image data. It is to be sent to the part 20. In other words, RGB image data may be input to the image processing apparatus 10 or CMYK image data may be input. In either case, CMYK image data is finally output. It has become so. Note that R means red, G means green, B means blue, C means cyan, M means magenta, Y means yellow, and K means black.

  Hereinafter, RGB image data is referred to as additive color image data, and CMYK image data is referred to as subtractive color image data. In this specification, image data is data including pixel values indicating the density of each pixel. The pixel value of the additive color mixture image data is set so that the value increases as the pixel density decreases. For example, in 8-bit additive color image data, a pixel value of 0 indicates the highest density (black), and a pixel value of 255 indicates the lowest density (white). On the other hand, the pixel value of the subtractive color image data is set so that the value decreases as the pixel density decreases. For example, in 8-bit subtractive color image data, a pixel value of 0 indicates a minimum density (white) and a pixel value of 255 indicates a maximum density (black).

  Although not shown in FIG. 1, the image processing apparatus 10 includes a memory in which image data is expanded and a control device (CPU: Central Processing Unit) that controls each unit in the apparatus. . The control device also controls transfer of image data between each unit in the apparatus and the memory.

  Next, the color material amount suppression unit 12 will be described in detail. FIG. 2 is a block diagram showing an example of the internal configuration of the color material amount suppression unit 12 shown in FIG. As shown in FIG. 2, the color material amount suppression unit 12 includes a large region processing unit 31, a small region processing unit 32, a difference calculation unit 33, an adjustment calculation unit 34, and a pixel value output unit (pixel value processing unit) 35. Have.

The large area processing unit 31 has a position corresponding to each pixel in an area composed of M × M pixels (M: an integer equal to or larger than 2) including the target pixel, and a weighting coefficient is set at each position ( Window), the product sum value Rm (second product sum value) of the pixel values of each pixel in the region is calculated. The product sum value Rm is obtained by the following [Equation 1]. K _ij in [ _Equation 1] indicates a weighting coefficient at the position of the i-th row and the j-th column in the large region filter, and I _{ij in} [ _Equation 1] is at the position of the i-th row and the j-th column in the large region filter. The pixel value of the corresponding pixel is shown.

In other words, the product-sum value Rm weights the pixel value by multiplying the pixel value and the weighting coefficient for each pixel in the region composed of M × M pixels, and sums the weighted pixel values (total amount). , Cumulative).

  In the present embodiment, the large area processing unit 31 obtains the product sum value Rm using the large area filter 51 shown in FIG. As shown in FIG. 4, the large area filter 51 corresponds to a size of 7 × 7 pixels, and the values shown at the respective positions in the large area filter 51 indicate weighting coefficients. In the large area filter 51, the center position (position where the weighting coefficient is 49) is a position corresponding to the target pixel.

The small region processing unit 32 has each position corresponding to each pixel in a region composed of N × N pixels (N: 1 or more and an integer smaller than M) including the target pixel, and a small weight coefficient is set at each position. This is a block for calculating a product sum value Rn (first product sum value) of pixel values of each pixel in the region using a region filter (window). The product-sum value Rn is obtained by the following formula 2. K _ij in [ _Expression 2] indicates a weighting coefficient at the position of the i-th row and j-th column in the small region filter, and I _{ij in} [ _Expression 2] is at the position of the i-th row and j-th column in the small region filter. The pixel value of the corresponding pixel is shown.

In other words, the product-sum value Rn is obtained by weighting the pixel value by multiplying the pixel value and the weighting coefficient for each pixel in the area composed of N × N pixels, and summing the weighted pixel values (total amount). , Cumulative).

  In the present embodiment, the small region processing unit 32 obtains the product sum value Rn using the small region filter 52 shown in FIG. As shown in FIG. 4, the small area filter 52 corresponds to a size of 3 × 3 pixels, and the values shown at each position in the small area filter 52 indicate weighting coefficients. The small region filter 52 has a center position (a position where the weighting coefficient is 220) corresponding to the target pixel.

  In the present embodiment, the values of the weighting coefficients of the large area filter 51 and the small area filter 52 are set so that the sum of the weighting coefficients of the large area filter 51 is equal to the sum of the weighting coefficients of the small area filter 52. It has been established. In the example of FIG. 4, the sum of the weighting coefficients is 360 for both the large area filter 51 and the small area filter 52.

The difference calculation unit 33 obtains a difference value between Rm obtained by the large region processing unit 31 and Rn obtained by the small region processing unit 32, and transmits the obtained difference value to the adjustment calculation unit 34. However, the difference calculation unit 33 makes the difference value calculation method different depending on whether the image data input to the color material amount suppression unit 12 is additive color mixture image data or subtractive color mixture image data.

More specifically, when the image data input to the color material amount suppression unit 12 is additive color mixture image data, the difference calculation unit 33 obtains a difference value by the following equation (1), and the color material amount suppression unit When the image data input to 12 is subtractive color image data, the difference value is obtained by the following equation (2).
Difference value = Rm−Rn Formula (1)
Difference value = Rn−Rm Formula (2)
In other words, in the case of additive color mixture image data, the product-sum value obtained using the small region filter 52 is subtracted from the product-sum value obtained using the large region filter 51. On the other hand, in the case of subtractive color image data, the product-sum value obtained using the large region filter 51 is subtracted from the product-sum value obtained using the small region filter 52.

  Further, the difference calculation unit 33 corrects the difference value when the difference value calculated by Expression (1) or Expression (2) is an unusable value due to the relationship with the number of bits. Specifically, when the calculation result of the formula (1) or the formula (2) is an unusable value, the difference calculation unit 33 sets the value closest to the calculation result among the usable values as the difference value. And For example, when the image data is 8-bit data, usable values are 0 to 255, and other values cannot be used. Therefore, the calculation result of Expression (1) or Expression (2) is In the case of a negative value, the difference value is set to zero, and in the case where the calculation result of Expression (1) or Expression (2) is 256 or more, the difference value is set to 255.

The adjustment calculation unit 34 outputs an adjusted difference value by multiplying the difference value transmitted from the difference calculation unit 33 by the adjustment coefficient based on the following equation (3). Then, the adjustment calculation unit 34 transmits the adjusted difference value to the pixel value output unit 35.
Difference value after adjustment = Adjustment coefficient × Difference value Formula (3)
The reason why the difference value is multiplied by the adjustment coefficient is to adjust the density of the entire image in the final output image. The smaller the adjustment coefficient, the lower the density of the entire output image.

  Here, the adjustment coefficient is set to the reciprocal of a value of several percent to several tens of percent of the sum of the weighting factors of the large area filter 51. In the present embodiment, the adjustment coefficient is 1/85. In this case, the adjustment coefficient “1/85” is the reciprocal of “85”, and “85” corresponds to 24% of “360”, which is the sum of the weighting coefficients of the large area filter 51 or the small area filter 52. .

  When the reciprocal (1/360) of the sum of the weighting coefficients of the large area filter 51 or the small area filter 52 is used as the adjustment coefficient, the adjusted difference value is smaller than the weighted average value obtained by using the large area filter 51. This is a difference value from the weighted average value obtained using the region filter 52. However, in this case, since the density of the output image becomes too low, in this embodiment, the density adjustment is performed using the reciprocal of 24% of the sum as an adjustment coefficient.

The pixel value output unit 35 is a block that outputs the pixel value of the pixel of interest based on the adjusted difference value transmitted from the adjustment calculation unit 34. Specifically, when the image data input to the color material amount suppression unit 12 is subtractive color mixing image data, the pixel value output unit 35 directly uses the adjusted difference value as the pixel of the target pixel according to the following equation (4). Value.
In the case of subtractive color mixture: pixel value = difference value after adjustment Equation (4)
That is, when the image data is subtractive color mixture, the pixel value output unit 35 outputs the adjusted difference value as the pixel value of the target pixel to the subsequent post-processing unit 13. Accordingly, the pixel value of the target pixel is determined such that the smaller the adjusted difference value, the lower the density of the target pixel, and the higher the adjusted difference value, the higher the target pixel density.

On the other hand, when the image data input to the color material amount suppression unit 12 is additive color mixture image data, the pixel value output unit 35 obtains the pixel value of the target pixel by calculating the following equation (5). . The “maximum value” in the equation (5) means the highest value within the numerical range that the pixel value can take, and is 255 when the image data is 8-bit data. In the present specification, the calculation according to the following equation (5) is referred to as “inversion processing”.
In case of additive color mixture: pixel value = maximum value−difference value after adjustment Equation (5)
That is, when the image data is additive color mixture, the pixel value output unit 35 outputs a value obtained by subtracting the adjusted difference value from the maximum value to the post-processing unit 13 at the subsequent stage as the pixel value of the target pixel. It will be.
Here, the reason why the inversion process is performed when the image data is additive color mixture will be described. In the present embodiment, the smaller the difference value (adjusted difference value), the lower the target pixel density, and the larger the difference value (adjusted difference value) value, the higher the target pixel density. This is for setting. That is, by performing the inversion process, even when the image data is additive color mixture, the smaller the adjusted difference value, the lower the density of the target pixel, and the larger the adjusted difference value, the higher the target pixel density. The pixel value of the target pixel is determined.

  Then, the pixel value output unit 35 transmits the pixel value of the target pixel determined by the above formula (4) or formula (5) to the post-processing unit 13 (see FIG. 1) at the subsequent stage.

  Next, the processing order of the color material amount suppression unit 12 will be described with reference to FIG. FIG. 3 is a flowchart showing the processing order of the color material amount suppression unit 12.

  When the image data is input, the color material amount suppression unit 12 obtains the product sum value Rm using the large region filter 51 for the M × M region including the target pixel (S1). Next, the color material amount suppression unit 12 calculates the product sum value Rn using the small region filter 52 for the N × N region including the target pixel (S2). After S2, the color material amount suppression unit 12 determines the color space of the input image data (S3).

  When it is determined in S3 that the color space of the input image data is a subtractive color space, the color material amount suppression unit 12 calculates Rn−Rm, thereby calculating the product sum value Rm and the product sum value Rn. A difference value is calculated (S4). Thereafter, the color material amount suppression unit 12 obtains the adjusted difference value by multiplying the difference value calculated in S4 by the adjustment coefficient. Further, the color material amount suppression unit 12 outputs the adjusted difference value as the pixel value of the target pixel. Then, when all the pixels of the input image are not handled as the target pixel (No in S5), the color material amount suppression unit 12 performs S1 to S4 for the next target pixel. On the other hand, the color material amount suppression unit 12 ends the process when all the pixels of the input image data are handled as the target pixel (Yes in S5).

