JP4640257B2 - Image processing apparatus, image processing method, and program - Google Patents

Description

  The present invention relates to an image processing apparatus, an image processing method, and a program for performing image processing on image data including characters and line drawing objects.

  A white character is a character in a background with a maximum density or a high density close to it, and a low density character with a minimum density or close to it. May become thinner or crushed black. This is because of the output characteristics of the printer, when an isolated point for one pixel is output at the maximum pixel value, the isolated point becomes larger as it exceeds the region for one pixel. This phenomenon is called dot gain and appears more or less regardless of which printing process is employed.

  As an improvement measure, in addition to a method of improving the printing process itself, a method of performing output control by image processing can be considered. For example, by predicting the amount of output that exceeds the region that should be output when an isolated point is output, and performing image processing to increase the line width of the white character in advance, dot gain can be increased. Can be prevented.

FIG. 10 shows an example of the processing.
FIG. 10A is a diagram illustrating an image of a white character “T”. The character area “T” has a pixel value close to the minimum value, and the background area has a pixel value close to the maximum value. When this image is output without any particular processing, a dot gain as shown in FIG. 10B is generated in the background area. In order to prevent dot gain, image processing is performed to reduce the pixel value of the pixel in the background area adjacent to the outline character. By reducing the pixel value, the dots in the background area are within a predetermined area for one pixel, so that the dots are prevented from entering the white character area, Degradation (crushing) can be suppressed.

  As described above, it is necessary to manipulate pixel values around white characters in order to perform processing for preventing white characters from being crushed. Therefore, it becomes a problem to specify the exact position of the outline character in the image, specifically, the outline of the outline character.

  Conventionally, a method using pattern matching has been disclosed (for example, see Patent Document 1). This is because pattern matching is performed by applying a pattern in which white (low density) and black (high density) pixels are arranged in a predetermined order to image data, and one white pixel is surrounded by black pixels. In addition, this is a method for detecting a thin line portion where character collapse is likely to occur. According to this method, by changing the pixel value of the detected black pixel, it is possible to prevent the white character from being crushed.

Also, conditions regarding attributes such as the density, thickness, color, size, font type, etc. of the character or line included in the output target image are determined from the print command, and the thickness or density of the character or line is determined according to the determined condition. A method of changing the attribute information of a print command is also disclosed (see, for example, Patent Document 2).
JP 2000-138832 A Japanese Patent Application Laid-Open No. 11-12754

  However, the method described in Patent Document 1 can only handle small characters because the pattern itself is small. In addition, a process for preventing character collapse is applied only to a portion that matches the pattern, not the entire character, but the line width of the character differs vertically and horizontally as represented by Mincho. In the case of such character types, there is a problem that when processing is performed locally using a pattern, the balance of the shape of the entire character is lost and the reproducibility of the character is lowered. Further, according to this method, image quality deterioration can be effectively prevented for characters, but when a natural image other than characters is included in the image, the pattern is also applied to the natural image. On the other hand, the image quality of natural images is degraded.

In the method described in Patent Document 2, the thickness and density of a character are changed according to the character attribute. However, the processing is not performed on image data, and the font attribute information is changed at the preceding stage. Is. For this reason, even if character collapse is likely to occur for a part of the character, it is considered that the entire character is changed, and the result does not conform to the user's intention.
Also, in the case of Japanese font characters, in order to prevent garbled characters, they are often outlined and converted into image data on a word processor application. At this time, since the font attribute is lost due to the outline conversion, these outline characters may not be processed by this method.

  An object of the present invention is to suppress deterioration in image quality of a character or line drawing object.

The invention according to claim 1 is an image processing apparatus,
Printing image generation means for generating image data based on intermediate data generated based on printing control data;
Whether or not each pixel constituting the image data generated by the printing image generation unit is white and has a font or vector data attribute based on the printing control data. White area data generation means for determining and generating white area data indicating the determination result;
A target pixel is sequentially set for each pixel constituting the image data, and it is determined based on the white region data whether or not a pixel of the white object region exists in a peripheral pixel adjacent to the target pixel. 1 determination means;
Second determination means for determining whether or not a pixel value of the target pixel is a predetermined value or more when it is determined by the first determination means that a pixel of the white object region exists in the peripheral pixels;
When the second determination means determines that the pixel value of the target pixel is greater than or equal to a predetermined value, the corrected pixel value of the target pixel is determined based on the pixel value of the white object region, and the determination Correction means for correcting the pixel value of the pixel of interest based on the pixel value that has been
It is characterized by providing.

The invention according to claim 2 is the image processing apparatus according to claim 1 ,
Fine line structure detecting means for detecting pixels constituting the fine line structure among the pixels adjacent to the white object region;
A correction control means for controlling the degree of correction of the pixel by the correction means when a pixel constituting the fine line structure is detected by the fine line structure detection means;
It is characterized by providing.

The invention according to claim 3 is the image processing apparatus according to claim 1 ,
Fine line structure detecting means for detecting pixels constituting the fine line structure among the pixels adjacent to the white object region;
A correction control unit that invalidates correction of the pixel by the correction unit when a pixel constituting the thin line structure is detected by the thin line structure detection unit;
It is characterized by providing.

