JP3476270B2 - Print data creation device - Google Patents

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a print data creating apparatus. The print data creation device is a device that converts image data for displaying an image on a monitor device in a computer system into print data that is input to a printer to print out substantially the same image.

[0002]

2. Description of the Related Art In a design system for designing products (packages, cars, etc.) and posters using a computer and a display (color monitor device), and a desktop publishing system for creating pictorial documents, an operator uses a mouse or the like. Image data is created while looking at the display using the input device, or the image data is input by a scanner device or the like. Then, while observing the display, image processing such as color assignment to each part of the image, adjustment / correction of the assigned color, and the like is performed. Then, the image processed in this way is printed by a color printer.

Further, in electronic catalogs, electronic picture books, etc., original analog images are digitized by an image scanner or the like, and color adjustment, size conversion, composition with other images or documents,
It is stored in a CD-ROM or the like after being subjected to processing such as. The image data stored in such an electronic catalog or the like is reproduced in a computer system, displayed on a display, and printed by a color printer.

In the use of a color image on such a computer, it is possible to operate the image with high precision and freedom, a human interface (computer-human interface) that is easy to use, and other processing are performed. It is demanded that the printed image can be printed with high precision and high accuracy.

Computers usually handle color image data as a set of pixels. This is called a bitmap. Each pixel in this bitmap is composed of three primary colors of R (red), G (green), and B (blue) indicated by 8-bit intensities (range of 0 to 255). When displaying such color image data on the display, each pixel (RGB
(Composed of pixels of three colors) is caused to emit light in accordance with the intensities of the RGB three primary colors in the pixels of the corresponding color image data to obtain a full-color image of about 16M colors.

On the other hand, when printing such a color image with a color printer such as an inkjet printer, it is possible to use the image data in which each of RGB is represented by 8-bit intensity as it is for various reasons described below. Can not. Therefore, this RGB 8-bit image data is converted into 2
It must be converted to printing image data in which Y (yellow) M (magenta) C (cyan) K (black) for ink is indicated by the intensity (dot) of the value. In this image conversion process,
The gamma correction process, the color conversion / black generation process, the resolution conversion process, and the binarization process are sequentially executed. The reason for each of these processes will be described below.

First, the gamma correction process will be described.
The light emission characteristic of the display with respect to the data intensity and the reflection characteristic of the print result with respect to the input data to the printer are different. That is, even if data of the same size is given,
The brightness (reflectance) of the printed result is smaller than the brightness seen on the display and the image looks dark. Therefore, gamma correction processing is performed to correct this difference (gamma characteristic). At this time, at the same time, a process of matching the black and white of the image data with the black and white of the printer (white balance process) is also performed.

Next, the color conversion / black generation processing will be described. The printer prints a color image by mixing color inks, but uses YMC (yellow, magenta, cyan) color inks for printing instead of RGB for reasons such as color development characteristics. These are RGB (red,
Since it corresponds to the complementary colors of green and blue), by calculating the complement of each intensity of RBG, it is possible to obtain the printing data in which each of YMC is represented by 8-bit intensity. In principle, YMC should be able to be used to express black, but due to the fact that it is difficult to get a pure black when superposed, and it is uneconomical due to the large amount of ink and the amount of water increases, etc. It is expressed individually using black (K) ink. That is, when YMCs are mixed with the same intensity, black (K) of theoretically the same intensity is obtained. Therefore, black (K) data of the same intensity as the minimum intensity of YMC is created and the same black as this black is produced. Correction is performed to reduce the intensity from the color data of each YMC. In this way, the color conversion / black generation processing is executed.

Next, the resolution conversion processing will be described.
Normally, the image displayed on the display has a resolution of 70-
It is displayed at about 120 [dpi (dots per inch)]. This is the pixel pitch of the display (0.
This is for adjusting to 25 to 0.35 [mm]). On the other hand, the printing resolution of the printer is different from this. For example, one of the color inkjet printers on the market recently
It is possible to print at a resolution of 80 to 300 to 720 [dpi]. Therefore, at the time of printing, it is necessary to match the image size on the display with the image size of the print result unless otherwise specified. Therefore, image resolution conversion processing is required. For example, 72 [dp
When the image of [i] is printed at 360 [dpi], a process of enlarging the number of pixels by 5 times both vertically and horizontally is performed.