  When it is determined in S3 that the color space of the input image data is an additive color space, the color material amount suppression unit 12 calculates Rm−Rn, thereby calculating the product sum value Rm and the product sum value Rn. Is calculated (S6). Thereafter, the color material amount suppression unit 12 obtains the adjusted difference value by multiplying the difference value calculated in S6 by the adjustment coefficient. Furthermore, the color material amount suppression unit 12 performs inversion processing on the adjusted difference value (S7), and outputs the value obtained by the inversion processing as the pixel value of the target pixel. Then, when all the pixels of the input image are not handled as the target pixel (No in S5), the color material amount suppression unit 12 performs S1 to S3, S6, and S7 for the next target pixel. On the other hand, the color material amount suppression unit 12 ends the process when all the pixels of the input image data are handled as the target pixel (Yes in S5).

  According to the processing of the color material amount suppression unit 12 described above, when a solid portion (for example, bold characters) is included in the image to be processed, the density is gradually increased from the contour (outside) of the portion toward the inside. Therefore, an image corrected so as to be lowered is output. And the center of the said part turns into white (solid color). This point will be described below with reference to FIG.

  FIG. 5A is a diagram showing an image printed when certain image data is processed in the normal mode. FIG. 5B is a diagram showing an image printed when the same image data as in FIG. 5A is processed in the save mode. As shown in FIG. 5, when the print image is a character image, the background region has a low density and the character region often has a high density (for example, the background region is white and the character region is Black).

  When the save mode is selected (when the processing by the color material amount suppression unit 12 is performed), the density of the outline of the character image remains, but the area inside the outline becomes almost white (solid). For example, as shown in FIG. 5A, it is assumed that there is image data that prints an image showing a thick character 61 composed of a solid portion when the normal mode is selected. On the other hand, as shown in FIG. 5B, when the save mode is selected, the outline of the bold character 61 remains as a line, but the inside of the outline is printed as being almost plain (white). become. Therefore, in the save mode, the shape of the bold character 61 is maintained, and the amount of toner used to form the bold character 61 is significantly reduced compared to that in the normal mode.

  Furthermore, although it is not clear from FIG. 5B, in the output image after the processing by the color material amount suppressing unit 12, the portion that was a solid portion before processing is directed inward from the contour of the portion. The density decreases gradually (gradually). FIG. 17A is an enlarged view showing the outline portion of the black character in the image including the black character and the white background region, and shows a state before the processing by the color material amount suppression unit 12 is performed. FIG. 17B is a view showing the same portion as the outline portion of the black character in FIG. 17A, and shows a state after the processing by the color material amount suppression unit 12 is performed. It is. In FIG. 17A, all pixels with X coordinates 1 to 7 are pixels belonging to black characters, and all pixels with X coordinates 8 to 14 are pixels belonging to a white background region. From FIG. 17A and FIG. 17B, in the output image after the processing by the color material amount suppression unit 12, the density gradually decreases from the black character outline (edge) toward the inside. I understand that.

  Further, when the processing by the color material amount suppression unit 12 is performed, the density of the solid part before the processing is gradually reduced from the outline toward the inside while the outline of the part remains. For a fine character image, the outline remains as it is, but the density is only slightly reduced in the central portion (to the extent that it cannot be observed with the naked eye), and the central portion does not become white. In other words, as shown in FIG. 5, when the small letter 62 composed of thin lines is printed, even if the save mode is selected, the density reduction is hardly confirmed with the naked eye, and the outline of the small letter 62 is interrupted. Therefore, the legibility of the lowercase letter 62 is maintained.

  As described above, according to the save mode of the printing system 1 of the present embodiment, the outline of both bold and small letters is maintained. Therefore, in a general pixel thinning process, there is a problem that the lower-case line is interrupted and the legibility of the character is deteriorated. However, the problem can be suppressed in the save mode of the printing system 1 of the present embodiment. Further, according to the save mode of the printing system 1 according to the present embodiment, when the image to be processed includes bold characters, the density gradually decreases from the outline of the bold characters toward the inside, Image processing is performed so that the central portion is substantially white (solid color). Therefore, it is possible to sufficiently reduce the density of the entire bold character without losing the outline shape of the bold character, and in general pixel thinning processing, there remains a room for suppressing the amount of toner used for the solid portion of the bold character. When a problem has occurred, the problem can be suppressed in the save mode of the printing system 1 of the present embodiment.

Next, when the processing by the color material amount suppression unit 12 is performed, as shown in FIG. 5, the outline of the bold character remains as a line and the central part of the bold character is corrected to almost white (plain color). Will be explained. FIG. 6A to FIG. 6D are diagrams for explaining the effect of the processing by the color material amount suppression unit 12.

  FIG. 6 shows an enlarged outline of a black character (black solid portion) formed on a white background. Also, the image data is subtractive color black data and is 8-bit data. In FIG. 6, it is assumed that the pixel values of the black solid region are 255 and all are equal, and the pixel values of the white solid region are 0 and all are equal.

  As shown in FIG. 6A, when the entire area of the large area filter 51, the entire area of the small area filter 52, and the target pixel face the black solid area of black characters, the pixel value of the target pixel is 0 (white). )become. This is because the sum of the weighting coefficients of the large area filter 51 and the sum of the weighting coefficients of the small area filter 52 are equal, so that the difference value of Equation (2) becomes zero.

  Next, as shown in FIG. 6B, the entire area of the small area filter 52 and the target pixel face the black solid area, but the large area filter 51 has a black solid area and a white solid area (white background). ), The pixel value of the pixel of interest output from the color material amount suppression unit 12 is a positive value. This is because the sum of the weighting coefficients of the large area filter 51 and the sum of the weighting coefficients of the small area filter 52 are equal, so that Rn> Rm in the situation shown in FIG. This is because the obtained difference value becomes positive.

  In the situation as shown in FIG. 6B, the value of Rm decreases as the target pixel approaches the outline of the character. Therefore, in the black character region, the pixel value becomes larger as the pixel is closer to the contour, and as a result, the density gradually decreases from the character contour toward the inside of the character.

  As shown in FIG. 6C, the entire region of the small region filter 52 and the target pixel face the white solid region, but the large region filter 51 faces both the black solid region and the white solid region. The pixel value of the pixel of interest output from the color material amount suppression unit 12 is zero. This is because Rn <Rm in the situation as shown in FIG. 6C, and the difference value obtained by the equation (2) is negative, but the negative value is an unusable value. It is because it is corrected to.

  As shown in FIG. 6D, when the entire area of the large area filter 51, the entire area of the small area filter 52, and the target pixel are opposed to the white solid area, the pixel value of the target pixel is 0 (white). Become. This is because the sum of the weighting coefficients of the large area filter 51 and the sum of the weighting coefficients of the small area filter 52 are equal, so that the difference value of Equation (2) becomes zero.

  From the above, when the entire area of the large area filter 51 is opposed to the black solid area, the pixel value of the target pixel is white, and the entire area of the large area filter 51 is opposed to the white solid area. The pixel value of the target pixel is also a value indicating white even when the When the large area filter 51 straddles the outline of the black character (in the case of FIG. 6B), the pixel value of the target pixel becomes a positive value. Therefore, white is maintained in the white solid area, the black solid area is converted to white, and the outline of the character remains as a line.

  Next, the case where the black character and the white background image data shown in FIGS. 6A to 6D are additive color mixture will be described. In the following description, it is assumed that the image data is 8 bits, the pixel values of all the pixels in the black solid region are (R, G, B) = (0, 0, 0), and all the pixels in the white solid region are Assume that the pixel values of (R, G, B) = (255, 255, 255). Hereinafter, only the processing of the R pixel value will be described, but the same applies to other color components.

As shown in FIG. 6A, when the entire area of the large area filter 51, the entire area of the small area filter 52, and the target pixel face the black solid area of black characters, the pixel value of the target pixel is 255 (white). )become. This is because the sum of the weighting coefficients of the large area filter 51 and the sum of the weighting coefficients of the small area filter 52 are equal, the difference value of equation (1) is 0, and this difference value is 255 according to equation (5). This is because it is converted into the pixel value shown.

  As shown in FIG. 6B, although the entire region of the small region filter 52 and the target pixel are opposed to the black solid region, the large region filter 51 has a black solid region and a white solid region (white background). When both face each other, the pixel value of the target pixel output from the color material amount suppression unit 12 is a value less than 255. This is because, in the situation as shown in FIG. 6B, Rm> Rn, so that the difference value of Equation (1) is larger than 0, and as a result, the pixel value obtained by Equation (5) This is because the value becomes less than 255.

  In the situation as shown in FIG. 6B, the value of Rm increases as the target pixel approaches the outline of the character. Therefore, in the black character region, the pixel value becomes smaller as the pixel is closer to the contour, and as a result, the density gradually decreases from the character contour toward the inside of the character.

  As shown in FIG. 6C, the entire region of the small region filter 52 and the target pixel face the white solid region, but the large region filter 51 faces both the black solid region and the white solid region. The pixel value of the target pixel output from the color material amount suppression unit 12 is 255 (white). This is because, in the situation shown in FIG. 6C, Rn> Rm, and the difference value obtained by Equation (1) is negative, but the negative value is an unusable value, so the difference value Is corrected to 0, and this difference value is converted into a pixel value indicating 255 by Equation (5).

  As shown in FIG. 6D, when the entire area of the large area filter 51, the entire area of the small area filter 52, and the target pixel are opposed to the white solid area, the attention output from the color material amount suppressing unit 12 is performed. The pixel value of the pixel is 255 (white). This is because the sum of the weighting coefficients of the large area filter 51 and the sum of the weighting coefficients of the small area filter 52 are equal, the difference value of the equation (1) becomes 0, and this difference value is 255 according to the equation (5). This is because it is converted into the pixel value shown.

  From the above, even when the image data is additive color mixture, if the entire area of the large area filter 51 faces the black solid area, the pixel value of the target pixel becomes a value indicating white, and the large area filter 51 The pixel value of the target pixel is also a value indicating white even when the whole area of the pixel faces the white solid region. When the large area filter 51 straddles the outline of the black character (in the case of FIG. 6B), the pixel value of the target pixel becomes a value other than the value indicating white (less than 255). Therefore, the white solid area is maintained white, the black solid area is converted to white, and the outline of the character remains as a line.