The invention according to claim 4 is an image processing method,
A printing image generation step for generating image data based on the intermediate data generated based on the printing control data;
Whether or not each pixel constituting the image data generated by the printing image generation step is white and has a font or vector data attribute based on the printing control data. A white area data generation step of determining and generating white area data indicating the determination result;
A target pixel is sequentially set for each pixel constituting the image data, and it is determined based on the white region data whether or not a pixel of the white object region exists in a peripheral pixel adjacent to the target pixel. 1 determination process;
A second determination step of determining whether a pixel value of the target pixel is equal to or greater than a predetermined value when it is determined in the first determination step that a pixel of the white object region exists in the peripheral pixels;
When it is determined in the second determination step that the pixel value of the target pixel is greater than or equal to a predetermined value, a corrected pixel value of the target pixel is determined based on the pixel value of the white object region, and the determination A correction step of correcting the pixel value of the target pixel based on the pixel value that has been performed ;
It is characterized by including.

The invention according to claim 5 is the image processing method according to claim 4 ,
A fine line structure detection step of detecting pixels constituting a fine line structure among pixels adjacent to the white object region;
A correction control step for controlling the degree of correction of the pixel in the correction step when a pixel constituting the thin line structure is detected in the fine line structure detection step;
Is further included.

The invention according to claim 6, in the image processing method according to claim 5 or 6,
A fine line structure detection step of detecting pixels constituting a fine line structure among pixels adjacent to the white object region;
When a pixel constituting the thin line structure is detected in the fine line structure detection step, a correction control step for invalidating the correction for the pixel in the correction step;
Is further included.

The invention described in claim 7
Computer
Printing image generation means for generating image data based on intermediate data generated based on printing control data;
Whether or not each pixel constituting the image data generated by the printing image generation unit is white and has a font or vector data attribute based on the printing control data. White area data generating means for determining and generating white area data indicating the determination result;
A target pixel is sequentially set for each pixel constituting the image data, and it is determined based on the white region data whether or not a pixel of the white object region exists in a peripheral pixel adjacent to the target pixel. 1 determination means,
Second determination means for determining whether a pixel value of the target pixel is equal to or greater than a predetermined value when the first determination means determines that the pixel of the white object region exists in the peripheral pixels;
When the second determination means determines that the pixel value of the target pixel is greater than or equal to a predetermined value, the corrected pixel value of the target pixel is determined based on the pixel value of the white object region, and the determination Correcting means for correcting the pixel value of the target pixel based on the pixel value that has been
It is a program for making it function as.

The invention according to claim 8 is the program according to claim 7 ,
Computer
Fine line structure detecting means for detecting pixels constituting a fine line structure among pixels adjacent to the white object region;
A correction control means for controlling the degree of correction of the pixel by the correction means when a pixel constituting the fine line structure is detected by the fine line structure detection means;
It is a program for making it function as.

The invention according to claim 9 is the program according to claim 7 ,
Computer
Fine line structure detecting means for detecting pixels constituting a fine line structure among pixels adjacent to the white object region;
A correction control unit that invalidates correction of the pixel by the correction unit when a pixel constituting the thin line structure is detected by the thin line structure detection unit;
It is a program for making it function as.

According to the inventions described in claims 1, 4 , and 7 , it is possible to perform correction for reducing the pixel value of the pixel adjacent to the white object. By reducing the pixel value of the pixel adjacent to the white object, it is possible to prevent dot gain from occurring, and it is possible to suppress deterioration in image quality in the white object. Further, since the white object area is determined based on the control data, it is possible to determine the white object area in units of objects. Furthermore, since the correction is performed according to the attribute, the white object area having the attribute that does not need to be corrected can be excluded from the correction target, and the image quality deterioration due to the correction can be avoided.

In addition , it is possible to detect and correct pixels adjacent to the white object area in units of objects. When detecting the pixels adjacent to the white object region by using a pattern or the like, it may not be identified properly picture element becomes the detection of local picture elements. In contrast, by determining the total necessary correction of the object, it is possible to accurately detect the base can picture element subjected to correction in reality. As a result, it is possible to perform correction in consideration of the entire object.

Also, a predetermined value or more pixel values, may be the subject of the correction only high Ige containing possibility dot gain occurs.

In addition , the correction value of the target pixel can be determined in consideration of the relationship with the pixel value of the white object region. For example, the correction value is determined so that the correction amount of the target pixel decreases when the pixel value of the white object region is large, and conversely, the correction amount of the target pixel increases when the pixel value of the white object region is small. It is possible to reproduce the original white object and the surrounding contrast.

According to the inventions described in claims 2 , 5 , and 8 , it is possible to perform control to reduce the degree of correction for the pixels constituting the thin line structure. That is, the pixel value of the pixels constituting the fine line structure is greatly reduced, thereby preventing the contrast between the white object region and its surroundings from being lowered and avoiding the loss of reproducibility of the fine line structure. Can do.