Next, the binarization process will be described. As described above, the full-color image data on the computer is RG
The intensity of each B is represented by 8 bits (0 to 255). On the other hand, the printer can only represent binary values with and without dots. Even if the dot size is made variable, at most about 4 values can be represented. Therefore, it is necessary to change the 8-bit gradation data into data represented by 1 bit (or 2 bits) for each color. As this method, a density pattern method (see FIG. 8) and an error diffusion method (see FIG. 9) are known. This density pattern method is one pixel data (0 to 2
(Having an intensity of 55) is replaced with a dot pattern of n × n pixels (having an intensity of n × n + 1 ways). FIG. 8 shows an example in which the dot pattern is replaced with n = 2. In the error diffusion method, actual data (having an intensity of 0 to 255) in a target pixel is converted into dots (0 or 255).
The intensity error (difference between the actual density data and the replaced dot data) caused by this substitution is dispersed in the surroundings to represent a pseudo halftone in the entire periphery. It is a thing.

[0011]

In the density pattern method,
As a result of the conversion, the size of the image becomes n times the vertical and horizontal sizes, so the result is that the resolution conversion is also performed at the same time (FIG.
reference). Therefore, the processing can be performed at high speed. However, in the case of the density pattern method, one pixel having an intensity of 8 bits (0 to 255) is replaced with a pattern of n × n pixels, and therefore, only n × n + 1 intensity changes can be represented. That is, the strength of the actual data and 2
Since the error between the intensity after the binarization is neglected, the image quality of the image of the print result is deteriorated as compared with the original image.

On the other hand, according to the error diffusion method, since the error caused by the replacement with dots can be finally reflected, it is possible to obtain a print result relatively faithful to the original image data. However, since the size of the image is not changed even if the conversion is performed, it is necessary to perform the resolution conversion separately. In this case, binarization by the error diffusion method
It is performed for each pixel in the image data obtained as a result of the resolution conversion. Therefore, if the number of pixels of the image increases due to the resolution conversion for printing, the influence of the processing time increases due to the increase in the binarization target, and the waiting time of the operator and the usage time of the computer increase.

As described above, the binarization process in the conventional print data creating procedure has advantages and disadvantages regardless of whether the density pattern method or the error diffusion method is adopted, and there are some disadvantages. This is the first problem in the prior art.

When the density pattern method is used as the binarization processing, there is a problem of deterioration of image quality due to the type of pattern (brightness / darkness position in the pattern for representing intermediate density). That is, in the density pattern method, either the Bayer type or the fattening type is used as the pattern type.

As shown in FIG. 15, the Bayer type is a type in which dots are dispersed as much as possible in an n × n pattern and the number of dots is increased according to strength.
The Bayer type looks fine when the dot density of the print is low, but the edge extension of the dot is relatively long.Therefore, when the dot density is high, the bright part of the dot in the middle gradation is crushed due to ink bleeding. There is a problem that ends up.

On the other hand, the fatting type is shown in FIG.
As shown in FIG. 6, this is a type in which the dots are increased according to the intensity while the dots are concentrated as much as possible in the n × n pattern. The fattening type has a relatively short dot edge extension, so even if the printing dot density is high, gradation reproducibility is good, but if the dot density is low,
There is a problem that the coarseness of the image becomes noticeable.

As described above, the optimum patterns are different depending on the printing resolution, but in the past, since either pattern was uniformly selected and used, the optimum printing is performed when the resolution is changed. No image was obtained.
This is the second problem in the related art.

A first object of the present invention is to solve the above-mentioned first problem in the prior art, and in the case of performing the binarization processing and the resolution conversion processing, the data after binarization and the original image data. It is an object of the present invention to provide a print data creation apparatus that can obtain print data with high image quality that is faithful to the original image and that reflects the error between and in a relatively short time.

A second object of the present invention is to solve the above-mentioned second problem in the conventional art. Therefore, it is possible to obtain image data for printing without deterioration in image quality even if the resolution after resolution conversion processing changes. It is to provide a print data creation device capable of performing the above.