In the configuration described above, the small region processing unit 32 obtains a product sum value Rn of pixel values for a region (small region) composed of N × N pixels, and the large region processing unit 31 represents a region composed of M × M pixels. The product sum Rm of pixel values for (large region) is obtained. Then, when the image data is subtractive color mixture, the pixel value output unit 35 outputs the pixel value having a lower density as the pixel value of the target pixel as the difference value obtained by Expression (2) is smaller, and the image data is additive color mixture. In this case, the smaller the difference value obtained by Equation (1), the lower the pixel value is output as the pixel value of the target pixel. The small region processing unit 32 obtains the product sum value Rn by using the small region filter 52 that determines each weighting coefficient to be applied to the pixel value of each pixel belonging to the region composed of N × N pixels, and the large region processing unit No. 31 obtains the product sum value Rm using a large area filter 51 that defines each weighting coefficient to be multiplied to the pixel value of each pixel belonging to the area composed of M × M pixels. The weighting coefficients of the small area filter 52 and the large area filter 51 are determined so that the sum of the weighting coefficients of the small area filter 52 is equal to the sum of the weighting coefficients of the large area filter 51. According to such a configuration, when a solid portion (for example, bold text) is included in the image to be processed, the density gradually decreases as it goes inward from the contour of the portion, and the center of the portion becomes The image can be corrected so as to be white (solid).

  Even if the sum of the weighting coefficients of the small area filter 52 and the sum of the weighting coefficients of the large area filter 51 are slightly shifted, if there is a solid part in the image to be processed, the outline of the part is inward. If the effect of decreasing the density stepwise as it goes is obtained, it can be said that the sum of the weighting coefficients of the small area filter 52 and the sum of the weighting coefficients of the large area filter 51 are substantially equal.

  For example, when the error between the sum of the weighting coefficients of the small area filter 52 and the sum of the weighting coefficients of the large area filter 51 is 1, the adjusted difference value obtained by the adjustment calculation unit 34 and the error is zero. In such a case, if the difference value after adjustment obtained by the adjustment calculation unit 34 matches, even if there is an error in both sums, it is considered that both sums are substantially equal. More specifically, when Rn and Rm are calculated with the number of bits of image data being 8 and a pixel located at the center of the solid image as a target pixel, if the error is 1, Rn and Rm are There may be a deviation of up to 255. However, since the system is normally constructed so that the value after the decimal point of the adjusted difference value obtained by the adjustment calculation unit 34 is rounded off, if the adjustment coefficient is 1/512 or less, the error is 1. The adjusted difference value that is finally output in the case of zero matches.

  In addition, since the input image data of the present embodiment is RGB data or CMYK data, the above processing by the color material amount suppression unit 12 is performed for each color channel (each color component). The weighting coefficients in the large area filter 51 and the small area filter 52 may be switched for each color channel or may be the same for each color component. In the configuration in which the weighting coefficient is switched for each color channel, when the input image data is data read from the scanner, if there is a variation in resolution for each color channel due to the characteristics of the optical system, this is suppressed. It becomes possible. For example, the large area filter 51b and the small area filter 52b shown in FIG. 11 are filters for color channels with low resolving power (filters with low smoothness).

  Further, in Patent Document 1, when the pattern is changed at the edge portion without changing the pattern, since there is only one type of pattern change, the gap at the boundary is conspicuous and sufficient printing material is used. The reduction effect may not be expected. In contrast, in the present embodiment, it is possible to obtain an output result that is resistant to noise, halftone dot patterns, and the like in the image data by using weighted values by filters of different sizes. When generating a reduced image, it is possible to achieve both good character readability and toner reduction effect by performing relatively simple filter processing, particularly on the character portion, without being aware of the halftone dot pattern.

  In addition, as shown in FIGS. 17A and 17B, the output image after the processing by the color material amount suppressing unit 12 is stepped inward from the outline (edge) of the black character. The reason for this is explained below.

It is assumed that the images in FIGS. 17A and 17B are subtractive color and 8-bit image data. Also, in FIG. 17A, the value of K (black) is 255 for the pixels whose X coordinates are 1 to 7. In FIG. 17A, although not shown in the figure, the area where the Y coordinate is smaller than 1 and the area where the Y coordinate is 8 or more have a K (black) value of 255 for the pixels whose X coordinate is 1 to 7. It shall be. Further, in FIG. 17A, it is assumed that the value of K is 0 for all pixels whose X coordinates are 8 to 14. In FIG. 17A, although not shown in the figure, the area where the Y coordinate is smaller than 1 and the area where the Y coordinate is 8 or more also have a K (black) value of 0 for the pixels whose X coordinate is 1 to 7. It shall be. Further, in the images of FIGS. 17A and 17B, X = 7 pixels correspond to the outline (edge) of the black character, and the direction parallel to the X axis and X = 7 pixels A direction toward one pixel is a direction toward the inside from the outline of the black character.

  First, when the color material amount suppression unit 12 performs the process of FIG. 3 on the image of FIG. 17A using the large area filter 51 and the small area filter 52 of FIG. 4 (the adjustment coefficient is 1/85). ), The Rn, Rm, difference value, and adjusted difference value of the pixel whose X coordinate value of the target pixel is 4 to 11 are the values shown in FIG. Note that the difference value is a negative value for a pixel whose X coordinate value of the target pixel is 8 to 10. However, when the difference value is a negative value, the difference value is corrected to zero, so that the adjusted difference value is also zero as shown in FIG.

  FIG. 17C shows the calculation result for each pixel having a Y coordinate of 4 and an X coordinate of 4 to 11, but the X coordinate is also obtained in a region other than the Y coordinate of 4. Similar results are obtained for each pixel 4-11.

  Then, based on the result shown in FIG. 17C, the image of FIG. 17B is output. Here, as apparent from FIGS. 17B and 17C, in the output image, the pixel with X = 7 has the highest density, and the pixel with X = 6 has the density next to the pixel with X = 7. The pixel with X = 5 has the next highest density after the pixel with X = 6, and the pixel with X = 4 has the lowest density (white). In other words, in the output image, the density of the black characters decreases stepwise (in a gradation) from the outline of the black characters toward the inside.

  Although not shown in FIG. 17 (b), the same gradation pattern as the region having the Y coordinate of 1 to 7 is formed even in the region where the Y coordinate is smaller than 1 and the region where the Y coordinate is 8 or more. become.

  The gradation state varies depending on the filter size, the filter coefficient, and the adjustment coefficient of the adjustment calculation unit 34. Furthermore, the number of gradation steps changes according to the difference between the size of the large area filter 51 and the size of the small area filter 52. For example, when the index value of the size difference between the large area filter 51 of M × M pixels and the small area filter 52 of N × N pixels is MN, the number of gradation steps increases as MN increases. . For example, in the case of the combination of the large area filter 51 and the small area filter 52 in FIG. 4, MN is 4, and the number of gradation steps is 3 as shown in FIG. When the large area filter is 9 × 9 pixels and the small area filter is 3 × 3 pixels, MN is 6 and the number of gradation steps is 4. Further, when the large region filter has a size of 13 × 13 pixels and the small region filter has a size of 5 × 5 pixels, MN is 8 and the number of gradation steps is 5.

  When the image in FIG. 17A is composed of additive color mixture image data, Rn, Rm, the difference value, and the adjusted difference value are as shown in FIG.

[Embodiment 2]
In the first embodiment, an operation for obtaining the product-sum value Rm using the large region filter 51, an operation for obtaining the product-sum value Rn using the small region filter 52, an operation for obtaining a difference value between Rm and Rn, The difference value is multiplied by an adjustment coefficient to obtain an adjusted difference value. The difference value is Rm−Rn when the image data is additive color mixture, and is Rn−Rm when the image data is subtractive color mixture.

On the other hand, a coefficient in which the weighting coefficient of the large area filter 51, the weighting coefficient of the small area filter 52, and the adjustment coefficient are calculated in advance at positions corresponding to each other in the large area filter 51 and the small area filter 52. In addition, a value corresponding to the adjusted difference value may be obtained using a filter using this coefficient as a weighting coefficient. That is, a single weighting filter is created by combining the large area filter 51 and the small area filter 52. Hereinafter, this weighting filter creation method will be described. In the following description, the weighting coefficient of the large area filter 51 is referred to as a first coefficient, and the weighting coefficient of the small area filter 52 is referred to as a second coefficient.

  First, a method for creating a weighting filter for additive color mixture image data will be described. A difference is obtained by subtracting the second coefficient from the first coefficient at positions corresponding to each other of the large area filter 51 and the small area filter 52 shown in FIG. 4, and an adjustment coefficient (1/85) is calculated for the difference. The value obtained by multiplication is taken as the third coefficient. Of the positions of the large area filter 51, those having no corresponding small area filter 52 are calculated with the second coefficient set to zero.

  For example, the center position of the large area filter 51 and the center position of the small area filter 52 correspond to each other, and the first coefficient of the center position of the large area filter 51 is 48 as shown in FIG. The second coefficient at the center position of 220 is 220. Therefore, by calculating (48−220) × (1/85), −2.024 is obtained as the third coefficient of the center position.

  Further, the right adjacent position of the center position of the large area filter 51 and the right adjacent position of the center position of the small area filter 52 correspond to each other, and as shown in FIG. The first coefficient is 17, and the second coefficient at the position right next to the center position of the small region filter 52 is 24. Therefore, by calculating (17-24) × (1/85), −0.082 is obtained as the third coefficient at the right adjacent position.

  Furthermore, as shown in FIG. 4, 1 is set as the first coefficient at the vertex position of the large area filter 51, but the position of the corresponding small area filter 52 does not exist at this vertex position. Therefore, by calculating (1-0) × (1/85), 0.012 is obtained as the third coefficient of the vertex position.

  As described above, the third coefficient is obtained for each position of the large area filter 51, and a first weighting filter in which all the obtained third coefficients are determined as weighting coefficients is created. An example of the first weighting filter is shown in FIG.

  Since the sum of the coefficients of the large area filter 51 is equal to the sum of the coefficients of the small area filter 52, the sum of the coefficients of the first weighting filter is usually zero. However, when the value after the decimal point of the third coefficient is rounded off as in the calculation example described above, the sum of the coefficients of the first weighting filter may be slightly deviated from zero. Also in the above calculation example, since the third decimal place of the third coefficient is rounded off, the sum of the coefficients of the first weighting filter is 0.008. Therefore, the coefficients in the first weighting filter are adjusted so that the sum of the coefficients of the first weighting filter becomes zero. For example, in the above calculation example, in the first weighting filter created from the large area filter 51 and the small area filter 52, the coefficient at the center position is −2.024, but the coefficient at the center position is −2.024. By changing (correcting) from -2.032, the sum of the coefficients of the first weighting filter can be made zero. The first weighting filter 53 in FIG. 10 is created from the large area filter 51 and the small area filter 52, and the coefficient of the center position is changed from −2.024 to −2.032. .

