JP2019114845A - Printer controller and computer program - Google Patents

Abstract

To improve the appearance of a print image, by compensating for the intensity of an edge appropriately.SOLUTION: A printer controller for controlling a print execution part includes: an image acquisition part for acquiring object image data; a condition acquisition part for acquiring condition information indicating print conditions for printing a print image based on an object image; a calculation part for calculating a feature amount related to variation of the values of multiple peripheral pixels by using the values of the multiple peripheral pixels located on the periphery of a target pixel in the object image; a determination part for determining correction processing to be applied to the target pixel on the basis of the feature amount and the condition information, and correcting the intensity of an edge in the object image including the target pixel; a generation part for executing generation processing including the determined correction processing for the object image data, and generating print image data indicating the print image; and a print control part for controlling the print execution part to print the print image according to the print image data.SELECTED DRAWING: Figure 8

Description

  The present specification relates to image processing for generating print image data using target image data.

  Patent Document 1 discloses image processing that a multifunction peripheral executes at the time of printing. In this image processing, image processing is disclosed in which the correction strength of edge emphasis is changed according to the magnitude and frequency of the fluctuation of pixel signal values in peripheral pixel groups centering on the processing target pixel. According to this image processing, it is possible to reduce the occurrence of adverse effects that may occur due to edge enhancement, for example, moiré.

JP, 2008-11268, A

  However, if the degree of correction of the edge intensity in the image can be determined more appropriately, the appearance of the printed image can be further improved.

  The present specification discloses a technique that can improve the appearance of a printed image by appropriately correcting the edge strength.

  The technology disclosed in the present specification is made to solve at least a part of the above-mentioned problems, and can be realized as the following application example.

Application Example 1 A printing control apparatus that controls a printing execution unit that prints an image using a color material,
An image acquisition unit for acquiring target image data indicating a target image, a condition acquisition unit for acquiring condition information indicating a printing condition for printing a print image based on the target image, and a periphery of a target pixel in the target image Calculating the feature amount related to the variation of the values of the plurality of peripheral pixels using the values of the plurality of peripheral pixels located on the target pixel, based on the feature amount and the condition information; A determination unit that determines the correction process, which is a correction process to be applied and is a process of correcting an intensity of an edge in the target image including the pixel of interest; A generation unit that executes generation processing including correction processing to generate print image data indicating the print image; and a print control unit that causes the print execution unit to print the print image according to the print image data. Obtain, print control apparatus.

  According to the above configuration, the value of the pixel of interest is corrected by the correction processing determined based on the condition information indicating the printing condition, in addition to the feature amount related to the fluctuation of the values of the plurality of peripheral pixels. As a result, it is possible to correct the edge strength in the image according to the printing conditions. Therefore, the appearance of the printed image can be improved by appropriately correcting the edge intensity in the image.

  The technology disclosed in the present specification can be realized in various forms, and for example, a multifunction machine, a scanner, a printer, an image processing method, a function of these devices, or a computer for realizing the above method. The present invention can be realized in the form of a program, a recording medium recording the computer program, and the like.

FIG. 2 is a block diagram showing configurations of a terminal device 100 as a print control device and a printer 300 in the embodiment. 5 is a flowchart of print processing. It is a figure which shows an example of the target image used by a present Example. 5 is a flowchart of correction processing. It is an explanatory view of calculation of a correction parameter. It is a figure which shows an example of an edge emphasis filter. It is a figure which shows an example of a smoothing filter. It is a figure which shows an example of filter selection table FT1 of 1st Example. It is a figure which shows an example of filter selection table FT2 of 2nd Example. It is a figure which shows an example of filter selection table FT3 of 3rd Example. It is a figure which shows an example of filter selection table FT4 of a modification. It is a figure which shows an example of filter selection table FT5 of a modification. It is a figure which shows an example of filter selection table FT6 of a modification.

A. Example:
A-1: Configuration of Print Control Device Next, an embodiment will be described based on an example. FIG. 1 is a block diagram showing the configuration of a terminal device 100 as a print control device and a printer 300 in the embodiment. The terminal device 100 and the printer 300 are communicably connected to each other by wired or wireless communication.

  The terminal device 100 is a computer used by the user of the terminal device 100, and is, for example, a personal computer or a smartphone. The terminal device 100 includes a CPU 110 as a controller of the terminal device 100, a volatile storage device 120 such as a RAM, a non-volatile storage device 130 such as a hard disk drive or a flash memory, a display unit 140 such as a liquid crystal display, a liquid crystal panel And a communication interface (IF) 170 and a printer 300. The terminal device 100 is communicably connected to an external device such as the printer 300 via the communication interface 170. The communication interface 170 is, for example, a USB interface, a wired LAN interface, or an IEEE 802.11 wireless interface.

  The volatile storage device 120 provides a buffer area for temporarily storing various intermediate data generated when the CPU 110 performs processing. The non-volatile storage device 130 stores a computer program PG. The volatile storage device 120 and the non-volatile storage device 130 are internal memories of the terminal device 100.

  The computer program PG can be provided, for example, as downloaded from a server connected via the Internet. Alternatively, the computer program PG may be provided in a form stored in advance in the non-volatile storage device 130 when the terminal device 100 is manufactured, or in a form recorded on a CD-ROM or the like. The CPU 110 functions as a printer driver for controlling the printer 300 by executing the computer program PG. The CPU 110 executes, for example, print processing described later as a printer driver.

  In the present embodiment, the printer 300 is an apparatus that prints an image by using an ink as a coloring material and forming dots on a printing medium such as a sheet according to an inkjet method. The printer 300 of this embodiment is an inkjet printer that performs printing using ink as a color material. The printer 300 according to this embodiment performs color printing using four types of ink, cyan (C), magenta (M), yellow (Y), and black (K).

A-2: Printing Process FIG. 2 is a flowchart of the printing process. The printing process is a process of causing the printer 300 to print a print image based on a target image using target image data indicating the target image. The printing process is executed by the CPU 110 of the terminal device 100. The printing process is started, for example, when the terminal device 100 acquires a print instruction of the user via the operation unit 150.

  In S10, the CPU 110 acquires target image data indicating a target image to be used for printing. The target image data is, for example, image data selected from among a plurality of image data stored in the non-volatile storage device 130 based on user's designation. The target image data in this embodiment is, for example, read image data generated by a scanner or a digital camera (not shown) optically reading a document using an image sensor. Instead of this, for example, the target image data may be image data created by an application program such as document creation and image creation.

  The target image data acquired in this embodiment includes the values of a plurality of pixels, and each of the values of the plurality of pixels represents the color of the pixel by an RGB value. That is, the target image data is RGB image data. The RGB values of one pixel include, for example, three component values of red (R), green (G) and blue (B) (hereinafter also referred to as R value, G value, B value) . If the target image data to be acquired is not RGB image data, conversion processing such as rasterization processing is performed on the target image data, for example, to convert it into RGB image data.

  FIG. 3 is a view showing an example of a target image used in the present embodiment. The target image OI1 includes a background BG, and an object such as a character TX or a photo IM disposed on the background BG.

  At S15, the CPU 110 acquires printing condition information. In the first embodiment, at least material information indicating the material of a sheet for printing a print image is acquired as the printing condition information. The material information is included, for example, in printing condition information input together with a print instruction via a UI screen (not shown). The material of the sheet assumed in this embodiment is two types of plain paper and glossy paper. Glossy paper is characterized in that ink bleeding is less likely to occur compared to plain paper.

  In S20 to S30, the CPU 110 executes generation processing including the correction processing of S20 on the target image data to generate print image data. In S20, the CPU 110 executes correction processing on the target image data to generate corrected target image data. The correction process is a process for improving the appearance of the print image by executing the correction process according to the printing conditions (in the present embodiment, the material of the sheet). The correction process of the present embodiment is a process of applying the filter process to each pixel in the target image. The correction process will be described later.

  In S25, the CPU 110 executes color conversion processing using a color conversion profile on the corrected target image data (RGB image data in this embodiment), and a CMYK image representing the color of each pixel with the CMYK value Generate data. The CMYK values include a plurality of component values (C value, M value, Y value, K value in the present embodiment) corresponding to colors of the plurality of types of ink used in printing (in the present embodiment, CMYK) It is a color value. In this embodiment, the R value, the G value, the B value, the C value, the M value, the Y value, and the K value are each 8-bit (256 gradations) values. The color conversion profile is, for example, a known lookup table that defines the correspondence between RGB values and CMYK values.