According to the inventions described in claims 3 , 6 , and 9 , pixels constituting the thin line structure can be excluded from correction. That is, by reducing the pixel value of the pixels constituting the fine line structure, it is possible to prevent the contrast between the white object region and its surroundings from being lowered and to avoid the loss of reproducibility of the fine line structure. it can.

First, the configuration will be described.
FIG. 1 is a diagram illustrating a printing system.
A printing system 100 shown in FIG. 1 prints out output target data created by a PC (Personal Computer) 10 by an MFP (Multi Function Printer) 20.

The PC 10 includes application software related to a word processor, drawing, photo editing, and the like, and can create various data such as text data and image data.
Further, the PC 10 includes printer driver software, and the output target data created by the application is converted into PDL (Page Description Language) format data (hereinafter referred to as PDL data) that is control data for printing. And is transmitted to the MFP 20.

  The MFP 20 includes the image processing apparatus 1, the printer 13, and the like according to the present invention. The image processing apparatus 1 generates image data for each pixel based on the PDL data input from the PC 10, and the printer 13 based on the image data. Is used for printing out.

FIG. 2 shows an internal configuration of the image processing apparatus 1.
As shown in FIG. 2, the image processing apparatus 1 includes a controller 2, a line buffer 3, a monochrome conversion unit 4, a white object determination unit 5, a target pixel determination unit 6, a fine line structure detection unit 7, a correction control unit 8, a white object It comprises a correction unit 9, a γ correction unit 11, a dither processing unit 12, and the like.

  The controller 2 includes an I / F 21, a CPU (Central Processing Unit) 22, a RAM (Random Access Memory) 23, a ROM (Read Only Memory) 24, a renderer 25, a page memory 26, and the like.

  The I / F 21 is an interface that controls data transfer between a host computer (not shown) in the MFP 20 and the image processing apparatus 1.

  The CPU 22 reads out various control programs from the ROM 24 and develops them in the RAM 23, performs various calculations according to the programs, or centrally controls the operations of the units 21, 23-26.

  When the PDL data is input from the host computer via the I / F 21, the CPU 22 stores the data in the RAM 23. Then, a PDL command included in the PDL data is analyzed, and a display list is created by classifying each image unit to be drawn (this is called an object). The display list is intermediate data in which position coordinates of an object to be drawn, address information of area data or color data, and the like are described.

FIG. 3 shows an example of a display list created for one object.
As shown in FIG. 3, the display list describes drawing coordinates, drawing size, drawing logic, start address of area data, start address of color data, and the like. The drawing coordinates are coordinate values indicating the printing position of the object within the printing range of one page. The drawing size is a numerical value indicating the vertical and horizontal sizes of the object. The drawing logic is a parameter for performing calculation (painting or clipping) with the background at the time of drawing. The start address of the area data is a numerical value indicating the memory address where the area data is stored. Similarly, the start address of the color data is a numerical value indicating the memory address where the color data is stored. The area data is data indicating the attributes (font, bitmap, graphic) of the object, and the color data is data indicating the color of the object. Here, it is assumed that color data indicating the color materials C (cyan), M (magenta), Y (yellow), and K (black) used in the printer 13 is stored.

  The CPU 22 creates a display list having such a data structure for all objects for one page, concatenates them, and stores them in the RAM 23.

The RAM 23 is a work memory used by the CPU 22.
The RAM 23 temporarily stores PDL data written by the CPU 22, a display list, and the like.

  The ROM 24 stores various control programs executed by the CPU 22 as well as parameters and data necessary for executing the programs.

  The renderer 25 reads a display list from the RAM 23 by a DMA (Direct Memory Access) function, and generates attribute data and white area data in addition to image data for each pixel of each color C, M, Y, and K based on the display list. It is stored in the page memory 26.

This will be specifically described below.
The renderer 25 reads the display list from the RAM 23 for each predetermined unit such as an object, generates image image data of each color of C, M, Y, and K based on the display list, and is prepared in the page memory 26. Write to the image data storage area. The image data is generated by assigning pixels to the object to be drawn and setting a pixel value for each assigned pixel. The pixel position is determined by the display list drawing coordinates, drawing size, and area data, and the pixel value is determined using color data and drawing logic.

  At the same time, the renderer 25 generates attribute data TAG in units of pixels based on the attribute of the object indicated by the area data in the display list, and stores it in the attribute data storage area prepared in the page memory 26. Attribute data TAG is TEXT (TAG = 0) indicating that it is a character, GRAPHICS (TAG = 1) indicating that it is a character, depending on whether the attribute of the object is font, vector data, or bitmap, Each is set to IMAGE (TAG = 2) indicating that it is a photographic image.

The renderer 25 determines whether the color of the object is white (Y = M = C = K = 0) from the color data, and whether the attribute of the object is font or vector data from the area data. The white area data indicating is generated. Hereinafter, an object that is white and has an attribute of font or vector data is referred to as a white object, and an area of pixels belonging to the white object is referred to as a white object area. In the white area data, data OLB indicating whether or not each pixel is a pixel of the white object area is set, and the renderer 25 has OLB = 1 if it is a white object area, and OLB otherwise. Set to = 0 and write to the page memory 26.
Note that the processing by the renderer 25 may be realized by software processing.