The coefficient adjustment position is not limited to the center position. For example, in the first weighting filter created from the large area filter 51 and the small area filter 52 based on the above calculation example, the coefficient at each vertex position is set to 0.012 while the coefficient at the center position is kept at −2.024. Even if the value is changed from 0.010 to 0.010, the sum of the coefficients of the first weighting filter can be made zero. If the sum of the weighting coefficients of the first weighting filter is a value slightly deviated from zero, if the sum of the weighting coefficients is substantially zero, the sum of the coefficients of the first weighting filter is There is no need to make it zero. The case where the sum of the weighting coefficients is substantially zero will be described in detail later.

  Next, the first weighting filter 53 in FIG. 10 will be described. The first weighting filter 53 of FIG. 10 corresponds to the same size as the large area filter 51, that is, the size of M × M pixels, and is used for image data of additive color mixture. The first weighting filter 53 has each position corresponding to each pixel of a block composed of 7 × 7 pixels centered on the target pixel. Each position of the first weighting filter 53 is associated with a weighting coefficient to be applied to each pixel corresponding to each position. Furthermore, in the first weighting filter 53 of FIG. 10, each position inside the thick line indicated by the symbol α corresponds to each pixel in the first region composed of 3 × 3 pixels centered on the target pixel. . Further, each position outside the thick line indicated by the symbol α is an area arranged so as to surround the first area in a block composed of 7 × 7 pixels centered on the target pixel, and on the outer periphery of the block. Corresponding to each pixel in the second region including the pixel adjacent to the pixel, a positive sign weighting coefficient is associated. The weighting coefficients of the first weighting filter 53 are set so that the sum is zero.

  Next, a method for creating a weighting filter for subtractive color image data will be described. First, a difference is obtained by subtracting the first coefficient from the second coefficient at positions corresponding to each other in the large area filter 51 and the small area filter 52 shown in FIG. 4, and an adjustment coefficient (1/85) is obtained with respect to the difference. ) Is used as the fourth coefficient. Of the positions of the large area filter 51, those having no corresponding small area filter 52 are calculated with the second coefficient set to zero.

  In the example shown in FIG. 4, the first coefficient at the center position of the large area filter 51 is 48, and the second coefficient at the center position of the small area filter 52 is 220. Therefore, by calculating (220−48) × (1/85), 2.024 is obtained as the fourth coefficient of the center position. Further, although 1 is set as the first coefficient at the vertex position of the large area filter 51, the position of the corresponding small area filter 52 does not exist at this vertex position. Therefore, by calculating (0-1) × (1/85), −0.012 is obtained as the fourth coefficient.

  In this way, the fourth coefficient is obtained for each position of the large area filter 51, and a second weighting filter is created in which all the obtained fourth coefficients are determined as weighting coefficients. An example of the second weighting filter is shown in FIG.

  Since the sum of the coefficients of the large area filter 51 is equal to the sum of the coefficients of the small area filter 52, the sum of the coefficients of the second weighting filter is usually zero. However, when the value after the decimal point of the fourth coefficient is rounded off as in the calculation example described above, the sum of the coefficients of the second weighting filter may not be zero. In the above calculation example as well, since the fourth decimal place of the fourth coefficient is rounded off, the sum of the coefficients of the second weighting filter becomes −0.008. Therefore, as in the case of the first weighting filter, the coefficients in the second weighting filter are adjusted so that the sum of the coefficients of the second weighting filter becomes zero. The second weighting filter 54 in FIG. 10 is created from the large area filter 51 and the small area filter 52, and the coefficient at the center position is set to 2.024 to 2. It is changed to 032.

  The coefficient adjustment position in the second weighting filter is not limited to the center position, as in the case of the first weighting filter. Similarly to the case of the first weighting filter, it is not necessary to make the sum of the coefficients zero when the sum of the weighting coefficients of the second weighting filter is substantially zero.

  Next, the second weighting filter 54 in FIG. 10 will be described. The 2nd weighting filter 54 has each position corresponding to each pixel of the block which consists of a 7x7 pixel centering on an attention pixel. Each position of the second weighting filter 54 is associated with a weighting coefficient to be applied to each pixel corresponding to each position. Furthermore, in the second weighting filter 54 of FIG. 10, each position inside the thick line indicated by the symbol β corresponds to each pixel in the first region composed of 3 × 3 pixels centered on the target pixel. . Further, each position outside the thick line indicated by the symbol β is an area arranged so as to surround the first area in a block of 7 × 7 pixels centered on the target pixel, and on the outer periphery of the block. A negative sign weighting coefficient is associated with each pixel in the second region including the pixel adjacent to the pixel. Each weighting coefficient of the second weighting filter 54 is set so that the sum thereof becomes zero.

  When the product sum value Rm ′ of the pixel values of the region composed of M × M pixels is obtained using the first weighting filter 53 or the second weighting filter 54 as described above, the product sum value Rm ′ is determined as the first embodiment. It becomes a value equal to the adjusted difference value. Therefore, if the product sum value Rm ′ (a value equal to the adjusted difference value) is obtained by using the first weighting filter 53 or the second weighting filter 54, both the large region filter 51 and the small region filter 52 are used. Thus, since the number of filters to be used can be reduced as compared with the first embodiment for obtaining the adjusted difference value, the calculation process can be greatly reduced.

The product-sum value Rm ′ is obtained by the following formula 3. K _ij in [ _Expression 3] indicates a weighting coefficient at the position of the i-th row and the j-th column of the first weighting filter 53 or the second weighting filter 54, and I _{ij in} [ _Expression 3] indicates the first weighting filter 53 or the first weighting filter 53. The pixel value of the pixel corresponding to the position of i row and j column of the 2 weighting filter 54 is shown.

That is, the product-sum value Rm ′ is obtained by weighting the pixel value by multiplying the pixel value and the weighting coefficient for each pixel in the region of M × M pixels, and summing the weighted pixel values (total , Cumulative).

  Next, a configuration example of the color material amount suppression unit 12 when image processing is performed using the first weighting filter 53 or the second weighting filter 54 will be described. FIG. 7 is a block diagram illustrating an internal configuration example of the color material amount suppressing unit 12 according to the second embodiment. In the present embodiment, the color material amount suppression unit 12 includes a filter selection unit 71, a product sum calculation unit 72, and a pixel value output unit 73, as shown in FIG.

The filter selection unit 71 is a block that determines the color space of the input image data and selects a filter according to the determination result. More specifically, the filter selection unit 71 selects the first weighting filter 53 shown in FIG. 10 when the input image data is additive color mixture data, and when the input image data is subtractive color mixture data. Second weighting filter 5 shown in FIG.
4 is selected.

  The product-sum value calculation unit 72 is a block that calculates the product-sum value Rm ′ using the filter selected by the filter selection unit 71 and transmits the calculated product-sum value Rm ′ to the pixel value output unit 73. However, when the calculated product-sum value Rm ′ is an unusable value due to the relationship with the number of bits, the product-sum value calculation unit 72 performs the same correction as the correction performed by the difference calculation unit 33. The correction is performed on Rm ′, and the corrected product-sum value Rm ′ is transmitted to the pixel value output unit 73.

The pixel value output unit 73 is a block that outputs the pixel value of the pixel of interest based on the product sum value Rm ′ sent from the product sum value calculation unit 72. Specifically, when the input image data is subtractive color image data, the pixel value output unit 35 uses the product-sum value Rm ′ as it is as the pixel value of the pixel of interest according to the following equation (6).
In the case of subtractive color mixture: pixel value = product sum value Rm ′ Expression (6)
On the other hand, when the input image data is additive color mixture image data, the pixel value output unit 35 obtains the pixel value of the target pixel by calculating the following equation (7). “Maximum value” in the equation (7) means the highest value within a numerical range that the pixel value can take, and is 255 when the image data is 8-bit data. In this specification, in addition to the calculation according to the equation (5), the calculation according to the following equation (7) is also referred to as “inversion processing”.
In the case of additive color mixture: pixel value = maximum value−product sum value Rm ′ Expression (7)
Note that the reason for performing the reversal process when the image data is additive color mixture is the same as in the first embodiment.

  Next, the processing order of the color material amount suppression unit 12 of this embodiment will be described with reference to FIG. FIG. 8 is a flowchart showing the processing order of the color material amount suppression unit 12 according to the second embodiment.

  When the image data is input, the color material amount suppression unit 12 determines the color space of the input image data (S11). Then, the color material amount suppression unit 12 selects the first weighting filter 53 of FIG. 10 when the input image data is additive color mixture data (S17), and when the input image data is subtractive color mixture data, The 2-weighting filter 54 is selected (S12).

  Next, the color material amount suppression unit 12 calculates a product sum value Rm ′ for the target pixel using the filter selected in S12 or S17 (S13). After S13, when the input image data is subtractive color mixture data (No in S14), the color material amount suppression unit 12 outputs the product sum value Rm ′ as the pixel value of the target pixel, and the process proceeds to S16. Let On the other hand, after S13, when the input image data is additive color mixture data (Yes in S14), the color material amount suppression unit 12 performs an inversion process on the product sum value Rm ′ and performs the inversion process. The value obtained in this way is output as the pixel value of the target pixel (S15), and the process proceeds to S16.

  Then, when all the pixels of the input image are not handled as the target pixel (No in S16), the color material amount suppression unit 12 performs the processing from S13 onward for the next target pixel. On the other hand, the color material amount suppression unit 12 ends the process when all the pixels of the input image data are handled as the target pixel (Yes in S16).

  As described above, in the present embodiment, the color material amount suppression unit 12 includes the product sum value calculation unit 72 and the pixel value output unit 73. Then, the product-sum value calculation unit 72 uses the first weighting filter 53 or the second weighting filter 54 to obtain a product-sum value Rm ′ of pixel values for a block composed of 7 × 7 pixels including the target pixel. . The pixel value output unit 73 outputs a pixel value having a lower density as the pixel value of the target pixel as the product sum value Rm ′ is smaller.

Here, the product-sum value Rm ′ is equal to the adjusted difference value in the first embodiment as described above. Therefore, the same effects as those of the first embodiment can be obtained in the above processing. That is, when the image to be processed includes a solid part (for example, bold characters), the density gradually decreases as it goes inward from the outline of the part, and the center of the part becomes white (solid). As described above, the image can be corrected.