  In S30, the CPU 110 executes halftone processing on the generated CMYK image data to generate dot data as print image data. The dot data represents the dot formation state for each pixel and for each color material. The value of each pixel included in the dot data indicates, for example, any of the formation states of four dots of “large dot”, “medium dot”, “small dot”, and “no dot”. Instead of this, the value of each pixel included in the dot data may indicate either of the formation state of two dots of “dot present” and “dot absent”. For the halftoning process, for example, a process according to an error diffusion method is used.

In S35, the CPU 110 generates a print job using dot data. For example, the CPU 110 executes a process of rearranging dot data in the order used when printing using the printer 300 and a process of adding a printer control code and a data identification code to the dot data. As a result, a print job interpretable by the printer 300 is generated. In S40, the CPU 110 transmits the generated print job to the printer 300. The printer 300 prints a print image indicated by print image data (dot data) in accordance with the print job transmitted from the terminal device 100.
Ru.

A-3: Correction Process The correction process of S20 of FIG. 2 will be described. As described above, the correction process is a process of applying the filter process to each pixel in the target image to generate corrected target image data. FIG. 4 is a flowchart of the correction process. FIG. 5 is an explanatory diagram of calculation of the correction parameter.

  In S100, the CPU 110 selects one target pixel CP from among the plurality of pixels in the target image OI. In S105, the CPU 110 sets a peripheral area AA including one target pixel CP. As shown in FIGS. 5A and 5B, in the present embodiment, the peripheral area AA is a rectangular area of 7 vertical pixels × 7 horizontal pixels centered on the pixel of interest CP. The plurality of pixels excluding the target pixel CP in the peripheral area AA are also referred to as a plurality of peripheral pixels SP located around the target pixel CP. In the example of FIGS. 5A and 5B, the peripheral area AA includes one target pixel CP and 48 peripheral pixels SP. As a modification, for the size of the peripheral area AA, any other size, for example, a size of 5 pixels vertically × 5 pixels horizontally, 9 pixels vertically × 9 pixels horizontally, etc. may be adopted.

  In S110, the CPU 110 changes the values of the plurality of peripheral pixels SP using the value of the target pixel CP (RGB values in this embodiment) and the values of the plurality of peripheral pixels SP in the peripheral area AA. The variation parameter AP, which is a feature quantity relating to In the present embodiment, the fluctuation speed VS is calculated as the fluctuation parameter AP. The fluctuation speed VS is a correction parameter indicating the degree to which the value of the pixel fluctuates with respect to the fluctuation of the position of the pixel in the peripheral area AA.

  Specifically, the CPU 110 selects seven peripheral pixels SP including the pixel of interest CP, which are arranged along the four directions of the vertical direction, the horizontal direction, and the two oblique directions. Do. For example, a pixel group PL1 shown in FIG. 5A indicates seven peripheral pixels SP in the horizontal direction, and a pixel group PL2 indicates seven peripheral pixels SP in the vertical direction. Pixel groups PL3 and PL4 shown in FIG. 5B respectively indicate seven peripheral pixels SP in the oblique direction.

The CPU 110 calculates the luminance L of the selected seven pixels. The luminance L is performed, for example, in accordance with a predetermined arithmetic expression. In the present embodiment, the following arithmetic expression is used.
L = (0.25R + 0.5G + 0.25B) / 255

  FIG. 5C shows an example of the luminance L of seven pixels in one direction. Among the seven pixels, “i” is attached as an identifier to the noticed pixel CP, and each of the six peripheral pixels SP is sequentially added as an identifier (i-3) from the left side of FIG. 5C. To (i-1) and (i + 1) to (i + 3) are attached. Hereinafter, a code attached with an identifier at the end indicates a value related to the pixel attached with the identifier. For example, the luminance L of the pixel (i-1) is expressed as luminance L (i-1).

  The CPU 110 calculates, for each of the four directions, the difference (also referred to as a primary difference ΔL1) of the luminance L of two neighboring pixels SP adjacent to both sides of the pixel of interest CP (pixel i in FIG. 5C). The primary difference ΔL1 (i) of the pixel i is {L (i + 1) −L (i−1)}. The CPU 110 determines the direction in which the absolute value of the first-order difference ΔL1 (i) is maximum as the attention direction.

  The CPU 110 calculates primary differences ΔL1 (i-2) to ΔL1 (i + 2) of the luminance L for each of five pixels (i-2) to (i + 2) of seven pixels in the direction of interest. For example, the primary difference ΔL1 (i-2) of the pixel (i-2) is {L (i-1) −L (i-3)}, and the primary difference ΔL1 (i of the pixel i (target pixel CP) ) Is {L (i + 1) -L (i-1)} as described above. In the example of FIG. 5C, the primary differences ΔL1 (i-2) to ΔL1 (i + 2) of the five pixels (i-2) to (i + 2) are 20, -100, -100, 50, and 50, respectively. It is 150.

  The CPU 110 determines the maximum value of the absolute values of the primary differences ΔL1 of the five pixels (i-2) to (i + 2) in the attention direction as the fluctuation speed VS of the attention pixel CP. In the example of FIG. 5C, the fluctuation speed VS of the pixel of interest CP (pixel i) is the absolute value “150” of the primary difference ΔL1 (i + 2) of the pixel (i + 2).

  In S115, the CPU 110 uses the filter selection table FT1 to select one use filter to be used from the plurality of candidate filters. Note that if different filters are selected in this step, different types of filter processing (correction of the pixel of interest) will be performed in S120 described later, so selecting the filter used is the pixel of interest CP To determine the correction process to be applied.

  In the present embodiment, a total of six types of filters combining two types and three types of sizes are used as candidate filters. The six types of filters are all filters for correcting the intensity of the edge in the target image OI. Two types are an edge emphasizing filter which makes edge strength high, and a smoothing filter which makes edge strength low. The three sizes are "small", "medium" and "large".

  FIG. 6 is a diagram showing an example of the edge emphasis filter. In FIGS. 6A, 6B, and 6C, edge emphasis filters having the sizes "small", "medium", and "large" are shown. The small edge emphasis filter FEs of FIG. 6A defines a correction coefficient (also referred to as a correction value) corresponding to each of the 3 vertical pixels × 3 horizontal pixels. That is, the small edge emphasis filter FEs defines a corresponding correction coefficient for each of the target pixel CP and the eight peripheral pixels SP located around the target pixel CP. For example, in the small edge emphasis filter FEs, the correction coefficient corresponding to the pixel of interest CP is 5, and the four correction coefficients corresponding to four neighboring pixels SP adjacent to the pixel of interest CP vertically and horizontally are −1 The four correction coefficients corresponding to the four peripheral pixels SP located at the upper left, upper right, lower left, and upper left of the target pixel CP are zero. Thus, in addition to the correction coefficient corresponding to the pixel of interest CP, the filter corrects the relative position of the pixel of interest CP with respect to each of the M (M is an integer of 1 or more) peripheral pixels SP and the corresponding correction. It can be said that it is the information which specified the coefficient.

  In the correction using the small edge emphasis filter FEs, values of nine pixels in the filter range including the target pixel CP and the peripheral pixel SP respectively have corresponding coefficients defined in the small edge emphasis filter FEs. By multiplying, nine correction values are calculated. Then, the sum of the nine correction values is calculated as the value of the corrected target pixel CP. As understood from this, the value of the peripheral pixel SP whose corresponding correction coefficient is 0 is not used for correction. For this reason, in the small edge emphasis filter FEs, correction coefficients are specified for eight peripheral pixels SP, but the number of peripheral pixels SP used for correction is four.

  The middle edge emphasizing filter FEm in FIG. 6B defines a correction coefficient corresponding to each of 3 vertical pixels × 3 horizontal pixels. That is, the middle edge emphasizing filter FEm defines corresponding correction coefficients for each of the target pixel CP and eight peripheral pixels SP located around the target pixel CP. For example, in the middle edge emphasizing filter FEm, the correction coefficient corresponding to the pixel of interest CP is 5, and the four correction coefficients corresponding to four neighboring pixels SP adjacent to the pixel of interest CP vertically and horizontally are 0 The four correction coefficients corresponding to the four peripheral pixels SP located at the upper left, upper right, lower left, and upper left of the pixel of interest CP are −1. In the middle edge emphasizing filter FEm, the number of peripheral pixels SP whose corresponding correction coefficient is different from 0 is four. For this reason, in the middle edge emphasizing filter FEm, the number of peripheral pixels SP used for correction is four.