  The page memory 26 has storage areas for storing C, M, Y, and K image data, attribute data TAG, and white area data OLB, respectively, and image data generated by the renderer 25 in these storage areas. , Attribute data TAG, and white area data OLB are held. The page memory 26 outputs these data to the line buffer 3 under the control of the CPU 22.

The line buffer 3 holds image data, attribute data TAG, and white area data OLB for several lines.
In the following processing, a pixel of interest is set for image data, the image data is scanned, and image processing is performed. When image processing is performed on the pixel of interest, its peripheral pixels are referred to. Here, as shown in FIG. 4, the pixel of interest is XS0, and its peripheral pixels are XS1 to XS8.
The line buffer 3 outputs the pixel values Sn (n = 0 to 8; the same applies hereinafter) of the target pixel XS0 and the peripheral pixels XS1 to XS8 to the monochrome conversion unit 4, the white object determination unit 5, and the correction control unit 8. Further, the white area data OLB of the target pixel and the peripheral pixel XSn is output to the white object determination unit 5.

The monochrome conversion unit 4 converts color image data for each of C, M, Y, and K into monochrome image data. In this case, since color information is not required in the subsequent processing, the processing efficiency is improved by using monochrome values. As a method of monochrome conversion, the average of the pixel values Sn [ch] (ch = C, M, Y, K, indicating each color) for each color for each pixel XSn is converted into monochrome as shown in the following formula (1). It may be obtained as a value or may be a weighted average. Moreover, it is good also as taking the maximum value among the pixel values Sn [ch] for every color.
Sn = (Sn [c] + Sn [m] + Sn [y] + Sn [k] / 4) (1)

  As a result of the monochrome conversion, the pixel value S0 obtained for the target pixel XS0 is output to the target pixel determination unit 6, and the pixel values S0 to S8 of the target pixel XS0 and peripheral pixels XS1 to XS8 are output to the thin line structure detection unit 7.

  Based on the white area data OLB, the white object determination unit 5 determines whether or not the outline of the white object area (hereinafter referred to as a white outline, and pixels belonging to the white outline are referred to as white outline pixels) around the target pixel XS0. And determination data PW indicating the determination result is generated. The white object determination unit 5 refers to the white area data OLB of the target pixel XS0 and the peripheral pixels XS1 to XS8, the OLB of the target pixel XS0 is OLB = 0, and OLB = 1 around the target pixel XS0. When there are one or more pixels, it is determined that a white outline exists adjacent to the target pixel XS0.

  If it is determined that there is a white outline in the vicinity, the white object determination unit 5 sets the determination data PW for the target pixel XS0 to PW = 1, and if it is determined that no white outline exists, sets PW = 0. To do. This determination data PW is output to the correction control unit 8.

  Also, the white object determination unit 5 refers to the pixel value Sn [ch] for each color of the pixels set to OLB = 1 among the peripheral pixels XS1 to XS8, and sets this as WH [ch]. This WH [ch] is used as a correction parameter in the subsequent white object correction processing. When there are a plurality of pixels with OLB = 1, the average value thereof or the maximum value or the minimum value thereof is set as WH [ch]. When there is no pixel with OLB = 1 in the peripheral pixels XS1 to XS8, WH [ch] = 0 is set. In this embodiment, since OLB = 1 is set for a white object that is white (C = M = Y = K = 0), WH [ch] = 0. This WH [ch] is output to the white object correction unit 9.

  The target pixel determination unit 6 determines whether the pixel value S0 of the target pixel XS0 is large enough to perform the white object correction process, and outputs determination data PC indicating the determination result. If the pixel value S0 of the target pixel XS0 is small, the density at the time of printing is low and dot gain does not occur, so there is no need to perform white object correction processing. That is, the target pixel determination unit 6 determines whether or not the pixel value of the target pixel XS0 is sufficiently high in density so that dot gain occurs.

  The pixel-of-interest determination unit 6 compares the pixel value S0 of the pixel of interest XS0 with the threshold value GAP, and if S0> GAP, determines that the pixel value is large enough to perform white object correction processing on the pixel of interest XS0. To set PC = 1. If S0 ≦ GAP, white object correction processing is unnecessary and PC = 0 is set. The threshold GAP is obtained by setting in advance the lowest pixel value that requires white object correction processing based on the output characteristics of the printer 13. The determination data PC is output to the correction control unit 8.

The fine line structure detection unit 7 determines whether or not the pixel of interest XS0 configures a fine line structure using a template for thin line structure detection, and generates determination data TL indicating the determination result. The fine line structure means a fine structure portion composed of one pixel or several pixels having substantially the same pixel value.
The white object correcting unit 9 at the subsequent stage prevents the white object from being crushed by reducing the pixel values of the peripheral pixels adjacent to the white object. However, if this is applied uniformly, the fine line structure may not be reproduced.