  In the first weighting filter 53 of FIG. 10, even when the total sum of the weighting coefficients is slightly deviated from zero, when there is a solid part in the image to be processed, as it goes inward from the outline of the part If the effect of decreasing the density stepwise is obtained, it can be said that the sum of the weighting coefficients is substantially zero. For example, it is assumed that the number of bits of image data is 8, the weighting coefficient of the weighting filter is valid up to the third decimal place, and the sum of the weighting coefficients in the weighting filter is 0.001. However, the product sum value obtained by the product sum value calculation unit 72 is normally constructed so that the value after the decimal point is rounded off, so that the product sum obtained when the sum of each weighting coefficient is 0.001. The value matches the product-sum value obtained when the sum of the weighting coefficients is zero. Therefore, even if the sum of the weighting coefficients is 0.001, it can be said that the sum of the weighting coefficients is substantially zero.

  Further, the first weighting filter 53 and the second weighting filter 54 in FIG. 10 may include a zero weighting coefficient. That is, in the first weighting filter 53, each coefficient outside the thick line indicated by the symbol α is not limited to a positive value and may be a value of zero or more. Further, in the second weighting filter 54, each coefficient outside the thick line of the symbol β is not limited to a negative value and may be a value equal to or less than zero. Further, each coefficient inside the thick line of the sign α of the first weighting filter 53 and each coefficient inside the thick line of the sign β of the second weighting filter 54 is a negative value even if it is a positive value. It may be zero or zero.

[Embodiment 3]
When a character image is formed in the white background area in the input image as shown in FIG. 5A, according to the processing of the color material amount suppression unit 12 of the first and second embodiments, FIG. As described above, the color of the contour portion of the character image after correction can be made almost the same as the color of the character image before correction.

  However, as shown in FIG. 9A, when a character image is formed in a colored background region in the input image, it is only necessary to perform the processing of the color material amount suppression unit 12 of the first and second embodiments. A situation may occur in which the color of the contour portion of the character image after correction is completely different from the color of the character image before correction or the color of the background area. Hereinafter, this reason will be described.

  For example, as shown in FIG. 9A, additive color mixture image data in which black characters 90 are formed on a red background area 89 is input, and the color material amount suppression unit 12 according to the first embodiment uses the image data. Consider the case of processing. In FIG. 9A, each pixel value of the red background region 89 is (R, G, B) = (255, 0, 0), and each pixel value of the black character 90 is (R, G, B). = (0, 0, 0).

  In this case, as shown in FIG. 6B, when the entire region of the small region filter 52 and the target pixel are opposed to the black solid region (black character), and the large region filter 51 is opposed to the base region and the black solid region. (Note that the background is white in FIG. 6B, but the background color is assumed to be red here.) If the adjusted difference value of Equation 3 for R is α, the pixel value of the pixel of interest is (255− α, 255, 255). That is, the pixel value of the target pixel that is output does not indicate the original color (black) of the target pixel, but indicates a complementary color of the color of the reference pixel that is referred to in the filter calculation.

FIG. 9B is a diagram illustrating a processed image when the color material amount suppressing unit 12 according to the first embodiment processes the image of FIG. In FIG. 9B, while the outline of the character remains, the inside of the outline and the portion that was the red background area are replaced with white. However, in FIG. 9B, the character outline 92 is blue-green (red complementary color). That is, there arises a problem that a color different from the original color of the character and the original color of the background is indicated as the outline of the character or the background.

  In order to avoid such a problem, the color material amount suppression unit 12 may be provided with the following similarity determination unit. The similarity determination unit calculates the color of all the reference pixels (pixels other than the target pixel) in the filter with the color of the target pixel before the filter calculation is performed in the large region processing unit 31 and the small region processing unit 32. Similarity data indicating similarity is calculated, the similarity data is compared with a threshold value, and it is determined whether the color of the reference pixel is similar to the color of the target pixel.

  Here, the similarity data may be any value as long as it is a value generally used as a value indicating the degree of difference between the color of the pixel A and the color of the pixel B. For example, when the image data is additive color mixture data, the Euclidean distance between the target pixel and the reference pixel (the square root of the square sum of the difference values of the pixel values for each color channel) may be used as the similarity data. In this case, the similarity determination unit compares the Euclidean distance between the target pixel and the reference pixel with a threshold, and determines that the color of the reference pixel is dissimilar to the color of the target pixel if the Euclidean distance is equal to or greater than the threshold. If the Euclidean distance is less than the threshold value, it is determined that the color of the reference pixel is similar to the color of the target pixel. Even if the image data is subtractive color mixture, the Euclidean distance can be obtained by converting the image data into additive color mixture image data. Therefore, the Euclidean distance may be used as the similarity data.

  Further, the similarity data may be a value obtained by converting into data in a color space other than the additive color mixture and subtractive color mixture. For example, the input image data is converted into HSI (H: Hue, S: Saturation, I: Lightness) color space data, and the difference between the hue value (hue angle) of the target pixel and the hue value of the reference pixel A first difference value, a second difference value that is the difference between the saturation value of the target pixel and the saturation value of the reference pixel, and a third difference value that is the difference between the lightness value of the target pixel and the lightness value of the reference pixel These difference values may be obtained as the similarity data. Then, the similarity determination unit compares these difference values with a threshold value, and determines that the color of the reference pixel is similar to the color of the target pixel if all the difference values are less than the threshold value, and otherwise. Judged as dissimilar. However, considering the influence of noise and the like, different thresholds are set for the first difference value, the second difference value, and the third difference value.

  Then, the large region processing unit 31 and the small region processing unit 32 in FIG. 2 convert the pixel value of the reference pixel having a color determined to be dissimilar to the color of the target pixel into a pixel value indicating white (minimum density). Then, the product-sum values Rm and Rn are calculated using the converted values (Note that the input pixel value is used as it is without performing the conversion for a reference pixel having a color determined to be similar to the color of the target pixel). .

  For example, when the input image data is 8-bit additive color mixture data, the reference pixel data having a color determined to be dissimilar to the color of the target pixel is (R, G, B) = (255, 255, 255). The product sum values Rm and Rn are calculated. When the input image data is 8-bit subtractive color mixture data, the reference pixel data having a color determined to be dissimilar to the color of the target pixel is (C, M, Y) = (0, 0, 0). The product sum values Rm and Rn are calculated.

Thereby, it can suppress that the problem that the color which does not exist in an input image produces | generates arises. For example, when the image shown in FIG. 9A is processed in the configuration including the similarity determination unit, the image shown in FIG. 9C is output. In the image shown in FIG. 9C, the black character outline 95 and the red base area outline 94 are formed adjacent to each other. The contour 95 is black, the contour 94 is red, and there is a situation in which a color different from the original color of the character or a color different from the original color of the background is shown as the outline of the character or the background. Absent.

  Moreover, the similarity determination part demonstrated above may be provided in the product sum value calculation part 72 (FIG. 7) of Embodiment 2. FIG. Then, the product-sum value calculation unit 72 calculates the product-sum value Rm ′ after converting the input pixel value of the reference pixel having a color determined to be dissimilar to the color of the target pixel into a pixel value representing white. To do.

[Embodiment 4]
Character images and graphic images frequently contain solid portions. Therefore, by performing processing using the large region filter 51 and the small region filter 52 and processing using the weighting filters 53 and 54 on the character image or graphic image, toner consumption is maintained while maintaining image readability. It has the merit that the amount can be suppressed.

  However, since natural images (photo areas) have a low frequency of including a solid portion, processing using the large area filter 51 and the small area filter 52 and processing using the weighting filters 53 and 54 are more effective than the above-described merit. However, there is a demerit that an uncomfortable image is output.

  Therefore, for character images and graphic images, processing using the large region filter 51 and small region filter 52 and processing using the weighting filters 53 and 54 are performed, while these processing is performed for natural images. If not, the demerit that an uncomfortable image is output can be suppressed. Hereinafter, this point will be described by taking the color material amount suppression unit 12 of FIG. 7 as an example. In the following description, the input image data is assumed to be additive color mixture data.

  When the image data input to the printing system 1 is PDL format data created by an external terminal, a flag indicating the type of each image area is described in the image data. Here, there are types of image areas such as a character (text) area, a graphic area, and a natural image (photo) area.

  When the image data is PDL format data created by an external terminal, the preprocessing unit (determination processing unit) 11 determines the type of each image area of the image data based on the flag described in the image data. The tag data indicating the determination result is generated. As described above, the types of image areas determined here include character areas, graphic areas, natural image areas, and the like. Then, the preprocessing unit 11 sends the tag data to the color material amount suppression unit 12.

  The color material amount suppression unit 12 determines an image area to which the target pixel belongs based on the tag data, and switches processing according to the image area.

  More specifically, when the image region to which the target pixel belongs is a character region or a graphic region, the filter selection unit 71 of the color material amount suppression unit 12 in FIG. 7 selects the first weighting filter 53 shown in FIG. It has become. On the other hand, when the image region to which the target pixel belongs is a natural image region, the filter selection unit 71 does not select the first weighting filter 53 shown in FIG. 10, but selects the high-intensity filter 60a shown in FIG. It is like that.

  The product-sum value calculation unit 72 calculates the product-sum value Rm ′ using the filter selected by the filter selection unit 71, and the pixel value output unit 73 includes the product-sum value calculation unit 72. The pixel value of the target pixel is output based on the product-sum value Rm ′ calculated in step (b).

  That is, the color material amount suppression unit 12 performs processing using the first weighting filter 53 for an image area determined as a character area or a graphic area, and for an image area determined as a natural image area. Processing using the first weighting filter 53 is not performed. As a result, it is possible to suppress the demerit that an image having a sense of incongruity with respect to the natural image region is output.

  In the present embodiment, instead of performing the process using the first weighting filter 53 on the natural image region, the process using the high brightness filter 60a shown in FIG. 12 is performed. Here, the high-intensity filter 60a shown in FIG. 12 is a filter in which a weighting coefficient is determined so that the luminance increases substantially uniformly over the entire region to be processed. Therefore, in this embodiment, it is possible to obtain a toner consumption suppression effect without causing a sense of incongruity even in the natural image region.

  12 is the same size (7 × 7 pixels) as the first weighting filter 53 in FIG. 10, but the size of the brightening filter is the same size as the first weighting filter 53. There is no need. For example, a 7 × 7 pixel first weighting filter 53 is used for a character region or a graphic region, while a 5 × 5 pixel weighting filter 60b (see FIG. 12) is used for a natural image region. Also good.