  The large edge emphasis filter FEl shown in FIG. 6C defines correction coefficients corresponding to each of 5 vertical pixels × 5 horizontal pixels. That is, the large edge emphasis filter FEl defines corresponding correction coefficients for each of the target pixel CP and the 24 peripheral pixels SP located around the target pixel CP. For example, in the large edge emphasizing filter FEl, the correction coefficient corresponding to the target pixel CP is 5, and among the 24 peripheral pixels SP, it corresponds to four peripheral pixels SP located at the center of the upper, lower, left, and right sides. The four correction factors are −1, and the 20 correction factors corresponding to the remaining 20 peripheral pixels SP are zero. In the large edge emphasis filter FEl, the number of peripheral pixels SP whose corresponding correction coefficient is different from 0 is four. For this reason, in the large edge emphasis filter FEl, the number of peripheral pixels SP used for correction is four.

  Here, the size of the filter can be indicated by the distance D between the farthest peripheral pixel FP farthest from the target pixel CP among the plurality of peripheral pixels SP used for correction and the target pixel CP. . That is, it can be said that the filter size is larger as the distance D between the farthest peripheral pixel FP and the target pixel CP is larger. Here, the distance Des of the small edge emphasis filter FEs is 1, the distance Dem of the middle edge emphasis filter FEm is SQRT (2), and the distance Del of the large edge emphasis filter FEl is 2. Here, SQRT (a) means the square root of a.

  FIG. 7 is a diagram showing an example of the smoothing filter. The smoothing filter is a filter for smoothing processing that smoothes an image. FIGS. 7A, 7B, and 7C show smoothing filters having the sizes of "small", "medium", and "large". The small smoothing filter FSs of FIG. 7A defines a correction coefficient corresponding to each of 3 vertical pixels × 3 horizontal pixels. That is, the small smoothing filter FSs defines corresponding correction coefficients for each of the target pixel CP and the eight peripheral pixels SP located around the target pixel CP. For example, in the small smoothing filter FSs, the correction coefficient corresponding to the target pixel CP and the eight correction coefficients corresponding to eight peripheral pixels SP surrounding the target pixel CP are all (1/9). In the small smoothing filter FSs, there is no surrounding pixel SP whose corresponding correction coefficient is zero.

  The middle smoothing filter FSm in FIG. 7B defines a correction coefficient corresponding to each of 5 vertical pixels × 5 horizontal pixels. That is, the middle smoothing filter FSm defines corresponding correction coefficients for each of the target pixel CP and the 24 peripheral pixels SP located around the target pixel CP. For example, in the middle smoothing filter FSm, the target pixel CP, four peripheral pixels SP located at the four corners of the middle smoothing filter FSm, and the middle portion of the four sides of the middle smoothing filter FSm rectangle 4 The correction coefficients corresponding to the number of peripheral pixels SP are all (1/9). Then, among the 24 peripheral pixels SP, 16 peripheral pixels SP are excluded except the four peripheral pixels SP located at the above-mentioned four corners and the four peripheral pixels SP located at the central part of the four sides. The corresponding correction coefficients are all zero. For this reason, in the middle smoothing filter FSm, the number of peripheral pixels SP used for correction is eight.

  The large smoothing filter FS1 shown in FIG. 7C defines correction coefficients corresponding to each of the seven vertical pixels and seven horizontal pixels. That is, the large smoothing filter FS1 defines corresponding correction coefficients for each of the target pixel CP and the 48 peripheral pixels SP located around the target pixel CP. For example, in the large smoothing filter FSl, the target pixel CP, four peripheral pixels SP located at the four corners of the large smoothing filter FSl, and the central portion of the four sides of the middle smoothing filter FSm rectangle 4 The correction coefficients corresponding to the number of peripheral pixels SP are all (1/9). Then, forty peripheral pixels SP except for the four peripheral pixels SP located at the above-mentioned four corners and the four peripheral pixels SP located at the central part of the four sides among the forty-eight peripheral pixels SP. The corresponding correction coefficients are all zero. For this reason, in the large smoothing filter FSl, the number of peripheral pixels SP used for correction is eight.

  Here, the size of the filter is the same as that of the above-described edge enhancement filter, of the farthest peripheral pixel FP farthest from the target pixel CP among the plurality of peripheral pixels SP used for correction, and the target pixel CP. It can be indicated by the distance D between them. Here, the distance Dss of the small smoothing filter FSs is SQRT (2), the distance Dsm of the middle smoothing filter FSm is SQRT (8), and the distance Dsl of the large smoothing filter FSl is SQRT (18 ).

  As understood from the above description, since the plurality of filters shown in FIGS. 6 and 7 are different from each other, combinations of the plurality of peripheral pixels SP and the plurality of correction coefficients are different from each other. The small smoothing filter FSs, the medium smoothing filter FSm, and the large smoothing filter FSl are all nine for the number of peripheral pixels SP used for correction, but the farthest peripheral pixels FP and the target pixel CP Because the distance D between them is different, the sizes of the filters are different from each other (FSs <FSm <FSl).

  The larger the size of the edge emphasizing filter in FIG. 6, the higher the level of correction, and the higher the degree of the edge strength. Also, the larger the size of the smoothing filter in FIG. 7, the higher the level of correction, and the greater the extent to which the edge strength is reduced. Therefore, these six types of filters are the large smoothing filter FSl, the middle smoothing filter FSm, the small smoothing filter FSs, the small edge emphasis filter FEs, the middle edge emphasis filter FEm, in descending order of the corrected edge strength. It is a large edge emphasis filter FEl.

  FIG. 8 is a diagram showing an example of the filter selection table FT1 of the first embodiment. The filter selection table FT1 includes a first sub-table PT1 (FIG. 8 (A)) and a second sub-table ET1 (FIG. 8 (B)). In the first sub-table PT1, the fluctuation speed VS as the fluctuation parameter AP is associated with the edge strength level to be realized. In the second sub-table ET1, the edge strength level and the used filter are associated. The CPU 110 refers to the first sub-table PT1 to determine an edge strength level corresponding to the fluctuation velocity VS calculated at S110. In the present embodiment, when the material information of the sheet acquired in S15 indicates the plain paper, the correspondence information C11 indicated by the broken line in FIG. 8A is referred to, and the edge strength corresponding to the fluctuation speed VS Level is acquired. When the material information of the sheet acquired in S15 indicates glossy paper, the correspondence information C12 indicated by the solid line in FIG. 8A is referred to, and the edge strength level corresponding to the fluctuation speed VS is acquired. .

  The CPU 110 refers to the second sub-table ET1 and selects a filter corresponding to the determined edge strength level as a use filter. The second sub-table ET1 includes a large smoothing filter FS1, a middle smoothing filter FSm, a small smoothing filter FSs, and a small edge emphasis filter FEs in descending order of the corrected edge strength for each of the edge intensity levels 1 to 6. , Middle edge emphasis filter FEm, and large edge emphasis filter FEl are associated (FIG. 8 (B)).

  Here, the higher the fluctuation speed VS of the pixel of interest CP, the higher the possibility that the pixel of interest CP is a pixel forming the edge of the character TX or a pixel located in the vicinity of the edge of the character TX. The possibility of the pixel constituting the background BG is reduced. As the variation speed VS of the pixel of interest CP is smaller, the pixel of interest CP is less likely to be a pixel forming the edge of the character TX or a pixel located in the vicinity of the edge of the character TX. There is a high possibility that the pixel is a component. It is because the fluctuation of the luminance L is relatively rapid at the edge of the character TX, and the fluctuation of the luminance L is relatively gentle in the photograph IM and the background BG.

  Since the readability of the character TX may deteriorate and the appearance of the character TX may be degraded if the edge of the character TX is blurred, it is preferable that a correction process for increasing the edge strength be applied to the pixels forming the edge of the character TX. On the other hand, when the strength of the edge of the photo IM and the base BG is increased, the appearance is likely to be deteriorated due to the color unevenness and the like being emphasized, and it is preferable to reduce the edge strength. Furthermore, the pixels constituting the picture IM and the background BG may include halftone dots in the original used for generating the target image data. In the printed image including these halftone dots, moiré (interference fringes) may occur, which is a phenomenon leading to a decrease in image quality. In order to suppress moiré, it is preferable to apply a correction process to lower the edge intensity in order to eliminate halftone dots on the pixels constituting the picture IM and the background BG.