  For example, when a white object as shown in FIG. 5A is drawn, the target of the white object correction process is its surrounding pixels as shown in FIG. However, this white object forms a fine line structure with peripheral pixels (the circled portion in FIG. 5B), and white object correction processing is also applied to the peripheral pixels constituting this fine line structure. Then, the contrast between the white object and the surrounding pixels is lowered, and the reproducibility of the thin line structure is lost.

  In order not to lose the fine line structure, the peripheral pixels constituting the fine line structure are excluded from the target of the white object correction process, or the white object correction process is performed, but the degree of the correction needs to be reduced. There is. Therefore, prior to the white object correction process, the fine line structure detection unit 7 detects the fine line structure in the white object.

Hereinafter, a method for detecting a thin line structure will be described.
The thin line structure detection unit 7 first classifies the target pixel and the peripheral pixel XSn into three categories S, W, and DC using two threshold values VH and VL (VL <VH). The classification is performed by comparing the pixel value Sn after the monochrome conversion of the target pixel and the surrounding pixel XSn with the threshold values VH and VL. If VH ≦ Sn, the category S, if Sn ≦ VL, the category W, and VL <Sn <VH. If there is, classify it as category DC.

  The threshold values VH and VL are threshold values prepared in advance for category classification. The VL is set so that the low pixel value pixels constituting the white object are classified into the category W. In addition, the value of VH is set so that high-density peripheral pixels adjacent to the white outline pixel to be subjected to white object correction processing are classified into category S.

FIG. 6 shows an example of a template used for thin line structure detection.
The template shown in FIG. 6 is designed to detect a one-pixel-wide thin line structure composed of high-density pixels. As shown in FIG. 6, the target pixel XS0 located in the center and its peripheral pixels XS1 ~ Category relationship with XS8 is predetermined. The thin line structure detection unit 7 matches such a template with the target pixel and the peripheral pixels XS0 to XS8 so that the target pixel XS0 and the center position of the template (position of position number 4 shown in FIG. 6) match.

  FIG. 5C is a diagram illustrating a state in which a template is matched with an image including the white object illustrated in FIG. Since the pixels constituting the white object have low pixel values, the category should be classified as W. Further, since the peripheral pixels of the white object have a high density, they should be classified into category S. Therefore, when the surrounding pixels of category W have a predetermined positional relationship with respect to the target pixel XS0 of category S as defined in the template, the target pixel and the peripheral pixels XS0 to XS8 form a thin line structure. Should be. Note that the category DL in the template indicates that the pixel corresponding to the position where the category DL is set may be any category.

  Therefore, the thin line structure detection unit 7 sets TL = 1 for the target pixel XS0 when any one matches as a result of matching with the template, and TL = 0 when none matches the template. And output to the correction control unit 8.

  The correction control unit 8 determines whether or not to perform the white object correction process on the target pixel XS0 based on the determination data PW, PC, and TL, and determines the parameter α that controls the correction process. The parameter α is set to α = 0 when the white object correction process is not performed and invalid, and when the white object correction process is performed, two values v1 and v2 (0 <v2) indicating the degree of the correction are set. <V1) is set.

  The correction control unit 8 refers to the determination data PW or PC, and one of them is 0, that is, there is no white object area around the target pixel XS0, or the pixel value S0 of the target pixel XS0 is a predetermined value. If it is not GAP or more, it is determined that the white object correction process is not performed, and α = 0 is set to invalidate the process.

On the other hand, when both the determination data PW and PC are 1, the correction control unit 8 determines that a white object region exists around the pixel of interest XS0 and that the pixel value S0 of the pixel of interest XS0 is greater than or equal to the predetermined value GAP. Then, it is determined that the white object correction process is performed. In this case, reference is further made to TL, and when TL = 0, the normal correction parameter value α = v1 is set. Conversely, when TL = 1, the target pixel XS0 forms a thin line structure, and therefore α = v2 is set so that the degree of correction is smaller than usual.
The correction control unit 8 outputs the set parameter α to the white object correction unit 9.

The white object correction unit 9 performs white object correction processing on the pixel value S0 of the target pixel XS0 using the parameters α and WH [ch], and outputs the correction value WE [ch].
The white object correction unit 9 obtains a correction value WE [ch] for the pixel value S0 [ch] for each color of the target pixel XS0 by the following equation (2).
WE [ch] = S0 [ch]-(S0 [ch] -WH [ch]) × α (2)

  That is, when white object correction processing is not performed, since α = 0, WE [ch] = S0 [ch], and the original pixel value S0 of the target pixel XS0 is output. On the other hand, when α = v1 or v2, the value subtracted by (S0 [ch] -WH [ch]) weighted by the v1 or v2 from the original pixel value S0 becomes WE [ch]. The original pixel value S0 is lowered by the white object correction process. Further, since v1> v2, the degree to which the thin line structure is pulled down becomes small.

FIG. 7 shows the result of printing and outputting the white object shown in FIG. 5A after the white object correction processing.
As shown in FIG. 7, as a result of correction so that the pixel values of the peripheral pixels of the white object are reduced, the periphery of the white object has a low density. Further, although the fine line structure around the white object is corrected, the degree of the correction is weaker than other peripheral pixels not having the fine line structure, and the density is lower than the original pixel value. The density is higher than that of surrounding pixels.