In the color material amount suppression unit 12 of FIG. 2, the processing content may be changed according to the type of image area. For example, the large region processing unit 31 and the small region processing unit 32 in FIG. 2 perform processing using the large region filter 51 and the small region filter 52 on the image region determined to be a character region or a graphic region, and thus a natural image The processing using the large area filter 51 and the small area filter 52 may not be performed on the image area determined as the area.
Further, for the image area determined to be a natural image area, the large area processing unit 31 obtains the product sum value Rm using the brightness enhancement filter 63a of FIG. 18, and the small area processing unit 32 and the difference calculation unit 33 Without performing the processing, the adjustment calculation unit 34 obtains an adjusted product sum value based on the following equation (8). It is assumed that the adjustment coefficient of the following formula (8) when the high brightness filter 63a of FIG. 18 is used is 1/100.

Adjusted product sum value = adjustment coefficient × product sum value Rm Formula (8)
Then, when the input image data is subtractive color mixing data, the pixel value output unit 35 outputs the adjusted product sum value obtained by Expression (8) as the pixel value of the target pixel, and the input image data is additive. In the case of mixed color data, the pixel value obtained by calculating the following equation (9) is output as the pixel value of the target pixel. Note that the “maximum value” in equation (9) means the highest value within the numerical range that the pixel value can take, and is 255 when the image data is 8-bit data.
Pixel value = Maximum value−Adjusted product sum value Equation (9)
Thereby, also in the configuration of FIG. 2, it is possible to obtain a toner consumption suppression effect while suppressing the demerit that an uncomfortable image is output for the natural image region.

  18 is the same size (7 × 7 pixels) as the large area filter 51 in FIG. 4, but the size of the high intensity filter is the same as that of the large area filter 51 or the small area filter 52. It doesn't have to be size. For example, a 5 × 5 pixel high brightness filter 63b (see FIG. 18) may be used for the natural image region.

  Further, the adjustment coefficient in the expression (3) of the first embodiment may be changed according to the type of the image area determined by the preprocessing unit 11.

[Embodiment 5]
Further, when the image data input to the printing system 1 is image data read by a scanner, the type of the image region to which the target pixel belongs is determined by performing region separation processing, and for each type of image region, The filter to be used may be changed. Hereinafter, this point will be described by taking the color material amount suppression unit 12 of FIG. 7 as an example.

  When the input image data is image data read by a scanner, the preprocessing unit (determination processing unit) 11 performs region separation processing for determining the type of each image region included in the image of the image data. ing. Here, the types of image areas determined by the area separation processing include character areas, halftone dot areas, continuous tone areas (photographic paper photograph areas), and the like. Then, the preprocessing unit 11 sends an area identification signal indicating to which image area each pixel of the image data belongs to the color material amount suppression unit 12.

  The color material amount suppression unit 12 determines an image region to which the target pixel belongs based on the region identification signal, and changes a filter to be used according to the image region.

  More specifically, when the image region to which the target pixel belongs is a character region, the filter selection unit 71 of the color material amount suppression unit 12 in FIG. 7 selects the first weighting filter 53 shown in FIG. Yes. On the other hand, when the image region to which the target pixel belongs is a halftone region or a continuous tone region, the filter selection unit 71 does not select the first weighting filter 53 shown in FIG. 60a is selected.

  The product-sum value calculation unit 72 calculates the product-sum value Rm ′ using the filter selected by the filter selection unit 71, and the pixel value output unit 73 includes the product-sum value calculation unit 72. The pixel value of the target pixel is output based on the product-sum value Rm ′ calculated in step (b).

  As a result, the color material amount suppression unit 12 performs processing using the first weighting filter 53 on the image area determined as the character area, and the image area determined as the halftone area or the continuous tone area. On the other hand, the process using the first weighting filter 53 is not performed. As a result, it is possible to suppress the demerit that an image having a sense of incongruity with respect to the natural image region is output.

  Note that the size of the high brightness filter is not necessarily the same as the size of the first weighting filter 53 as in the case of the fourth embodiment.

  In the present embodiment, instead of performing the process using the first weighting filter 53 on the halftone area or the continuous tone area, the process using the high brightness filter 60a shown in FIG. 12 is performed. It has become. Here, the brightening filter 60a shown in FIG. 12 is a filter in which a weighting coefficient is determined so that the luminance increases substantially uniformly over the entire region to be processed. Therefore, in the present embodiment, it is possible to obtain a toner consumption suppression effect without causing a sense of incongruity also in the halftone area or the continuous tone area.

Furthermore, in the color material amount suppression unit 12 of FIG. 2, the filter to be used may be switched according to the result of the region separation process. For example, the large region processing unit 31 and the small region processing unit 32 in FIG. 2 perform processing using the large region filter 51 and the small region filter 52 on the image region determined as the character region, The processing using the large area filter 51 and the small area filter 52 may not be performed on the image area determined as the continuous tone area. Further, for the halftone dot area or continuous tone area, the large area processing unit 31 obtains the product-sum value Rm using the brightness enhancement filter 63a of FIG. 18, and the small area processing unit 32 and the difference calculation unit 33 perform processing. The adjustment calculation unit 34 obtains an adjusted product sum value based on the equation (8). The pixel value output unit 35 outputs the adjusted product sum value as the pixel value of the pixel of interest when the input image data is subtractive color mixture data, and when the input image data is additive color mixture data, The pixel value obtained by calculating (9) is output as the pixel value of the target pixel. As a result, the color material amount suppression unit 12 of FIG. 2 can also obtain a toner consumption suppression effect without causing a sense of incongruity in the halftone area or continuous tone area.

  As in the case of the fourth embodiment, the size of the high brightness filter is not necessarily the same as the size of the large area filter 51 or the small area filter 52.

Further, as the region separation processing in the preprocessing unit 11, for example, the method described in JP-A-2002-232708 can be used. In this method, a maximum density difference that is a difference between a minimum density value and a maximum density value in an n × m block (for example, a 15 × 15 block) including a target pixel and an absolute value of a density difference between adjacent pixels are calculated. By calculating the total density busyness, which is the sum, and comparing the maximum density difference and the total density busyness with a plurality of predetermined thresholds, the background area / continuous tone area and the character edge area / halftone area are It is to be determined. Note that the determination is made based on the characteristics shown in the following (11) to (14).
(11) In the density distribution of the base region, the density change is usually small. Therefore, both the maximum density difference and the total density busyness are very small in the base area.
(12) The density distribution in the continuous tone region has a smooth density change. Therefore, in the continuous tone region, the maximum density difference and the total density busyness are both small and slightly larger than the background region.
(13) In the halftone dot region, the maximum density difference varies, but since there are density changes as many as the number of halftone dots, the ratio of the total density busyness to the maximum density difference increases. Therefore, when the total density busyness is larger than the product of the maximum density difference and the character / halftone dot determination threshold (one of the plurality of thresholds), it can be determined that the pixel is a halftone pixel.
(14) In the density distribution of the character area, the maximum density difference is large, and the total density busyness increases accordingly. However, since the density change in the character area is less than that in the halftone area, the total density busyness of the character area is smaller than the total density busyness of the halftone area. Therefore, when the total density busyness is smaller than the product of the maximum density difference and the character / halftone dot determination threshold, it is possible to determine that the pixel is a character edge pixel.

  Next, an example of the contents of the region separation process will be described. A comparison between the calculated maximum density difference and the maximum density difference threshold and a comparison between the calculated total density busyness and the total density busyness threshold are performed. When the maximum density difference is smaller than the maximum density difference threshold and the total density busyness is smaller than the total density busyness threshold, it is determined that the target pixel is a pixel in the background area or the continuous tone area, and so on. Otherwise, it is determined that the pixel is in the character / halftone area. In addition, when it is determined that the pixel is a character / halftone area pixel, the calculated total density busyness is compared with a value obtained by multiplying the maximum density difference by the character / halftone determination threshold value to obtain the total density busyness. If it is smaller, it is determined as a pixel in the character edge region, and if the total density busyness is larger, it is determined as a pixel in the halftone dot region.

  Note that the adjustment coefficient in the expression (3) of the first embodiment may be changed according to the type of the image area determined by the preprocessing unit 11.

[About copiers]
The color material amount suppression unit described above may be applied to an image processing apparatus provided in a copying machine. This point will be described below with reference to FIG.

The digital color copying machine 100 includes a color image input device 101, a color image processing device 102, and a color image output device 103. Hereinafter, the digital color copying machine 100, the color image input apparatus 101, the color image processing apparatus 102, and the color image output apparatus 103 are respectively referred to as the copying machine 100, the image input apparatus 101, the image processing apparatus 102, and the image output apparatus 103. Called.

  The image input apparatus 101 includes a scanner unit including a device that converts optical information such as a CCD into an electrical signal, and outputs a reflected light image from the document as an RGB analog signal.

  An analog signal read by the image input device 101 is converted into an A / D conversion unit 104, a shading correction unit 105, an input tone correction unit 106, a region separation processing unit 107, and a color material amount suppression unit in the image processing device 102. 12a, a color correction unit 109, a black generation and under color removal unit 110, a spatial filter processing unit 111, an output gradation correction unit 112, and a gradation reproduction processing unit 113, which are sent in this order, and are output as CMYK digital color signals as image output devices 103.

  The A / D conversion unit 104 converts RGB analog signals into digital signals. The shading correction unit 105 performs image input device 101 on the digital RGB signals sent from the A / D conversion unit 104. A process for removing various distortions generated in the illumination system, imaging system, and imaging system is performed. In addition, the shading correction unit 105 adjusts the color balance, and at the same time, performs processing for converting the signal such as a density signal into a signal that can be easily handled by the image processing system employed in the image processing apparatus 102.

  The input tone correction unit 106 performs image quality adjustment processing such as background density removal and contrast on the RGB signal from which various distortions have been removed by the shading correction unit 105. The region separation processing unit 107 separates each pixel in the input image into one of a character region, a halftone dot region, and a photographic region from the RGB signal. Based on the separation result, the region separation processing unit 107 transmits a region identification signal indicating which region the pixel belongs to to the black generation and under color removal unit 110, the spatial filter processing unit 111, and the gradation reproduction processing unit 113. In addition to the output, the RGB signal sent from the input tone correction unit 106 is transferred to the subsequent color material amount suppression unit 12a as it is.

  Similar to the color material amount suppression unit 12, the color material amount suppression unit 12 a uses the large area filter 51 and the small area filter 52 to perform the process shown in FIG. 3 when the save mode is selected from the operation panel of the copying machine 100. The processed image data is sent to the subsequent color correction unit 109. Further, the color material amount suppression unit 12 transfers the image data as it is to the color correction unit 109 when the toner save mode is not selected.

  As shown in FIG. 13, the image data input to the color material amount suppression unit 12a is always RGB image data. Therefore, the color material amount suppression unit 12a may be set so that S3 and S4 in FIG. 3 are not used and the process proceeds to S6 after S2.