  From the above, both the correspondence information C11 for plain paper and the correspondence information C12 for glossy paper are set so that the edge strength level gradually increases as the fluctuation speed VS increases. ing. As a result, an appropriate use filter can be selected so that the correction processing for appropriately correcting the edge intensity in the image is executed according to the type (text, picture, background) of the object image OI.

  Further, as shown in FIG. 8A, when the material information indicates glossy paper and the fluctuation speed VS is a specific value VSa, the large smoothing filter FS1 is selected as the use filter. Then, when the material information indicates plain paper and the fluctuation speed VS is a specific value VSa, a small smoothing filter FSs is selected in which the edge strength is higher than that of the large smoothing filter FS1. As a result, it is possible to correct the target image OI so as to have an edge strength appropriate for the sheet material. Specifically, the spread of the ink may differ depending on the material of the sheet. For example, when the sheet is plain paper, the degree of ink bleeding is greater than when the sheet is glossy. As a result, when the paper is plain paper, the bleeding of the ink lowers the granularity compared to the case where the paper is glossy paper, and the above-mentioned color unevenness and halftone dots become inconspicuous. And the background BG is less likely to be processed to lower the edge strength. According to the present embodiment, when the paper is plain paper, the edge strength is higher than when the paper is glossy paper, so the edge of an object such as a photo IM in the print image is excessive. Can be suppressed. Also, when the sheet is plain paper, the edge of the character TX is more likely to be blurred due to ink bleeding compared to when the sheet is glossy paper, so the edge strength is increased relative to the character TX The need for processing increases. According to the present embodiment, when the sheet is plain paper, the edge strength is increased compared to when the sheet is glossy paper, so that blurring of the edge of the character TX can be suppressed.

  Further, as shown in FIG. 8A, for any fluctuation speed VS within the specific range SR1, the filter selected when the material information indicates plain paper is selected when the material information indicates glossy paper. The edge strength of the filter is higher than that of the filter. As a result, it is possible to execute an appropriate correction process according to the material of the sheet for an arbitrary fluctuation speed VS in the specific range SR1.

  At S120, the CPU 110 executes filter processing on the pixel of interest CP. That is, the CPU 110 applies the use filter selected at S115 to the target pixel CP to correct the value of the target pixel CP. Specifically, the CPU 110 multiplies the values of (M + 1) pixels in the filter range including the target pixel CP and the peripheral pixel SP by the corresponding correction coefficients defined in the filter to be used, respectively ( Calculate M + 1 correction values. Then, the CPU 110 calculates the sum of the (M + 1) correction values as the value of the corrected target pixel CP.

  In S125, the CPU 110 determines whether all the pixels have been processed as the target pixel. If there is an unprocessed pixel (S125: NO), the CPU 110 returns to S100. If all the pixels have been processed (S125: YES), the CPU 110 ends the correction processing.

  According to the present embodiment described above, the CPU 110 calculates the feature amount (the fluctuation velocity VS in the present embodiment) regarding the fluctuation of the values of the plurality of peripheral pixels SP of the target pixel CP (S110 in FIG. 4) Based on the feature amount and the printing condition information, the correction process to be applied to the pixel of interest CP is determined (S115 in FIG. 4, FIG. 8). Then, the CPU 110 executes generation processing (S20 to S30 in FIG. 2) including such correction processing (S20 in FIG. 2 and FIG. 4) to generate print image data indicating a print image. The CPU 110 causes the printer 300 as a print execution unit to print a print image according to the print image data (S35, S40 in FIG. 2). As a result, the value of the pixel of interest CP is corrected by the correction processing determined based on the printing condition information, in addition to the feature amount related to the fluctuation of the values of the plurality of peripheral pixels SP. As a result, the appearance of the printed image can be improved by adjusting the edge intensity in the printed image according to the printing conditions.

  Specifically, as the feature amount, a fluctuation velocity VS, which is the degree to which the value of the pixel fluctuates with respect to the fluctuation of the position of the pixel, is used in the peripheral area AA (FIG. 5A) (FIG. 4, FIG. 5 (C)). As a result, the appearance of the printed image can be improved by adjusting the edge intensity in the printed image according to the fluctuation speed VS and the printing conditions.

  More specifically, the printing condition information includes material information indicating the material of the sheet. Even when the fluctuation speed VS is the same, the CPU 110 selects different filters as the use filters in the case where the material information indicates glossy paper and the case where the material information indicates plain paper (FIG. 8). . As a result, it is possible to correct the target image so as to have an edge strength appropriate for the sheet material.

  As understood from the above description, in the first embodiment, glossy paper is an example of the first material, and plain paper is an example of the second material. The correction process using the large smoothing filter FS1 that can be selected when the fluctuation speed VS is a specific value VSa is an example of a third correction process, and the fluctuation speed VS is a specific value VSa. The correction process using the small smoothing filter FSs that can be selected is an example of a fourth correction process.

B. Second Embodiment In the second embodiment, in S15 of FIG. 2, the CPU 110 acquires at least mode information indicating a print mode to be used when printing a print image as printing condition information. Mode information is included, for example, in printing condition information input together with a print instruction via a UI screen (not shown). There are two types of printing modes assumed in this embodiment: the standard mode and the high-speed mode in which the printing speed per page is faster than the standard mode. In the high speed mode, since the printing resolution is lower than in the standard mode and the number of dots to be ejected is smaller than in the standard mode, printing can be performed at higher speed than in the standard mode. For example, the standard mode is one-pass printing in which one image area is printed by one print head main scan, and the high speed mode is a multi-print in which one image area is printed by multiple print head scans. It is pass printing.

  In the correction process of the second embodiment, in S110 of FIG. 4, the fluctuation acceleration VA is calculated as the fluctuation parameter AP, instead of the fluctuation speed VS. The fluctuation acceleration VA is a correction parameter that indicates the degree to which the fluctuation speed VS calculated in the first embodiment fluctuates with respect to the fluctuation of the position of the pixel in the peripheral area AA. Specifically, the CPU 110 controls five pixels (i-2) to (i + 2) in the direction of interest for the pixel of interest CP (pixel (i) in FIG. 5C) as in S110 of the first embodiment. The primary differences ΔL1 (i-2) to ΔL1 (i + 2) are calculated. In the example of FIG. 5C, as described above, the primary differences ΔL1 of the five pixels (i-2) to (i + 2) are 20, -100, -100, 50, and 150, respectively.

  The CPU 110 calculates secondary differences ΔL2 (i-1) to ΔL2 (i + 1) of the luminance value L for each of three pixels (i-1) to (i + 1) of the five pixels in the direction of interest. calculate. For example, the secondary difference ΔL2 (i-1) of the pixel (i-1) is two pixels (i-2) adjacent to both sides of the pixel (i-1) in the attention direction, and the primary difference ΔL1 of i (I-2) is the difference between ΔL1 (i). That is, ΔL2 (i-1) = {ΔL1 (i) -L (i-2)}. Similarly, the secondary difference ΔL2 (i) of the pixel i is the primary difference ΔL1 (i-1) of two pixels (i-1) and (i + 1) adjacent to both sides of the pixel (i) in the direction of interest. , ΔL 1 (i + 1). That is, ΔL2 (i) = {ΔL1 (i + 1) −L (i−1)}. In the example of FIG. 5C, secondary differences ΔL2 (i-1) to ΔL2 (i + 1) of three pixels (i-1) to (i + 1) are -120, 150, and 250, respectively.

  The CPU 110 determines the maximum value of the absolute values of the secondary differences ΔL2 of the three pixels (i-1) to (i + 1) in the attention direction as the fluctuation acceleration VA of the attention pixel CP. In the example of FIG. 5C, the fluctuation speed VS of the pixel of interest CP (pixel i) is the absolute value “250” of the secondary difference ΔL2 (i + 1) of the pixel (i + 1).