[0020]

The present invention employs the following means in order to solve the above-mentioned problems. That is, in order to solve the first problem, the first aspect of the present invention is configured such that the high speed density pattern method and the high image quality error diffusion method are combined to perform resolution conversion and binarization at the same time. Specifically, FIG.
As shown in the principle diagram of the image data (10), image data (10
In a print data creating apparatus for creating print data (101) in which pixels represented by binary values are two-dimensionally arranged based on 0), a fixed number of pixels to which a dark portion or a light portion is respectively assigned are made flat. A table (102) in which each value of the digital value is made to correspond to any of a plurality of density patterns which are arranged and the number of pixels to which a dark part is assigned is changed respectively;
Conversion means (103) for reading the corresponding density pattern from the table (102) and writing it in the print data (101) based on the digital value of each pixel in the image data (100); An error calculating unit (104) for calculating an error between the intensity of the density pattern and the intensity of the digital value written in the print data (101) by the unit (103), and the error calculating unit (104). The error distribution means (105) for adding the error to the digital value of another adjacent pixel in the image data (100) (corresponding to claim 1).

Further, in order to solve the above-mentioned second problem, the second aspect of the present invention is configured so that the density conversion pattern type can be automatically selected according to the resolution of the resolution conversion. Specifically, in the above-described first aspect, the table is provided with a plurality of types of density patterns in which the arrangement positions of the dark areas are different, and the number of pixels to which the dark areas are allocated for each type. Each of the digital values is made to correspond to each of a plurality of density patterns formed by changing the above, and a density pattern type changing means for changing the type of the density pattern read by the converting means is further provided. It is characterized (corresponding to claim 4).

The requirements for the configuration of each part will be described below. (Image data) The image data may be monochrome image data or color image data. The color image data may be RGB color image data or YMC color image data.
If the image data is RGB color image data and the print data is YMC color print data, R
It is necessary to once convert the GB color image into the YMC color image. When YMC color image data is used, YMCK including black image data K that separately expresses black
It may be color image data.

Since the digital value may have a plurality of bits, it may have two or more bits. However, the effect of the present invention actually occurs in the case of 3 bits or more. For example,
If each of RGB has 8 bits, it is possible to obtain the number of colors that is generally called full color. (Print Data) The print data can be only monochrome when the image data is monochrome image data, but can be monochrome or color print data when the image data is color image data.

The color print data can be RGB color print data, YMC color print data, or YMCK color print data. The printer to which the print data is input can be of any type. For example, inkjet printer, laser printer, dot impact printer, thermal tape printer,
Etc. The (table) density pattern is composed of a plurality of pixels arranged in a plane with a size of 2 dots or more in the vertical and horizontal directions. If the number of pixels (size) of this density pattern increases, it becomes possible to create print data compatible with high resolution, and if the number of pixels (size) of the density pattern decreases, print data compatible with low resolution. Will be able to create.

Therefore, the density pattern stored in the table may have only one size, but if a plurality of sizes are prepared, print data of various resolutions can be created in accordance with the request from the printer. You can In the case of preparing a plurality of sizes, a plurality of density patterns each having a different number of pixels to which a dark area is assigned are prepared for each size, and each density pattern is made to correspond to each value of the digital value. Further, the density pattern size changing means for changing the size of the density pattern read by the converting means is further provided (corresponding to claim 2). In this case, the density pattern size changing means may be configured to change the size of the density pattern read by the converting means based on the resolution of the image data and the resolution required for the print data (corresponding to claim 3). ).

The number of dots in the vertical and horizontal directions of the density pattern is
If the numbers are the same, the resolution can be converted to the same aspect ratio, but if the numbers are different, the resolution can be converted by changing the aspect ratio. (Error Distribution Means) The error distribution means distributes the error calculated by the error calculation means to other pixels adjacent to the pixel to be processed in the image data. At this time, the number of pixels to be distributed may be singular or plural. If there are multiple pixels, it may be possible to distribute the error to all adjacent pixels, but it is difficult to reconvert the converted pixel, so distribute the error to the unconverted pixel. Is desirable. Further, in that case, if the distribution amount to the vertically or horizontally contacting pixels is larger than the distribution amount to the obliquely contacting pixels, the shift amount of the center of gravity of the color can be suppressed to be small.