  Further, the color material amount suppression unit 12a may be configured to perform the process of FIG. 8 using the first weighting filter 53 or the second weighting filter 54 of FIG.

  The color correction unit 109 performs a process of removing color turbidity based on the spectral characteristics of the CMY color material including unnecessary absorption components in order to achieve faithful color reproduction. In the color correction unit 109, the RGB signals are converted into CMY signals.

  The black generation and under color removal unit 110 generates black (K) signals from the CMY three-color signals after color correction, and subtracts the K signals obtained by black generation from the original CMY signals to generate new CMY signals. The process to generate is performed. As a result, the CMY three-color signal is converted into a CMYK four-color signal.

  The spatial filter processing unit 111 performs spatial filter processing using a digital filter on the image data of the CMYK signal input from the black generation and under color removal unit 110 to correct the spatial frequency characteristics. As a result, blurring of the output image and deterioration of graininess can be reduced.

  In addition, the color material amount suppression unit 12a is not particularly provided, and the spatial filter processing unit 111 may perform the processing of the color material amount suppression unit (the process of FIG. 3). In this case, when the toner save mode is designated, the corresponding filter coefficient is set to be used. Then, after the filter processing is performed, enhancement or smoothing processing is performed based on the region identification signal.

  As shown in FIG. 13, the image data input to the spatial filter processing unit 111 is always CMYK image data. Therefore, when the processing of the color material amount suppression unit is performed in the spatial filter processing unit 111, S3, S6, and S7 in FIG. 3 may not be used, and the process may be set to always shift to S4 after S2. .

  The output tone correction unit 112 performs output tone correction processing according to the output characteristic value of the image output device 103 on the CMYK signal that has been subjected to the spatial filter processing. The gradation reproduction processing unit 113 executes gradation reproduction processing for finally processing the image so that each gradation can be reproduced by separating the image into pixels.

  In addition, similar to the spatial filter processing unit 111, the gradation reproduction processing unit 113 performs predetermined processing to be described later on the image data of the CMYK signal based on the region identification signal. For example, in a region determined as a character by the region separation processing unit 107, a filter having a large high-frequency component enhancement amount is used as a spatial filter in the spatial filter processing unit 111 in order to improve the reproducibility of characters. At the same time, the gradation reproduction processing unit 113 performs binarization or multi-value processing using a high-resolution screen suitable for reproducing high-frequency components.

  In addition, with respect to the region separated into halftone dots by the region separation processing unit 107, the spatial filter processing unit 111 performs low-pass filter processing for removing the input halftone component. For the region separated into photographs by the region separation processing unit 107, the gradation reproduction processing unit 113 performs binarization or multi-value processing on the screen with an emphasis on gradation reproducibility.

  The image data subjected to the above-described processes is temporarily stored in the storage device, read at a predetermined timing, and sent to the image output device 103.

  The image output device 103 forms an image of image data on a recording medium such as paper. For example, a color printer using an electrophotographic method or an inkjet method can be used, but the image output device 103 is not particularly limited. No. The above processing is controlled by a CPU (Central Processing Unit) (not shown).

  Further, the color material amount suppression unit described above may be applied to an image processing apparatus provided in a digital color multifunction peripheral having a copier function, a printer function, a facsimile transmission function, a scan to e-mail function, and the like. The digital color multifunction peripheral may further include a communication device including a modem or a network card, for example.

  Also, when a facsimile transmission is performed in a digital color multifunction peripheral, if a transmission procedure with the other party is performed by a modem and a transmission ready state is secured, image data compressed in a predetermined format (read by a scanner) Image data) is read from the memory. Then, the image data read from the memory is subjected to necessary processing such as changing the compression format and sequentially transmitted to the other party via the communication line.

  Further, when receiving a facsimile in the digital color multifunction peripheral, the CPU receives the image data transmitted from the other party while performing a communication procedure, and inputs it to the image processing apparatus. In the image processing apparatus, the received image data is decompressed by a compression / decompression processing unit (not shown). The decompressed image data is subjected to rotation processing and resolution conversion processing as necessary. Thereafter, output gradation correction processing and gradation reproduction processing are performed on the image data, and an image of the image data subjected to these processing is output (printed) by an image output device (printer).

  The digital color multi-function peripheral can also perform data communication with a computer or other digital multi-function peripheral connected to the network via a network card or a LAN cable. Further, the color material amount suppression unit described above may be applied to an image processing apparatus of a multifunction machine that performs monochrome printing, or may be applied to an image processing apparatus of a single facsimile communication apparatus.

[About the printer]
The color material amount suppression unit described above may be applied to an image processing apparatus provided in a color printer. FIG. 14 is a block diagram illustrating a color printer including an image processing apparatus to which the above-described color material amount suppression unit is applied and a terminal device connected to the printer.

  The terminal device 200 in FIG. 14 is used by a user of the color printer 300, and is a computer in which a printer driver 202 for operating the color printer 300 is installed in addition to application software 201 such as image editing software. is there.

  Image data created by the terminal device 200 or image data held in the terminal device 200 is converted into image data (page description language data) in the PDL format by the printer driver 202. The image data in the PDL format is transmitted to the color printer 300. An example of page description language data is Post Script.

  The color printer 300 is an electrophotographic printing apparatus, and includes an image processing apparatus 310 and a print engine 320 as shown in FIG. The color printer 300 is not limited to an electrophotographic printing apparatus, but may be an inkjet printing apparatus.

  The image processing device 310 converts the image data in the PDL format transmitted from the terminal device 200 into image data that can be handled by the print engine 320. Then, the image processing apparatus 310 sends the converted image data to the print engine 320. When image data is sent from the image processing apparatus 310, the print engine 320 forms an image corresponding to the image data on a predetermined sheet (paper, OHP, etc.).

  Next, details of the image processing apparatus 310 will be described. As illustrated in FIG. 14, the image processing apparatus 310 includes a raster data generation unit 311, a color material amount suppression unit 12 b, a color correction unit 313, and a halftone processing unit 314.

The raster data generation unit 311 generates image data (data indicating gradation values for each pixel) that can be handled by each unit in the subsequent stage and tag data indicating the type of the image area from the input PDL format image data. The generated image data and tag data are sent to the subsequent color material amount suppression unit 12b. Here, it is assumed that RGB is specified in the input PDL format image data, and the image data output from the raster data generation unit 311 is also RGB image data. Further, the raster data generation unit 311 performs processing such as resolution conversion processing according to the output paper size as necessary.

  Similar to the color material amount suppression unit 12, the color material amount suppression unit 12 b performs processing shown in FIG. 3 using the large region filter 51 and the small region filter 52 when the save mode is selected from the operation panel of the copying machine 100. The processed image data is sent to the color correction unit 313 at the subsequent stage. Further, the color material amount suppression unit 12b transfers the image data as it is to the color correction unit 313 when the toner save mode is not selected. In the configuration of FIG. 14, since RGB image data is input to the color material amount suppression unit 12b, the color material amount suppression unit 12b executes S6 and S7 without executing S4 of FIG. It is supposed to be.

  Further, the color material amount suppression unit 12b may be configured to perform the process of FIG. 8 using the first weighting filter 53 or the second weighting filter 54 of FIG.

  When the RGB signal is sent from the color material amount suppression unit 12b, the color correction unit 313 performs color correction processing for removing color turbidity based on the spectral characteristics of the CMY color material including unnecessary absorption components. This color correction process converts the RGB signal into a CMY signal. Further, the color correction unit 313 performs processing for generating a black (K) signal from the CMY signal after color correction processing, and processing for generating a new CMY signal by subtracting the K signal from the original CMY signal. . Thus, the CMY signal is converted into a CMYK signal. Then, the CMYK signal output by the color correction unit 313 is sent to the halftone processing unit 314 at the subsequent stage.

  The halftone processing unit 314 performs an output tone correction process based on the output characteristics of the print engine 320 for the CMYK image data, and can finally reproduce the respective tone by separating the image into pixels. Gradation reproduction processing is performed. Again, the processing may be switched based on the tag data. For example, for a natural image (photo) region, binarization or multi-value processing is performed on a screen with an emphasis on gradation reproducibility.

  The image data that has been processed by the halftone processing unit 314 is sent to the print engine 320, and the print engine 320 prints an image of the image data on a sheet or the like.

  In the above configuration, the color correction unit 313 is arranged at the subsequent stage of the color material amount suppressing unit 12b. However, the color correction unit 313 is arranged at the subsequent stage of the raster data generating unit 311 and before the color material amount suppressing unit 12b. May be. However, in this case, CMYK image data is input to the color material amount suppression unit 12b, and the color material amount suppression unit 12b executes S4 without executing S6 and S7 of FIG.

  Next, data handled by the terminal device 200 and the image processing device 310 will be described. FIG. 15A shows an example of an image created by the terminal device 200, which is configured as an aggregate of various areas such as text, graphics, and natural images (photos). FIG. 15B shows an example of tag data generated by the raster data generation unit 311. FIG. 16 shows the structure of PDL data in which the image content of FIG. 15A is described in a page description language. It is a figure.

  In FIG. 16, reference numeral 441 denotes data indicating a text area, which is data for each pixel indicating a character shape without color information. 442 is data indicating a natural image area, and 443 is data indicating a graphic area such as a graph / graphic (in the case of 443, the graphic area can be determined from the presence of a drawing command such as linnet or closepath fill).

  Each piece of data in FIG. 16 includes typeface information, region attributes, starting position information, size, and color information. The area determination and area size are determined from these data, and tag data is generated.

  Further, as shown in FIG. 15B, the natural image area is a rectangular area having the points A, B, C, and D as vertices. In contrast, in FIG. 16, in the data 442 of the natural image area, the coordinates of the starting point A are (50, 300) and the sizes are 100, 200. Therefore, the B, C, and D coordinates of the rectangular region are B (249, 300), C (50, 399), and D (249, 399). The origin is the point O in FIG.

  Similarly, in the graphic area, the coordinates of F, G, and H can be obtained by looking at the command for the starting point E (50, 550), respectively. Note that “0 250 translate” of the reference symbol 443 means that the image area is moved 0 in the horizontal direction and 250 in the vertical direction with respect to the starting point of the image area.

[About the program]
Each block of the image processing apparatus 10 in FIG. 1 may be configured by hardware logic, or may be realized by software using a CPU as follows.

  That is, the image processing apparatus 10 includes a CPU (central processing unit) that executes instructions of a control program that realizes each function, a ROM (read only memory) that stores the program, and a RAM (random access memory) that expands the program. And a storage device (recording medium) such as a memory for storing the program and various data. An object of the present invention is a recording medium on which a program code (execution format program, intermediate code program, source program) of a control program of the image processing apparatus 10 which is software for realizing the functions described above is recorded so as to be readable by a computer. This can also be achieved by supplying the image processing apparatus 10 and reading and executing the program code recorded on the recording medium by the computer (or CPU or MPU). The recording medium on which the program is recorded is portable.