When the target pixel XS0 is set and corrected for one pixel as described above, the target pixel XS0 is shifted one pixel at a time and the above-described processing is performed in the same manner, and correction is performed for all the pixels constituting the image data. Done.
If the flow of this series of processing is made into a flowchart, it will become a flowchart as shown in FIG.
As shown in FIG. 8, first, when the line buffer 3 acquires image data Sn of the target pixel and the peripheral pixels XSn (step T1), the monochrome conversion unit 4 performs monochrome conversion (step T2).

  The white object determination unit 5 determines whether or not a white object area exists in the peripheral pixels XS1 to XS8 (step T3). Further, the target pixel determination unit 6 determines whether or not the target pixel XS0 has a sufficiently high density (step T4). If it is determined that there is no white object area in the peripheral pixels XS1 to XS8, or the target pixel XS0 is not sufficiently high in density (step T3; N, step T4; N), the correction control unit 8 determines white It is determined that the object correction process is not performed, and the parameter α for controlling the correction is set to α = 0 (step T6).

  On the other hand, when it is determined that the white object region exists in the peripheral pixels XS1 to XS8 and the target pixel XS0 has a sufficiently high density (step T3; Y, step T4; Y), the correction control unit 8 sets the target pixel XS0. Is determined to be subjected to the white object correction process. Since the thin line structure detection unit 7 determines whether or not the target pixel XS0 is a pixel forming the thin line structure (step T5), the correction control unit 8 determines that the thin line structure is not formed based on the determination result TL. If so (step T5; N), the parameter α is set to the normal parameter value v1 (step T7). On the other hand, when it is determined that the pixel constitutes a thin line structure (step T5; Y), the correction control unit 8 sets the parameter α to v2 smaller than the normal parameter value v1 (step T8).

When α is determined, the white object correction unit 9 receives the parameter α, the pixel value S0 [ch] of the target pixel XS0 and the WH [ch] obtained by the white object determination unit 5 in the above equation (2). Thus, the correction value WE [ch] is calculated (step T9). When α = 0, the original pixel value S0 is output for WE [ch] and no correction is performed as described above.
In this way, WE [ch] obtained for each color is output to the γ correction unit 11 corresponding to each color.
Note that this series of processing is performed by software, and this can be incorporated as a program.

  The γ correction unit 11 performs γ correction processing on the image data WE [ch] input based on a look-up table (LUT) prepared for γ correction. The image data WE [ch] after γ correction is output to the dither processing unit 12 corresponding to each color.

  The dither processing unit 12 performs dither processing on the input image data WE [ch] to reproduce halftones. The dithered image data WE [ch] is output to the printer 13.

  Alternatively, only the pixels that have been subjected to the white object correction process may be output in a continuous tone without performing the dither process. Specifically, the result of whether or not correction processing has been performed is stored as a flag for each pixel, pixels with a flag set are output in continuous tone, and pixels with no flag set are dithered. The process is performed like By doing so, it can be expected to suppress the occurrence of jaggy in the contour portion.

  The printer 13 is a color printer that can output C, M, Y, and K colors. The printer 13 includes a laser driver, an exposure unit, a photosensitive drum, and a developing unit for each color, and an intermediate belt, a paper feeding unit, and the like. In the printer 13, the exposure unit is driven by the laser driver for each color based on the image data WE [ch] for each color input from the image processing apparatus 1, and an electrostatic latent image is drawn on each photosensitive drum. Then, toner is deposited on the photosensitive drum by the developing unit. The toner images formed on the photosensitive drums of the respective colors are sequentially transferred onto the intermediate belt, and the toner images of the respective colors superimposed on the intermediate belt are transferred onto the printing paper at once.

  As described above, according to the present embodiment, the white object region is determined based on the display list, and among the peripheral pixels adjacent to the white object region, the peripheral pixel having a pixel value greater than or equal to the predetermined value is the pixel. Apply correction to reduce the value. Thereby, it is possible to prevent the dot gain from occurring in the peripheral pixels adjacent to the white object, and it is possible to suppress the image quality deterioration in the white object.

  Further, since the white object area is determined using the display list that is intermediate data, the white object area can be determined in units of objects. Rather than locally detecting the surrounding pixels of the white object area, it is possible to accurately detect the surrounding pixels to be actually corrected by judging the entire object that needs to prevent image quality degradation. it can. As a result, it is possible to perform correction in consideration of the entire white object.

  For example, when a gradation is drawn on the background of a white object, a gradation may be formed by adjoining a plurality of rectangular objects having different densities. In such a case, if a technique for detecting the surrounding pixels by specifying the outline of the white object from the color density difference is adopted, the outline may be detected at the boundary of the object constituting the gradation. Only the contour cannot be detected accurately. However, in the present embodiment, since the white object region is determined at the intermediate data stage, it is possible to accurately detect the peripheral pixels of the white object region without being influenced by the presence of other objects.

  Further, by referring to the attribute data TAG, only a white object having the character and line drawing attributes can be selected as a processing target of the white object correction process. This makes it possible to easily exclude an object having an attribute that is not suitable for white object correction processing, such as a photographic image, and to prevent image quality deterioration of a photographic image or the like due to the correction processing. .