[0027]

The digital value of each pixel of the image data 100 is sequentially taken out and input to the conversion means 103. The conversion unit 103 refers to the table 102, reads the density pattern that is associated in advance as having the intensity closest to the intensity indicated by the input digital value, and writes it in the corresponding position in the print data 101. This conversion means 1
When an error occurs between the intensity of the original digital value and the intensity of the density pattern written in the print data 101 during the conversion by 03, this error is calculated by the error calculating means 104. The calculated error is the error distribution means 105.
Is added to the digital value of another pixel adjacent to the pixel currently being processed in the image data 100. When the pixel to which this addition is performed is converted by the conversion means 103, it is converted into a density pattern while reflecting this error. Therefore, it is possible to reproduce the color tone faithfully to the original image that reflects the error. Further, since the density pattern is formed by arranging a plurality of pixels in the vertical and horizontal directions, when the conversion is performed by the conversion unit 103, the resolution is inevitably increased. Moreover, since it is not necessary to perform error distribution on the pixels after the resolution is increased, the amount of calculation can be reduced. That is, by combining the high-speed density pattern method and the high-quality error diffusion method, it is possible to realize the high-speed / high-quality processing despite the simultaneous resolution conversion and binarization. Action).

If the density pattern size changing means changes the size of the density pattern read by the converting means, the resolution can be switched (the function of claim 2).

Further, if the density pattern size changing means changes the size of the density pattern read by the converting means based on the resolution of the image data and the resolution required for the print data, the required resolution of the print data is obtained. The resolution can be switched automatically in accordance with the above (operation of claim 3).

If the density pattern type changing means changes the density pattern type read by the converting means, the pattern type can be automatically selected according to the printing resolution. A high-quality processing result can be obtained even for an image (operation of claim 4).

[0031]

Embodiments of the present invention will be described below with reference to the drawings.

[0032]

First Embodiment FIGS. 2 to 7 show an image processing system to which a print data creating apparatus according to a first embodiment of the present invention is applied. <Overall Configuration of Image Processing System> FIG. 2 is a block diagram showing the image processing system in the first embodiment. As shown in FIG. 2, this image processing system includes a CPU (central processing unit) 1, and an input device 2, a memory A3, a memory B4, a memory C5, which are respectively connected to the CPU 1.
The density pattern lookup table storage unit 6, the printer 7, and the display 8 are provided.

The input device 2 is composed of a keyboard, a mouse, a pen input device and a scanner, and sends each command to the CPU.
1 and an analog image as digital image data to the CPU 1.

The display 8 displays the image data output from the CPU 1 (bitmap data consisting of a set of pixels each of which has an intensity of 8 bits for each color of RGB, hereinafter referred to as "8").
It is a device for displaying a full-color image by causing pixels on the display screen to emit light based on "bit RGB data".

The printer 7 outputs print data output from the CPU 1 (print data obtained by arranging pixels represented by binary values in a plane) (data represented by binary dots for each YMCK, hereinafter referred to as "binary value"). "YMCK data")
Each color ink (yellow ink, magenta ink,
This is a device that performs full-color printing by depositing cyan ink and black ink) in a dot shape. Specifically, it is a color inkjet printer.

The CPU 1 is a device that creates image data by executing the image creating program and displays it on the display 2, and outputs the printing image data to the printer 7 by running the print program (printer driver). is there. By executing these programs, the CPU 1 produces the various functions shown in FIG. That is, an n-value determination unit 10 that receives an input from the input device 2, an RGB-YMCK conversion unit 12, an image data creation unit 15, a display data output unit 16 that outputs 8-bit RGB data to the display 8, and an n-value determination unit. A density pattern determination unit 11, an RGB-YMCK conversion unit 12, a binarization unit 13 connected to the density pattern determination unit 11, and a print data output that is connected to the binarization unit 13 and outputs binary YMCK data to the printer 7. The functional part of the part 14 is generated. The functional units 10 to 16, the memories 3 to 5, and the density pattern lookup table 6 will be described in detail below.