  In the correction process of the second embodiment, the CPU 110 uses the filter selection table FT2 different from the filter selection table FT1 (FIG. 8) of the first embodiment in S115 of FIG. From among the types of candidate filters, select one use filter to be used.

  FIG. 9 is a diagram showing an example of the filter selection table FT2 of the second embodiment. The filter selection table FT2 is different from the first sub-table PT1 of the first embodiment in the first sub-table PT2 of FIG. 9 and the second sub-table ET1 (FIG. 8 (B)) identical to the first embodiment. including. In the second sub-table PT2, the fluctuation acceleration VA as the fluctuation parameter AP is associated with the edge strength level to be realized. The CPU 110 refers to the first sub-table PT2 to determine an edge strength level corresponding to the fluctuation acceleration VA calculated at S110. In the present embodiment, when the mode information acquired in S15 indicates the high-speed mode, the correspondence information C21 indicated by the broken line in FIG. 9 is referred to, and the edge strength level corresponding to the fluctuation acceleration VA is acquired. . When the mode information acquired in S15 indicates the standard mode, the correspondence information C22 indicated by the solid line in FIG. 9 is referred to, and the edge strength level corresponding to the fluctuation acceleration VA is acquired. The CPU 110 refers to the second sub-table ET1 and selects a filter corresponding to the determined edge strength level as a use filter.

  Here, as the variation acceleration VA of the pixel of interest CP is larger, the pixel of interest CP is more likely to be a pixel forming the edge of the character TX or a pixel located near the edge of the character TX. The possibility of the pixel constituting the background BG is reduced. As the variation acceleration VA of the pixel of interest CP is smaller, the pixel of interest CP is less likely to be a pixel forming the edge of the character TX or a pixel located near the edge of the character TX, There is a high possibility that the pixel is a component. As described above, at the edge of the character TX, the fluctuation of the luminance L is relatively rapid, and at the photo IM and the background BG, the fluctuation of the luminance L is relatively gentle.

  Then, as described in the first embodiment, it is preferable that correction processing for increasing the edge strength be applied to the pixels forming the edge of the character TX. On the other hand, it is preferable that correction processing for reducing the intensity of the edge be applied to the pixels constituting the photograph IM and the background BG.

  From the above, both the correspondence information C21 for the high-speed mode and the correspondence information C22 for the standard mode are set so that the edge strength level gradually increases as the fluctuation acceleration VA increases. ing. As a result, an appropriate use filter can be selected so that the correction processing for appropriately correcting the edge intensity in the image is executed according to the type (text, picture, background) of the object image OI.

  Furthermore, as shown in FIG. 9, when the mode information indicates the standard mode and the fluctuation acceleration VA is a specific value VAa, the large smoothing filter FS1 is selected as the use filter. Then, when the mode information indicates the high-speed mode and the fluctuation acceleration VA has a specific value VAa, a small smoothing filter FSs is selected in which the edge strength is higher than that of the large smoothing filter FSl. As a result, it is possible to correct the target image OI so as to have an edge strength appropriate for the print mode. Specifically, when the printing mode is the high-speed mode, the probability of using a large dot is high and the probability of using a small dot is low because the resolution is low, compared to the standard mode. As a result, when printing the same image, the high speed mode is more likely to use a larger amount of ink than the standard mode. The amount of ink required to form dots of the same area is because a larger amount of ink is required when using a large dot than when using a small dot. This is because the landing area of the ink is proportional to the square of the diameter of the ink droplet, while the amount (volume) of the ink is proportional to the cube of the diameter of the ink droplet. Further, in the high-speed mode, a large amount of ink droplets are ejected in a short time as compared with the standard mode, so the ink in a state not absorbed by the sheet is likely to be accumulated on the sheet in a large amount. From this, when the printing mode is the high-speed mode, the degree of ink bleeding is larger than when the printing mode is the standard mode. As a result, when the printing mode is the high-speed mode, the ink smears and the granularity is lowered compared to the case where the printing mode is the standard mode paper, and the above-mentioned color unevenness and halftone dots become inconspicuous. There is less need to perform processing to lower the intensity of the edge on the photo IM and the background BG. According to the present embodiment, when the mode information indicates the high-speed mode, the edge strength is increased compared to the case where the mode information indicates the standard mode, and thus the edge of an object such as a photo IM in the print image Can suppress excessive blurring. When the mode information indicates the high-speed mode, the edge of the character TX is more likely to be blurred due to ink bleeding compared to the case where the mode information indicates the standard mode. The need for higher processing is increased. According to the present embodiment, when the mode information indicates the high-speed mode, the edge strength is increased as compared to the case where the mode information indicates the standard mode, so blurring of the edge of the character TX can be suppressed.

  Furthermore, as shown in FIG. 9, for any given variable acceleration VA within the specific range SR2, the filter selected when the mode information indicates the high-speed mode is the filter selected when the mode information indicates the standard mode. Is also a filter that increases the edge strength. As a result, it is possible to execute an appropriate correction process according to the print mode for any fluctuation acceleration VA within the specific range SR2.

  According to the second embodiment described above, as described above, in the peripheral area AA (FIG. 5A), the fluctuation speed VS fluctuates with respect to the fluctuation of the position of the pixel as the feature quantity. The fluctuation acceleration VA is used (FIG. 4, FIG. 5 (C)). As a result, the appearance of the print image can be improved by adjusting the intensity of the edge in the print image according to the fluctuation acceleration VA and the printing condition.

  More specifically, the printing condition information includes mode information indicating a printing mode to be used for printing a print image. Even when the variation acceleration VA is the same, the CPU 110 selects different filters as the use filters in the case where the mode information indicates the high-speed mode and the case where the mode information indicates the standard mode (FIG. 9) . As a result, the target image can be corrected to have an edge strength appropriate for the print mode.

  As understood from the above description, in the second embodiment, the standard mode is an example of the first print mode, and the high speed mode is an example of the second print mode. The correction process using the large smoothing filter FS1 that can be selected when the fluctuation acceleration VA is a specific value VAa is an example of a fifth correction process, and the fluctuation acceleration VA is a specific value VAa. The correction process using the small smoothing filter FSs that can be selected is an example of a sixth correction process.

C. Third Embodiment In the third embodiment, the CPU 110 at least acquires size information indicating the size of a sheet for printing a print image as printing condition information in S15 of FIG. The size information is included in, for example, printing condition information input together with a printing instruction via a UI screen (not shown). The sheet size assumed in this embodiment is two types of A4 and L size. As a modification, in place of A4, various other sizes such as A3 size and A5 size may be adopted, and in place of L size, other various sizes such as business card size and postcard size may be adopted. It can be adopted.

  In the correction process of the second embodiment, the number of times of fluctuation VN is calculated as the fluctuation parameter AP in S110 of FIG. 4 instead of the fluctuation speed VS. The number of times of fluctuation VN is the number of times the value of the pixel increases or decreases with respect to the fluctuation of the position of the pixel in the peripheral area AA. Specifically, as in the case of S110 of the first embodiment, the CPU 110 respectively sets the pixel groups PL1 to PL4 in the four directions shown in FIG. 5 for the pixel of interest CP (pixel (i) in FIG. 5C). , Primary differences ΔL1 (i-2) to ΔL1 (i + 2) of the five pixels (i-2) to (i + 2) of the pixel group are calculated. In the example of FIG. 5C, as described above, the primary differences ΔL1 of the five pixels (i-2) to (i + 2) are 20, -100, -100, 50, and 150, respectively.

  The CPU 110 sets primary differences ΔL1 (i-2) to ΔL1 (i + 2) of five pixels (i-2) to (i + 2) included in the pixel group in one direction along the one direction. Calculate the number of changes (the number of primary changes) from a negative value to a positive value or from a positive value to a negative value. In the example of FIG. 5 (C), the number of primary fluctuations is two. The CPU 110 calculates the number of primary fluctuations for each of the pixel groups PL1 to PL4 in the four directions, and calculates the total value of the number of primary fluctuations as the number of fluctuations VN of the target pixel CP.

  In the correction process of the third embodiment, in S115 of FIG. 4, the CPU 110 uses the filter selection table FT3 different from the filter selection table FT1 (FIG. 8) or FT2 (FIG. 9) described above. Out of six types of seven candidate filters, select one use filter to be used.