  The recording medium may be a program medium composed of a memory such as a ROM because processing is performed by a microcomputer, or a program reading device is provided as an external storage device. It may be a program medium that can be read by being inserted.

  In any case, the stored program may be accessed and executed by the microprocessor. Alternatively, in any case, the program may be read, the program may be downloaded to a program storage area of a microcomputer, and the program may be executed. It is assumed that this download program is stored in the main device in advance.

  Examples of the recording medium include tapes such as magnetic tapes and cassette tapes, magnetic disks such as floppy (registered trademark) disks / hard disks, and disks including optical disks such as CD-ROM / MO / MD / DVD / CD-R. Card system such as IC card, IC card (including memory card) / optical card, or semiconductor memory system such as mask ROM / EPROM / EEPROM / flash ROM.

Further, the image processing apparatus 10 according to the present embodiment may have a system configuration capable of connecting to a communication network including the Internet. In this case, the recording medium is fluid so as to download the program code from the communication network. Or a medium carrying the program code. When the program code is downloaded from the communication network in this way, the program code for downloading may be stored in the main apparatus in advance or installed from another recording medium. . The embodiment of the present invention can also be realized in the form of a computer data signal embedded in a carrier wave in which the program code is embodied by electronic transmission.

  Furthermore, the present embodiment includes an image input device such as a flatbed scanner, a film scanner, and a digital camera, a computer that processes each block of the image processing device 10 by loading a predetermined program, and a processing result of the computer. It may be a system constituted by an image display device such as a CRT display or a liquid crystal display for displaying, and a printer for outputting the processing result of the computer to paper. In addition, this system may be provided with a network card, a modem, or the like as a communication means for connecting to a server or the like via a network.

  The present invention is not limited to the above-described embodiments, and various modifications are possible within the scope shown in the claims, and embodiments obtained by appropriately combining technical means disclosed in different embodiments. Is also included in the technical scope of the present invention.

  The present invention is suitable for an image forming apparatus such as a printer, a copier, a multifunction peripheral, and a facsimile machine, and an image processing apparatus that processes image data handled by the image forming apparatus.

1 Printing system (image forming device)
10 image processing apparatus 11 pre-processing unit (determination processing unit)
12 Color material amount suppression unit 12a Color material amount suppression unit 12b Color material amount suppression unit 31 Large region processing unit 32 Small region processing unit 35 Pixel value output unit (pixel value processing unit)
51 Large Area Filter 52 Small Area Filter 53 First Weighting Filter 54 Second Weighting Filter 72 Product Sum Value Calculation Unit 73 Pixel Value Output Unit (Pixel Value Processing Unit)
100 Copying machine (image forming device)
300 Printer (image forming device)
310 Image processing apparatus

Claims (15)

Processing image data handled in an image forming apparatus having a normal mode for printing an image of image data using a color material and a save mode for printing the image while suppressing the amount of the color material used compared to the normal mode An image processing apparatus that
In the save mode, a color material amount suppression unit that performs image processing on the image data so that the amount of the color material used is suppressed than in the normal mode;
The color material amount suppression unit, when a solid part is included in the image of the image data, reduces the density of the part stepwise from the outline of the part toward the inside. apparatus. The image data is data including a pixel value indicating the density of a pixel, and the pixel value is set so that the value decreases as the density decreases.
The color material amount suppression unit weights the pixel values of each pixel in a block including a plurality of pixels including the target pixel using a weighting filter, and a product-sum value that is a sum of the weighted pixel values Is a pixel value such that the lower the density is, the lower the pixel value of the pixel of interest is.
The block has a first area including the pixel of interest and a second area which is an area arranged to surround the first area and includes pixels adjacent to pixels on the outer periphery of the block. And
The weighting filter defines a weighting coefficient to be applied to the pixel value of each pixel in the block, and the weighting coefficient to be applied to the pixel value of each pixel in the second area is a value of zero or less, 2. The image processing according to claim 1, wherein a sum of weighting coefficients applied to pixel values of pixels included in the first area and the second area is set to be zero or substantially zero. apparatus. The image data is data including a pixel value indicating the density of a pixel, and the pixel value is set such that the lower the density, the larger the value.
The color material amount suppression unit weights the pixel values of each pixel in a block including a plurality of pixels including the target pixel using a weighting filter, and a product-sum value that is a sum of the weighted pixel values Is a pixel value such that the lower the density is, the lower the pixel value of the pixel of interest is.
The block has a first area including the pixel of interest and a second area which is an area arranged to surround the first area and includes pixels adjacent to pixels on the outer periphery of the block. And
The weighting filter defines a weighting coefficient to be applied to the pixel value of each pixel in the block, and the weighting coefficient to be applied to the pixel value of each pixel in the second region is a value of zero or more. 2. The image processing according to claim 1, wherein a sum of weighting coefficients applied to pixel values of pixels included in the first area and the second area is set to be zero or substantially zero. apparatus. The color material amount suppression unit includes a similarity determination unit that determines whether the color of a reference pixel other than the target pixel in the block is similar to the color of the target pixel,
The pixel value of a reference pixel having a color determined to be dissimilar to the color of the target pixel is converted into a pixel value indicating a minimum density, and the weighting is performed on the converted pixel value. Item 4. The image processing device according to Item 2 or 3. A determination processing unit that determines whether each image region included in the image of the image data corresponds to a character region, a graphic region, or a photo region;
The color material amount suppression unit performs processing using the weighting filter on an image region determined as a character region or a graphic region by the determination processing unit, and an image determined as a photographic region by the determination processing unit. 5. The image processing apparatus according to claim 2, wherein a process using the weighting filter is not performed on a region. 6. A determination processing unit that determines whether each image region included in the image of the image data corresponds to a character region, a halftone dot region, or a continuous tone region;
The color material amount suppression unit performs processing using the weighting filter on the image region determined as the character region by the determination processing unit, and determines the halftone dot region or the continuous tone region by the determination processing unit. 5. The image processing apparatus according to claim 2, wherein a process using the weighting filter is not performed on the image area that has been processed. 6. The image data is data including a pixel value indicating the density of a pixel, and the pixel value is set so that the value decreases as the density decreases.
The color material amount suppression unit includes a small region processing unit that weights the pixel value of each pixel in a small region including a plurality of pixels including a target pixel, and includes the small region and a pixel that is smaller than the small region. A large area processing unit that weights the pixel values of each pixel in the large area having a large number, and the large area from the first product sum value that is the sum of the pixel values weighted by the small area processing unit A pixel value output unit that outputs a pixel value having a lower density as a pixel value of the target pixel as a difference value obtained by subtracting a second product sum value that is a sum of pixel values weighted by the processing unit is smaller. ,
The small region processing unit performs weighting using a small region filter that defines weighting coefficients to be applied to pixel values of the pixels belonging to the small region, and the large region processing unit performs the weighting of each pixel belonging to the large region. Weighting is performed using a large area filter that defines each weighting coefficient to be applied to the pixel value,
The small region filter and the large region filter are set so that a sum of weighting coefficients of the small region filter is equal to or substantially equal to a sum of weighting coefficients of the large region filter. Item 8. The image processing apparatus according to Item 1. The image data is data including a pixel value indicating the density of a pixel, and the pixel value is set such that the lower the density, the larger the value.
The color material amount suppression unit includes a small region processing unit that weights the pixel value of each pixel in a small region including a plurality of pixels including a target pixel, and includes the small region and a pixel that is smaller than the small region. A large area processing unit for weighting the pixel values of each pixel in the large area having a large number, and the second area from the second product sum value that is the sum of the pixel values weighted by the large area processing unit A pixel value output unit that outputs a pixel value having a lower density as the pixel value of the target pixel as the difference value obtained by subtracting the first product sum value that is the sum of the pixel values weighted by the processing unit is smaller. ,
The small region processing unit performs weighting using a small region filter that defines weighting coefficients to be applied to pixel values of the pixels belonging to the small region, and the large region processing unit performs the weighting of each pixel belonging to the large region. Weighting is performed using a large area filter that defines each weighting coefficient to be applied to the pixel value,
The small region filter and the large region filter are set so that a sum of weighting coefficients of the small region filter is equal to or substantially equal to a sum of weighting coefficients of the large region filter. Item 8. The image processing apparatus according to Item 1. The color material amount suppression unit includes a similarity determination unit that determines whether the color of a reference pixel other than the target pixel in the small region and the large region is similar to the color of the target pixel,
The large region processing unit and the small region processing unit convert a pixel value of a reference pixel having a color determined to be dissimilar to the color of the target pixel into a pixel value indicating a minimum density, and the converted pixel value The image processing apparatus according to claim 7, wherein the weighting is performed using the image processing apparatus. A determination processing unit that determines whether each image region included in the image of the image data corresponds to a character region, a graphic region, or a photo region;
The color material amount suppression unit performs processing using the small region filter and the large region filter on the image region determined as the character region or the graphic region by the determination processing unit, and the determination processing unit performs a photograph. The image processing apparatus according to claim 7, wherein processing using the small region filter and the large region filter is not performed on an image region determined to be a region. A determination processing unit that determines whether each image region included in the image of the image data corresponds to a character region, a halftone dot region, or a continuous tone region;
The color material amount suppression unit performs processing using the small region filter and the large region filter on the image region determined to be a character region by the determination processing unit, and performs a halftone dot region or an image region by the determination processing unit. The image processing according to any one of claims 7 to 9, wherein processing using the small region filter and the large region filter is not performed on an image region determined to be a continuous tone region. apparatus.   2. An image forming apparatus comprising: a normal mode for printing an image of image data using a color material; and a save mode for printing the image while suppressing the amount of the color material used compared to the normal mode. An image forming apparatus comprising the image processing apparatus according to any one of items 1 to 11. Processing image data handled in an image forming apparatus having a normal mode for printing an image of image data using a color material and a save mode for printing the image while suppressing the amount of the color material used compared to the normal mode An image processing method for
In the save mode, a color material amount suppression step of performing image processing on the image data so that the amount of the color material used is suppressed than in the normal mode,
The color material amount suppression step is a step in which, when a solid portion is included in the image of the image data, the density of the portion is gradually decreased from the contour of the portion toward the inside. Image processing method.   The program which makes a computer function as each part of the image processing apparatus of any one of Claim 1 to 11.   The computer-readable recording medium which recorded the program of Claim 14.

Images