The image data generator 15 converts the digital image data input from the input device 2 into 8-bit RGB data and stores it in the memory A3. Further, the image data creation unit 15 reads out the 8-bit RGB data stored in the memory A3, processes the 8-bit RGB data according to the image processing instruction from the input device 2, and returns the 8-bit RGB data to the memory A3.

The memory A3 is a memory for storing 8-bit RGB data of one screen in a table format of horizontal x columns and vertical y rows. Each column in this table corresponds to each pixel of 8-bit RGB data, and stores the intensity of each of the RGB colors forming this pixel as an 8-bit digital value (0 to 255).

The display data output unit 16 displays the screen for the screen to be processed by the image data creation unit 15.
The bit RGB data is read from the memory A3 and output to the display 8.

The RGB-YMCK conversion section 12 receives the print start command from the input device 2 and outputs the data from the memories A3 to A8.
The bit RGB data is read out, subjected to γ correction, and converted into each complementary color data of Y ₀ M ₀ C ₀ . And
The black signal K is calculated from each of the complementary color data, and the intensity of the black signal K is subtracted from each of the complementary color data to calculate the corrected color data YMC. In this way, the intensity of the color of each pixel in the 8-bit RGB data is converted into the intensity of each color of YMCK. As a result, the obtained data is Y
Bit map data (hereinafter referred to as “8-bit YMCK”) that is a set of pixels in which each MCK color is represented by 8-bit strength.
"Data"). RGB-YMCK converter 12
Separates the 8-bit YMCK data into bitmaps for each color and stores them in the memory B4.

In the memory B4, 8-bit YMCK data separated for each color is stored in a table Y prepared for each color.
Store in ~ K. Each of the tables Y to K has horizontal x columns and vertical y rows. Each column corresponds to each pixel of 8-bit YMCK data, and stores the intensity of the color forming the pixel as an 8-bit digital value (0 to 255).

On the other hand, the n-value determining section 10 determines the resolution conversion value n.
To decide. The resolution conversion value n increases the resolution (x × y) of the original 8-bit RGB data to the resolution (nx × ny) for the binary YMCK data when converting the 8-bit RGB data into the binary YMCK data. Is a value for.
The n-value determining unit 10 receives the instruction from the input device 2 or automatically based on the resolution (x × y) of 8-bit RGB data and the printing resolution of the printer, the resolution conversion value n.
To decide. The n-value determination unit 10 notifies the density pattern determination unit 11 of the determined resolution conversion value n.

The density pattern determining unit 11 as the density pattern size changing means and the density pattern type changing means is
Based on the resolution conversion value n notified from the value determination unit 10, a density pattern used when converting 8-bit RGB data into binary YMCK data is determined. This density pattern is stored in the look-up table storage unit 6 for density pattern.
A plurality of sizes of patterns (n × n pixel patterns, n = 2 to 5) corresponding to each n value are prepared for each type (Bayer type, fattening type). That is, the density pattern determination unit 11 determines a density pattern of 2 × 2 pixels when the resolution conversion value n is 2, and n
If the value is 3, a density pattern of 3 × 3 pixels is determined.

The density pattern look-up table storage unit 6 is provided with a look-up table for each n × n pixel pattern of each type. In each lookup table as a table, n × n + 1 replacement patterns in which dots (dark portions) (0 to n × n) are written in each n × n pixel pattern are replaced with 8-bit data. Stored in association with a value. For example, FIG. 8 shows a lookup table for a 2 × 2 pixel pattern of the fatting type, in which a pattern 0 of 0 dots is associated with a data value 0,
The data value 1 to 85 is associated with the pattern 1 of one dot, the data values 86 to 170 is associated with the pattern 2 of two dots, and the data values 171 to 254.
Is associated with the pattern 3 of three dots, and the data value 255 is associated with the pattern 4 of four dots.