  FIG. 10 is a diagram showing an example of the filter selection table FT3 of the third embodiment. The filter selection table FT3 includes the first sub-table PT3 of FIG. 10 and the second sub-table ET1 (FIG. 8 (B)) identical to the first embodiment. In the first sub-table PT3, the number of times of fluctuation VN as the fluctuation parameter AP is associated with the edge strength level to be realized. The CPU 110 refers to the first sub-table PT3 to determine an edge strength level corresponding to the variation number VN calculated in S110. In the present embodiment, when the size information acquired in S15 indicates A4, the correspondence information C31 indicated by the broken line in FIG. 10 is referred to, and the edge strength level corresponding to the number of times of fluctuation VN is acquired. When the size information acquired in S15 indicates L size, the correspondence information C32 indicated by the solid line in FIG. 10 is referred to, and the edge strength level corresponding to the number of times of fluctuation VN is acquired. The CPU 110 refers to the second sub-table ET1 and selects a filter corresponding to the determined edge strength level as a use filter.

  Here, as the number of times of fluctuation VN of the pixel of interest CP is larger, the pixel of interest CP is more likely to be a pixel constituting a halftone dot in the image, and the pixel of the edge of the character TX or the edge of the character TX Is less likely to be a pixel located in the vicinity of As the number of times of fluctuation VN of the pixel of interest CP is smaller, the pixel of interest CP is more likely to be a pixel forming the edge of the character TX or a pixel located near the edge of the character TX. It is likely to be. As described above, since the variation of the pixel value based on the edge of the character is not as fine as the halftone dot, the number of times of variation of the pixel value due to the edge of the character TX is the number of variations of the pixel value due to the halftone dot It tends to be less than that.

  Then, as described in the first embodiment, it is preferable that correction processing for increasing the edge strength be applied to the pixels forming the edge of the character TX. On the other hand, it is preferable that correction processing for reducing the intensity of the edge is applied to the pixels constituting the halftone dot in order to eliminate the halftone dot and to suppress the moiré.

  From the above, both the correspondence information C31 for A4 and the correspondence information C32 for L format are set so that the edge strength level gradually decreases as the number of times of fluctuation VN increases. There is. As a result, a correction process is appropriately performed to appropriately correct the edge intensity in the image, depending on whether the pixel of interest is likely to form the character TX or halftone dot. , You can choose the appropriate use filter.

  Furthermore, as shown in FIG. 10, when the size information indicates A4, and the number of times of fluctuation VN is a specific number of times VNa, the small edge emphasis filter FEs is selected as a used filter. Then, when the size information indicates an L size smaller than A4, and the number of times of fluctuation VN is a specific number of times VNa, the large edge emphasis filter FEl having an edge strength higher than that of the large smoothing filter FSl is selected. Be done. As a result, it is possible to correct the target image OI so as to have an edge strength appropriate for the print mode.

  Specifically, the normal observation distance of the print image differs depending on the size of the sheet. Generally, the larger the size of the sheet, the longer the viewing distance of the printed image printed on the sheet. For example, when the size of the sheet is a business card size or an L-size, the observation distance of the print image is about 10 cm to 15 cm. On the other hand, in the case where the size of the sheet is an A4 size larger than the business card size and the L size, the observation distance of the print image is about 30 cm. On the other hand, the appearance (for example, graininess and sharpness) when a specific print image is observed at a relatively short observation distance is the appearance when the particular print image is observed at a relatively long observation distance. It can be different. This is because, for example, the size of the image falling within a predetermined visual field range of the observer decreases as the observation distance decreases, and increases as the observation distance decreases. For example, at relatively long viewing distances, even an image that looks natural may appear as a blurred image because it is easier to view finer portions at relatively short viewing distances. Specifically, at the business card size or L size size where the observation distance is relatively short, the edge of the object such as the character TX is easily blurred. Therefore, the edge intensity is applied to the pixels forming the edge of the object such as the character TX. There is a high need to On the other hand, in the case of A4 size and A3 size with relatively long viewing distance, blurring of the edge of the object such as the character TX is less noticeable, so it is less necessary to increase the edge strength. To reduce the edge strength.

  According to this embodiment, when the size information indicates an L size smaller than A4, the edge strength is increased compared to the case where the size information indicates A4, so the size of the sheet is relatively small, Although the assumed viewing distance is relatively short, it is possible to suppress the problem that the edge of the object such as the character TX is blurred. Also, when the size information indicates A4, the edge strength is lower than when the size information indicates L size, so the possibility of halftone dots remaining can be reduced.

  Furthermore, as shown in FIG. 10, the filter selected when the size information indicates L for any number of times of fluctuation VN in the specific range SR3 is more than the filter selected when the size information indicates A4. This is a filter that increases the edge strength. As a result, it is possible to execute an appropriate correction process according to the size of the sheet for the arbitrary number of times of fluctuation VN within the specific range SR3.

  According to the third embodiment described above, as described above, the number of times of fluctuation VN fluctuates with respect to the fluctuation of the position of the pixel in the peripheral area AA (FIG. 5A) as the feature value. The fluctuation acceleration VA is used (FIG. 4, FIG. 5 (C)). As a result, the appearance of the print image can be improved by adjusting the intensity of the edge in the print image according to the number of times of fluctuation VN and the printing conditions.

  More specifically, the printing condition information includes size information indicating the size of a sheet for printing a print image. Even when the number of times of fluctuation VN is the same, the CPU 110 selects different filters as the used filters in the case where the size information indicates L size and the case where the size information indicates A4 (FIG. 10). As a result, it is possible to correct the target image so as to have an edge strength appropriate for the size of the sheet.

  As understood from the above description, in the third embodiment, A4 is an example of the first size, and L size is an example of the second size. The correction process using the small edge emphasis filter FEs that can be selected when the variation count VN is a specific count VNa is an example of a first correction process, and the variation count VN is a specific count VNa. The correction process using the large edge emphasis filter FEl that can be selected is an example of the second correction process.

D. Modification:
(1) In the first embodiment, which of the two pieces of correspondence information C11 and C12 is referred to based on only the material information indicating the material of the sheet is switched to select the use filter, and the second embodiment is performed. In the example, which of the two pieces of correspondence information C21 and C22 is referred to based on only the mode information indicating the print mode is used to switch the selection of the use filter. Instead of this, whether to use the filter may be switched by referring to three or more pieces of correspondence information based on a plurality of pieces of printing condition information.

  FIG. 11 is a diagram showing an example of the filter selection table FT4 of the modification. The filter selection table FT4 includes four pieces of correspondence information C41 to C44 in which the fluctuation speed VS is associated with the edge strength level to be realized. Which one of these four pieces of correspondence information is to be referred to is switched based on the material information and the mode information. Specifically, in the first case where the material information indicates plain paper and the mode information indicates a high-speed mode, the CPU 110 uses the correspondence information C41 to select a use filter corresponding to the fluctuation speed VS. In the second case where the material information indicates plain paper and the mode information indicates standard mode, the CPU 110 uses the correspondence information C42 to select a use filter corresponding to the fluctuation speed VS. In the third case where the material information indicates glossy paper and the mode information indicates the high-speed mode, the CPU 110 uses the correspondence information C43 to select a use filter corresponding to the fluctuation speed VS. When the material information indicates glossy paper and the mode information indicates the standard mode, the CPU 110 uses the correspondence information C44 to select the use filter corresponding to the fluctuation speed VS.

  The correspondence information C41 to C44 are all set so that the edge strength level becomes higher in stages as the fluctuation rate VS increases. As a result, an appropriate use filter can be selected so that the correction processing for appropriately correcting the edge intensity in the image is executed according to the type (text, picture, background) of the object image OI.

  Furthermore, the correspondence information C41 to C44 is set such that the edge strength level becomes higher in the order of the correspondence information C41, C42, C43, and C44 when the fluctuation speed VS is a specific value VSb. That is, when the fluctuation speed VS is a specific value VSb, the edge strength is increased in the order of the first case, the second case, the third case, and the fourth case, as described above. The pixel of interest CP is corrected. As a result, the intensity in the image can be appropriately corrected according to both the material information and the mode information.

(2) In the above embodiments, the printer 300 is an inkjet printer, but may be a laser printer that performs printing using toner as a colorant instead. In this case, as in the third embodiment, for example, which of the two pieces of correspondence information is referred to based on the number of times of fluctuation VN and the size information of the sheet is used to switch the use filter. It may be done. In the laser printer, processing according to a known dither method using a dither matrix is used in the halftone processing of S30.