  Further, the correction value for the peripheral pixel is determined based on the pixel value WH [ch] of the peripheral pixel belonging to the white object region. Therefore, it is possible to determine the correction value of the peripheral pixel in relation to the pixel value of the white object region, and to control the contrast between the white object region and the peripheral pixel.

  Further, a fine line structure constituted by peripheral pixels adjacent to the white object region is detected, and control is performed so as to reduce the degree of correction, that is, the degree to which the pixel value is reduced. As a result, the reproducibility of the detail portion of the white object can be prevented from being lost as a result of the low density of the fine line structure.

The above description is a preferred example to which the present invention is applied, and the present invention is not limited to this.
For example, the fine line structure detection processing by the fine line structure detection unit 7 may be realized in the renderer 25.
Also, the presence / absence of a white object area is determined based on the display list as intermediate data and the white area data OLB is set. However, the white object area may be determined based on the PDL data. Similarly, the attribute data TAG may be generated based on the PDL data.

  In the above description, Y = M = C = K = 0, and the object having the minimum density value is set as white area data OLB = 1, and this is treated as a white object. It is possible to perform the above white object correction processing on the density object as a white object. The renderer 25 may set OLB = 1 for pixels belonging to an object whose average value or minimum value of C, M, Y, and K is a predetermined value or less.

  When a low density object is also included as a white object, WH [ch] calculated by the white object determination unit 5 may have a positive value, and WE [ch] calculated in the white object correction process may be a positive value. Will be affected. That is, in the above equation (2), the correction amount (S0−WH [ch]) by which the original pixel value S0 of the peripheral pixels is reduced by the pixel value WH [ch] of the low density object. That is, if the density of the white object is large, the correction amount of the peripheral pixels is small, and if the density of the white object is small, the correction amount of the peripheral pixels is large. As a result, the contrast between the white object and its surroundings can be stabilized, and the reproducibility of the original image is enhanced.

  Further, when the target pixel XS0 has a thin line structure, the correction control unit 8 sets α = v2 and controls to reduce the degree of correction as a target of white object correction processing. The object may not be subjected to object correction processing. In this case, dot gain may be generated, but the reproducibility of the thin line structure is improved.

  In the above description, the white object determination unit 5 determines whether or not the target pixel XS0 does not belong to the white object area and the surrounding pixels XS1 to XS8 belong to the white object area. Although it has been determined whether or not the pixel is a peripheral pixel adjacent to the contour pixel, the present invention is not limited to this, and the white contour pixel may be detected in advance by the renderer 25.

  In this case, the renderer 25 draws only the outlines of all white objects on the page memory at the rendering stage, and outputs the drawn data as white outline data RLB instead of the white area data OLB. In the white outline data RLB, RLB = 1 is set for a pixel having a white outline, and RLB = 0 is set for a pixel having no white outline. The white contour data RLB is output to the white object determination unit 5. The white object determination unit 5 can easily determine whether or not a white object region exists around the target pixel XS0 by referring to the white contour data RLB of the peripheral pixels XS1 to XS8 of the target pixel XS0. .

Further, when the white contour data RLB is used, the following effects are considered to be obtained.
For example, consider a case where the print positions of a plurality of objects overlap as shown in FIG. FIG. 9A is a diagram showing a case where the objects partially overlap in the order of white object A, black object B, white object C, and red object D from the top.

  In this case, the first white object A is visualized as an image, but the third white object C is completely overwritten by the second black object B and is not visualized as an image. On the other hand, the white area data OLB indicates not only the first white object A but also the area of the third white object C as shown in the upper part of FIG. 9B. However, the outlines of the white objects A and C in the part where the white objects A and C overlap each other are not understood. That is, the white outline of the uppermost white object A can only be partially captured only by referring to the white area data OLB. As a result, in the portion where the white objects A and C overlap, for the black pixel adjacent to the outline of A, OLB = 1, so PW = 0 and the white object correction processing is invalidated. It becomes.

  However, this problem can be improved by referring to the white contour data RLB instead of the white area data OLB. The lower part of FIG. 9B shows the white contour data RLB in this case. Since the white contour data RLB is data of only the contour, even if they overlap, only a few portions are overwritten and the contour becomes unknown. As a result, the white object correction processing is almost performed even in the portion where the white objects A and C overlap. Thus, the processing may be performed more accurately when the white contour data RLB is used together.

1 is a diagram illustrating a system configuration of a printing system. It is a figure which shows the internal structure of the image processing apparatus of FIG. It is a figure which shows a display list example. It is a figure which shows an attention pixel and a surrounding pixel. (A) is a figure which shows the example of a white object. (B) is a figure which shows the surrounding pixel of the white object shown to (a). (C) is a figure which shows a mode that the template for thin line structure detection was applied to the white object shown to (a). It is a figure which shows the example of a template for a thin wire | line structure detection. It is a figure which shows the result of having performed the white object correction process. It is a flowchart which shows the flow of a series of processes until it performs a white object correction process with respect to a white object in an image processing apparatus. (A) is a figure which shows the example which overlaps and outputs a several object. (B) is a conceptual diagram showing white area data and white outline data for the white object shown in (a). It is a figure explaining the image quality degradation which arises by the conventional image processing method.