The data value 0 corresponds to intensity 0%, and the data value 255 corresponds to intensity 100%. Similarly, data value 64 corresponds to a strength of 25% and data value 1
28 corresponds to 50% intensity, data value 192 is intensity 75
It corresponds to%. If the data values are these values, no error will occur even if the replacement pattern is replaced with the corresponding replacement pattern according to the look-up table of FIG. 8. However, if the data values are other than that, there is an error with the actual density due to the replacement. Occurs.

Returning to FIG. 2, the conversion unit, the error calculation unit, and the binarization unit 13 as the error distribution unit are RGB-YM.
Upon receiving the conversion completion notification from the CK conversion unit 12, the memory B
The data is read for each of the tables Y to K in FIG. Two
When reading each of the tables Y to K, the binarization unit 13 reads the 8-bit data of each column (each pixel) from the upper left to the lower right one by one (read from left to right in the same row,
After reading to the right end of the line, move to the left end of the next line. ).
Then, according to the pattern (type and size) determined by the density pattern determination unit 11, one of the lookup tables in the density pattern lookup table storage unit 6 is referenced to correspond to the read 8-bit data. Determine the replacement pattern. Binarization unit 13
Writes the determined replacement pattern on the table of the corresponding color in the memory C5. This writing is for memory B4
Similarly to reading from, the reading is performed in order from the upper left to the lower right. If the above error occurs due to the replacement with the replacement pattern, the binarization unit 13 performs error distribution calculation by the error diffusion method, and stores each error distribution value obtained as a result of the calculation in the memory. The values are added to the corresponding column values in the original tables Y to K in B, respectively. Therefore, when the value in the column to which these additions are made is read, the replacement that reflects this error distribution value is made. When the above process is performed for all the colors, the binary YMCK data is written in the memory C5.

The memory C5 stores binary Y values separated for each color.
The MCK data is stored in the tables Y to K prepared for each color. Each of the tables Y to K consists of horizontal nx columns and vertical ny rows. Each of the columns corresponds to each pixel of the binary YMCK data, and the intensity of the color forming the pixel is stored as a binary (1 bit) dot (0, 1).

Upon receipt of the binarization completion notification from the binarization unit 13, the print data output unit 14 reads out the data for each of the tables Y to K in the memory C5 and outputs the data to the printer 7. . In the printer 7, the binary YMCK data for each color is once written in the buffer and transferred to the inkjet drive unit prepared for each color. <Print Data Creation Process> Next, the n-value determination unit 10, the density pattern determination unit 11, the RGB-YMCK conversion unit 12 in the CPU 1,
The contents of the print data creation process executed by the binarization unit 13 will be described. This print data creation process is performed in the memory A
8-bit RGB data stored in 3 is converted to binary YM
This is a process for converting into CK data.

FIG. 3 is a flow chart showing the main routine of this print data creation processing. This main routine starts by receiving a print start command from the input device.

In the first step S001 after the start, the resolution conversion value n and the density pattern are determined. The flowchart of FIG. 4 shows a subroutine executed in step S001. In the first step S101 after entering this subroutine, an n-value designation input from the input device 2 is awaited, and the n-value determination unit 10 determines the resolution conversion value n. In the next step S102, the density pattern determination unit 11 determines the corresponding density pattern (n × n) based on the resolution conversion value n determined in step S101.
Pixel pattern) is determined (corresponding to the density pattern size changing means). That is, the look-up table to be referred to in the binarization unit 13 is specified from among the look-up tables stored in the density pattern look-up table 6. When step S102 is completed, this subroutine is terminated and the process is returned to the original main routine.

In the main routine, in the next step S002, the RGB-YMCK conversion unit 12 makes the RG
Perform B-YMCK conversion. The flowchart of FIG. 5 shows a subroutine executed in step S002.

In the first step S201 after entering this subroutine, the 8-bit RGB data of the image to be processed is read from the memory A3. In the next step S202,
Γ correction is applied to the read 8-bit RGB data. That is, the following equation (1) is executed for each color data of each pixel forming the 8-bit RGB data.

[0053]

## EQU00001 ## D '= Dmax.multidot. (D / Dmax) ^g (1) where D'is the corrected data, Dmax is the maximum data value in each color data in the 8-bit RGB data, and D is It is the original data and g is the γ coefficient.