  FIG. 12 is a diagram showing an example of the filter selection table FT5 of the modification. The filter selection table FT5 includes correspondence information C51 used when the size information indicates A4, and correspondence information C52 used when the size information indicates L size.

  The correspondence information C51 and C52 are both set so that the edge strength level gradually decreases as the number of times of fluctuation VN increases. By this, it is appropriate that the correction processing for appropriately correcting the intensity of the edge in the image is executed depending on whether the pixel of interest CP is a pixel that constitutes a character or a pixel that constitutes a halftone dot. You can select the use filter.

  The correspondence information C51 and C52 are set such that the edge strength level of the correspondence information C52 is higher than that of the correspondence information C51 when the number of times of fluctuation VN is the specific number of times VNb. That is, when the number of times of fluctuation VN is the specific number of times VNb, the pixel of interest CP is such that the edge strength is higher when the size information indicates L size than when the size information indicates A4. Is corrected. As a result, the intensity in the image can be properly corrected according to the size of the sheet.

  Specifically, as described in the third embodiment, as described above, for example, at relatively long observation distances, even for images that look natural in appearance, at relatively short observation distances, Because it is easy to view small parts, it may appear as a blurred image. Specifically, at the business card size or L size size where the observation distance is relatively short, the edge of the object such as the character TX is easily blurred. Therefore, the edge intensity is applied to the pixels forming the edge of the object such as the character TX. There is a high need to On the other hand, in the case of A4 size and A3 size with relatively long viewing distance, blurring of the edge of the object such as the character TX is less noticeable, so it is less necessary to increase the edge strength. To reduce the edge strength. In particular, in a laser printer using a dither method, moiré tends to occur. For this reason, the need for performing a smoothing process to lower the edge strength is high for the pixels forming the halftone dots, as compared to the ink jet printer. For this reason, in the present embodiment, especially when the size information indicates A4, the character and halftone dot are compared to the case where the size information indicates L size, with the edge strength level being up to "3" at the maximum. The difference between the edge strengths of and is reduced to give priority to the elimination of halftone dots. As a result, the possibility of halftone dots remaining in the image can be reduced.

(3) In the above embodiments, the terminal device 100 transmits the print job only to the inkjet printer 300, but the terminal device 100 transmits the print job to the laser printer (not shown). It is good. In this example, when the print job is transmitted to the inkjet printer 300, the halftone processing according to the error diffusion method is executed in the halftone processing of S30, and the print job is transmitted to the laser printer. In the halftone processing of S30, halftone processing according to the dither method is performed.

  In the laser printer, processing according to a known dither method using a dither matrix is used in the halftone processing of S30. In this case, for example, two pieces of processing information indicating the type of halftone to be used are acquired as the printing condition information, and the number of times of fluctuation VN and the processing information indicating the type of halftone processing to be used are two. It may be switched whether to select the use filter with reference to any of the correspondence information of. Alternatively, instead of the processing information, printer information indicating the type of printer (whether the printer is a laser printer or an inkjet printer) may be acquired as the printing condition information. In this case, it is possible to switch which of the two pieces of correspondence information is referred to based on the number of times of fluctuation VN and the printer information to select the use filter.

  FIG. 13 is a diagram showing an example of the filter selection table FT6 of the modification. The filter selection table FT6 includes correspondence information C61 used when the processing information indicates the error diffusion method, and correspondence information C62 used when the processing information indicates the dither method. When printer information is obtained instead of processing information, when the printer information indicates an inkjet printer, the correspondence information C61 is used as in the case where the processing information indicates an error diffusion method. When the printer information indicates a laser printer, the correspondence information C62 is used as in the case where the processing information indicates a dither method.

  The correspondence information C61 and C62 are set so that the edge strength level of the correspondence information C52 becomes higher than that of the correspondence information C61 when the number of times of fluctuation VN is the specific number of times VNc. That is, when the number of times of fluctuation VN is a specific number of times VNc, attention is focused so that the edge strength is higher when the processing information indicates the error diffusion method than when the processing information indicates the error diffusion method. Pixel CP is corrected. As a result, the intensity in the image can be properly corrected according to the type of halftone processing.

  Specifically, in the case of using the error diffusion method, the edge of an object such as the character TX is easily maintained without blurring as compared with the case of using the dither method. For this reason, in the present embodiment, in the correspondence information C61, the edge strength level is set to the lowest level regardless of the number of times of fluctuation VN. That is, when the processing information indicates the error diffusion method, the edge is selected regardless of the number of times of variation VN, that is, whether the pixel of interest CP is a pixel constituting the character TX or a pixel constituting a halftone dot. Only the correction process using the large smoothing filter FS1 that lowers the intensity of. By this, in the case of using the error diffusion method, the elimination of halftone dots is surely performed.

  On the other hand, when the processing information indicates the dither method, the edge strength level is set to be lower as the number of times of fluctuation VN increases. As a result, if the pixel of interest CP is a pixel forming a character, the edge strength is increased, and if the pixel of interest CP is a pixel forming a halftone dot, the edge strength is reduced. You can select the appropriate usage filter.

(4) In each of the above embodiments, as shown in FIG. 9 to FIG. 10, the edge strength level increases or decreases in a stepwise manner as the feature amount (fluctuating speed VS, fluctuating acceleration VA, fluctuating number VN) increases. As such, the filter used is determined. This is because the number of use filters that can be selected is limited. For example, the edge intensity level may be varied continuously, eg, by varying the filter coefficients continuously. In this case, the use filter is determined such that the edge strength level continuously increases or decreases as the feature amount (the fluctuation rate VS, the fluctuation acceleration VA, the number of fluctuations VN) increases.

(5) The fluctuation speed VS of the first embodiment is an example, and is not limited to this. In the modification, in the region including the target pixel CP and the peripheral pixel SP, another value may be used which indicates the degree to which the value of the pixel fluctuates with respect to the fluctuation of the position of the pixel. For example, the fluctuation speed VS may be an edge amount calculated by applying a first derivative filter to a filter range including the pixel of interest CP. For the first derivative filter, for example, a known filter such as a Prewitt filter or a Sobel filter may be used. Also, Euclidean distance of RGB values between the pixel of interest CP and the adjacent pixel may be used. Thus, for example, a value representing the value of a pixel in a region including the pixel of interest CP and the peripheral pixel SP or a difference representing the value based on the value of the pixel (brightness, lightness, saturation, etc.) may be used.

(6) The fluctuation acceleration VA of the second embodiment is an example, and is not limited to this. In the modification, in the region including the target pixel CP and the peripheral pixel SP, another value may be used which indicates the degree to which the fluctuation velocity VS fluctuates with respect to the fluctuation of the position of the pixel. For example, the fluctuation acceleration VA may be an edge amount calculated by applying a second derivative filter to a filter range including the pixel of interest CP. For the second derivative filter, for example, a known filter such as a Laplacian filter may be used. The difference between the Euclidean distance of the RGB value between the pixel of interest CP and the pixel adjacent to one side and the Euclidean distance of the RGB value between the pixel of interest CP and the pixel adjacent to the other side is used It may be done. Thus, for example, the value of the pixel in the area including the target pixel CP and the peripheral pixel SP or a value representing the acceleration based on the value of the pixel (brightness, lightness, saturation, etc.) may be used.

(7) The number of times of fluctuation VN of the third embodiment is an example, and is not limited to this. In the modification, in the region including the target pixel CP and the peripheral pixel SP, another value may be used to indicate the number of times the value of the pixel increases or decreases with respect to the fluctuation of the position of the pixel. For example, as the number of times of fluctuation VN, for example, spatial frequency such as luminance in the peripheral area AA, lightness, saturation or the like may be used. Thus, for example, a value representing the frequency of change of the value of the pixel in the area including the target pixel CP and the peripheral pixel SP or the value based on the value of the pixel (brightness, lightness, saturation, etc.) is used. obtain.

(8) A variable acceleration VA may be used instead of the variable velocity VS used in the first embodiment. Also, instead of the fluctuation acceleration VA used in the second embodiment, the fluctuation speed VS may be used. This is because the larger the feature amount, the higher the possibility that the focused pixel CP constitutes a character, and the smaller the smaller the feature amount, the higher the likelihood that the focused pixel CP constitutes a photograph or a background. Since the fluctuation acceleration VA indicates the degree to which the fluctuation speed VS fluctuates as described above, it can be said that the fluctuation speed VS itself and the fluctuation acceleration VA are “values based on the fluctuation speed VS”.