Explanation of symbols

10 PC
20 MFP
DESCRIPTION OF SYMBOLS 1 Image processing apparatus 2 Controller 22 CPU
23 RAM
25 renderer 26 page memory 3 line buffer 4 monochrome conversion unit 5 white object determination unit 6 target pixel determination unit 7 fine line structure detection unit 8 correction control unit 9 white object correction unit 13 printer

Claims (9)

Printing image generation means for generating image data based on intermediate data generated based on printing control data;
Whether or not each pixel constituting the image data generated by the printing image generation unit is white and has a font or vector data attribute based on the printing control data. White area data generation means for determining and generating white area data indicating the determination result;
A target pixel is sequentially set for each pixel constituting the image data, and it is determined based on the white region data whether or not a pixel of the white object region exists in a peripheral pixel adjacent to the target pixel. 1 determination means;
Second determination means for determining whether or not a pixel value of the target pixel is a predetermined value or more when it is determined by the first determination means that a pixel of the white object region exists in the peripheral pixels;
When the second determination means determines that the pixel value of the target pixel is greater than or equal to a predetermined value, the corrected pixel value of the target pixel is determined based on the pixel value of the white object region, and the determination Correction means for correcting the pixel value of the pixel of interest based on the pixel value that has been
An image processing apparatus comprising: Fine line structure detecting means for detecting pixels constituting the fine line structure among the pixels adjacent to the white object region;
A correction control means for controlling the degree of correction of the pixel by the correction means when a pixel constituting the fine line structure is detected by the fine line structure detection means;
The image processing apparatus according to claim 1, further comprising: Fine line structure detecting means for detecting pixels constituting the fine line structure among the pixels adjacent to the white object region;
A correction control unit that invalidates correction of the pixel by the correction unit when a pixel constituting the thin line structure is detected by the thin line structure detection unit;
The image processing apparatus according to claim 1, further comprising: A printing image generation step for generating image data based on the intermediate data generated based on the printing control data;
Whether or not each pixel constituting the image data generated by the printing image generation step is white and has a font or vector data attribute based on the printing control data. A white area data generation step of determining and generating white area data indicating the determination result;
A target pixel is sequentially set for each pixel constituting the image data, and it is determined based on the white region data whether or not a pixel of the white object region exists in a peripheral pixel adjacent to the target pixel. 1 determination process;
A second determination step of determining whether a pixel value of the target pixel is equal to or greater than a predetermined value when it is determined in the first determination step that a pixel of the white object region exists in the peripheral pixels;
When it is determined in the second determination step that the pixel value of the target pixel is greater than or equal to a predetermined value, a corrected pixel value of the target pixel is determined based on the pixel value of the white object region, and the determination A correction step of correcting the pixel value of the target pixel based on the pixel value that has been performed ;
An image processing method comprising: A fine line structure detection step of detecting pixels constituting a fine line structure among pixels adjacent to the white object region;
A correction control step for controlling the degree of correction of the pixel in the correction step when a pixel constituting the thin line structure is detected in the fine line structure detection step;
The image processing method according to claim 4 , further comprising: A fine line structure detection step of detecting pixels constituting a fine line structure among pixels adjacent to the white object region;
When a pixel constituting the thin line structure is detected in the fine line structure detection step, a correction control step for invalidating the correction for the pixel in the correction step;
The image processing method according to claim 4 , further comprising: Computer
Printing image generation means for generating image data based on intermediate data generated based on printing control data;
Whether or not each pixel constituting the image data generated by the printing image generation unit is white and has a font or vector data attribute based on the printing control data. White area data generating means for determining and generating white area data indicating the determination result;
A target pixel is sequentially set for each pixel constituting the image data, and it is determined based on the white region data whether or not a pixel of the white object region exists in a peripheral pixel adjacent to the target pixel. 1 determination means,
Second determination means for determining whether a pixel value of the target pixel is equal to or greater than a predetermined value when the first determination means determines that the pixel of the white object region exists in the peripheral pixels;
When the second determination means determines that the pixel value of the target pixel is greater than or equal to a predetermined value, the corrected pixel value of the target pixel is determined based on the pixel value of the white object region, and the determination Correcting means for correcting the pixel value of the target pixel based on the pixel value that has been
Program to function as. Computer
Fine line structure detecting means for detecting pixels constituting a fine line structure among pixels adjacent to the white object region;
A correction control means for controlling the degree of correction of the pixel by the correction means when a pixel constituting the fine line structure is detected by the fine line structure detection means;
The program of Claim 7 for functioning as. Computer
Fine line structure detecting means for detecting pixels constituting a fine line structure among pixels adjacent to the white object region;
A correction control unit that invalidates correction of the pixel by the correction unit when a pixel constituting the thin line structure is detected by the thin line structure detection unit;
The program of Claim 7 for functioning as.

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