(9) The terminal device 100 as a print control device that executes the printing process of FIG. 2 may be another type of device, for example, a CPU and a memory included in the printer 300. In this case, for example, the CPU included in the printer 300 acquires target image data from a memory included in itself and the terminal device 100, executes printing processing, and generates print image data. The CPU causes the print mechanism provided by the CPU to print the print image according to the print image data generated. In this case, the CPU and the memory included in the printer 300 are an example of a print control apparatus, and the print mechanism included in the printer 300 is an example of a print execution unit.

  Also, the print control apparatus that executes the printing process of FIG. 2 may be, for example, a server that acquires target image data from the terminal apparatus 100 or the printer 300 and executes image processing. Such a server may be a plurality of computers that can communicate with each other via a network. In this case, the plurality of computers that can communicate with each other via the network correspond to the print control device.

(10) In the above embodiments, a part of the configuration realized by hardware may be replaced by software, and conversely, a part or all of the configuration implemented by software is replaced by hardware You may do so. For example, part of the processing executed by the CPU 110 of the terminal device 100 of FIG. 1 may be realized by a dedicated hardware circuit.

  Although the present invention has been described above based on the examples and modifications, the above-described embodiment of the present invention is for the purpose of facilitating the understanding of the present invention, and does not limit the present invention. The present invention can be modified and improved without departing from the spirit and the scope of the claims, and the present invention includes the equivalents thereof.

  DESCRIPTION OF SYMBOLS 100 ... Terminal device, 110 ... CPU, 120 ... Volatile storage device, 130 ... Nonvolatile storage device, 140 ... Display part, 150 ... Operation part, 170 ... Communication interface, 300 ... Printer, VA ... Variation acceleration, BG ... Base , PG: computer program, OI: target image, IM: photograph, VN: fluctuation number, FP: farthest peripheral pixel, CP: notable pixel, AP: fluctuation parameter, SP: peripheral pixel, VS: fluctuation speed, FT1 to FT6 ... Filter selection table, TX ... Character, FEl, FEs, FEm ... Edge emphasis filter, FSl, FSm, FSs ... Smoothing filter

Claims (11)

A print control apparatus that controls a print execution unit that prints an image using a color material.
An image acquisition unit that acquires target image data indicating a target image;
A condition acquisition unit that acquires condition information indicating printing conditions for printing a print image based on the target image;
A calculation unit that calculates a feature amount related to variations in values of the plurality of peripheral pixels using values of a plurality of peripheral pixels positioned around a target pixel in the target image;
The correction processing to be applied to the target pixel is determined based on the feature amount and the condition information, which is processing to correct an edge intensity in the target image including the target pixel. The decision unit,
A generation unit that executes generation processing including the determined correction processing on the target image data to generate print image data indicating the print image;
A print control unit that causes the print execution unit to print the print image according to the print image data;
A print control device comprising: The printing control apparatus according to claim 1, wherein
The print control device, wherein the feature amount includes a variation speed which is a degree to which a value of a pixel fluctuates with respect to a fluctuation of a position of a pixel in a region including the target pixel and the plurality of peripheral pixels. The print control apparatus according to claim 1, wherein
The print control device, wherein the feature amount includes an increase / decrease number of times that the value of the pixel increases / decreases with respect to the change of the position of the pixel in the area including the target pixel and the plurality of peripheral pixels. The printing control apparatus according to any one of claims 1 to 3, wherein
The feature amount is a variation acceleration that is a variation speed at which the value of the pixel fluctuates with respect to the fluctuation of the position of the pixel in a region including the target pixel and the plurality of peripheral pixels. Including print control device. The printing control apparatus according to claim 1, wherein
The feature amount includes an increase / decrease number which is the number of times the pixel value increases / decreases with respect to the change of the position of the pixel in the region including the target pixel and the plurality of peripheral pixels.
The condition information includes size information indicating a size of a print medium for printing the print image,
The determination unit is
If the size information indicates a first size and the number of times of increase and decrease is a specific number, a first correction process is determined as the correction process to be applied,
When the size information indicates a second size smaller than the first size, and the number of times of increase and decrease is the specific number, the strength of the edge is higher than that of the first correction process. A print control apparatus, which determines a second correction process as the correction process to be applied. The printing control apparatus according to claim 5, wherein
The determination unit is
When the size information indicates the first size, the correction process in which the intensity of the edge decreases continuously or stepwise as the number of increases and decreases increases is determined as the correction process to be applied. And
When the size information indicates the second size, the correction process in which the intensity of the edge decreases continuously or stepwise as the number of increases and decreases increases is determined as the correction process to be applied. And
The correction process determined when the size information indicates the second size for any number of increases and decreases within a specific range is the correction determined when the size information indicates the first size A printing control apparatus, which is processing in which the strength of the edge is higher than processing. The printing control apparatus according to claim 1, wherein
The feature amount includes a value based on a fluctuation speed which is a degree to which the value of the pixel fluctuates with respect to the fluctuation of the position of the pixel in the area including the target pixel and the plurality of peripheral pixels.
The condition information includes material information indicating a material of a print medium for printing the print image,
The determination unit is
If the material information indicates the first material and the value based on the fluctuation speed is a specific value, then the third correction process is determined as the correction process to be applied,
If the material information indicates a second material in which the coloring material is more likely to blur than the first material, and the value based on the fluctuation speed is the specific value, the third correction process is performed. The print control apparatus, wherein the fourth correction process in which the edge strength is high is determined as the correction process to be applied. The print control apparatus according to claim 7, wherein
The determination unit is
When the material information indicates the first material, the correction process in which the strength of the edge increases continuously or stepwise as the value based on the fluctuation speed increases is the correction to be applied Determined as processing
When the material information indicates the second material, the correction process in which the strength of the edge increases continuously or in steps as the value based on the fluctuation speed increases is the correction to be applied Determined as processing
The correction process determined when the material information indicates the second material is a value determined based on an arbitrary fluctuation speed within a specific range, and the correction process is determined when the material information indicates the first material. The printing control apparatus, wherein the edge strength is higher than the correction processing. The printing control apparatus according to claim 1, wherein
The feature amount includes a value based on a fluctuation speed which is a degree to which the value of the pixel fluctuates with respect to the fluctuation of the position of the pixel in the area including the target pixel and the plurality of peripheral pixels.
The condition information includes mode information indicating a print mode,
The determination unit is
When the mode information indicates the first print mode and the value based on the fluctuation speed is a specific value, the fifth correction process is determined as the correction process to be applied,
If the mode information indicates a second printing mode in which the printing speed is faster than the first printing mode and the value based on the fluctuation speed is the specific value, the fifth correction process is performed. The print control apparatus, wherein a sixth correction process in which the edge strength is high is determined as the correction process to be applied. The print control apparatus according to claim 9, wherein
The determination unit is
In the case where the mode information indicates the first print mode, the correction process in which the intensity of the edge increases continuously or stepwise as the value based on the fluctuation speed increases should be applied. Determined as correction processing,
In the case where the mode information indicates the second print mode, the correction process in which the intensity of the edge increases continuously or stepwise as the value based on the fluctuation speed increases should be applied. Determined as correction processing,
The correction processing determined when the mode information indicates the second print mode for a value based on any of the fluctuation speeds within a specific range is the case where the mode information indicates the first print mode. A print control apparatus, which is a process in which the strength of the edge is higher than the correction process to be determined. A computer program for controlling a print execution unit that prints an image using a colorant,
An image acquisition function of acquiring target image data indicating a target image;
A condition acquisition function of acquiring condition information indicating printing conditions for printing a print image based on the target image;
A calculation function of calculating a feature amount related to variations in values of the plurality of peripheral pixels using values of a plurality of peripheral pixels positioned around a target pixel in the target image;
The correction processing to be applied to the target pixel is determined based on the feature amount and the condition information, which is processing to correct an edge intensity in the target image including the target pixel. With the decision function
A generation function of generating print image data indicating the print image by executing a generation process including the determined correction process on the target image data;
A print control function that causes the print execution unit to print the print image according to the print image data;
A computer program that makes a computer realize it.

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