In the next step S203, 8-bit RG
For each pixel of the B data, the intensity of each complementary color data (Yo [yellow], Mo [magenta], Co [cyan]) is calculated based on each intensity of RGB. Specifically, the following formula (2)
Execute (4).

[0055]

[Equation 2]       Yo = 255-B (2)

[Equation 3]       Mo = 255-G (3)

## EQU00004 ## Mo = 255-R (4) In the next step S204, black data (K) is generated based on the complementary color data (Yo, Mo, Co) obtained in step S203. Specifically, the calculation by the following equation (5) is performed.

[0056]

## EQU00005 ## K = Min (Yo, Mo, Co) (5) In this operation, the minimum data value of the complementary color data (Yo, Mo, Co) is set as the data value of the black data (K). It means that.

In the next step S205, step S2
Based on the black data (K) obtained in 04, step S
The under color removal processing of each complementary color data (Yo, Mo, Co) obtained in 203 is performed. Specifically, the following formulas (6) to (8)
To execute.

[0058]

[Equation 6]       Y = Yo-K (6)

[Equation 7]       M = Mo-K (7)

## EQU00008 ## C = Co-K (8) When step S205 is completed, this subroutine is terminated and the process is returned to the original main routine.

Next step S0 in the main routine
In 03, the RGB-YMCK conversion unit 12 performs the step S
8-bit YMCK obtained by 204 and S205
The data is stored in the memory B4. That is, 8-bit YMC
K data is stored for each color in each table Y to Y in the memory B4.
Write to K.

In subsequent steps S004 to 007, the binarization processing unit 13 executes the binarization processing for each color. That is, in step S004, 2 for Y (yellow)
The binarization process is performed, and when this is completed, the binarization process for M (magenta) is performed in step S005, and when this is completed, C (cyan) in step S006.
Is performed, and when this is completed, the binarization process for K (black) is performed in step S007. In each of the binarization processes of steps S004 to S007, the binarization process subroutine shown in FIG. 6 is executed for each 8-bit data of each color.

In the first step S301 after entering the subroutine of FIG. 6, one pixel (8-bit intensity data) is taken out from the table in the memory B4 corresponding to the color to be processed.

In the next step S302, step S3
Based on the intensity data value of the pixel extracted in 01, the lookup table determined in step S102 is referred to, and any replacement pattern for this intensity data value is determined.

In the next step S303, step S3
The replacement pattern determined in 02 is written in the corresponding color table in the memory C5 (corresponding to the conversion means). The position where the rewrite pattern is written in this table follows the position in the memory B4 of the original pixel data, as already described.

In the next step S304, error calculation is performed. That is, the error between the original intensity data value and the intensity value corresponding to the replacement pattern is calculated according to the following equation (9) (corresponding to the error calculating means).

[0065]

## EQU00009 ## d '(l, m) = d (l, m) -P (k) (9) where d (l, m) is the pixel (xl [first column], y
m [m-th line]) intensity data value. P (k) is the average intensity of the replacement pattern replaced in step S302. That is, in the example of FIG. 8, the average intensity of pattern 0 is 0.
The average intensity of pattern 1 is 64, the average intensity of pattern 2 is 128, the average intensity of pattern 3 is 192, and the average intensity of pattern 4 is 255.
d '(l, m) is an error associated with the replacement and can have both positive and negative polarities.

In the next step S305, step S3
Error distribution processing is performed based on the error d ′ (l, m) obtained in 04 (corresponding to error distribution means). FIG. 7 shows an error distribution processing subroutine executed in step S305.

In the first step S401 after entering the subroutine of FIG. 7, the pixel (xl + 1, ym:
The error distribution for the pixel on the right is calculated. That is, from the corresponding color table in the memory B4, the pixel (xl + 1,
The data value d (l + 1, m) of ym) is taken out and the calculation of the following formula (10) is executed.

[0068]

D (l + 1, m) = d (l + 1, m) + d ′ (l, m) × 7/16 (10) In the next step S402, the pixel (xl- 1,
ym + 1: lower left pixel) is calculated.
That is, the data value d (l-1, m + 1) of the pixel (xl-1, ym + 1) is taken out from the corresponding color table in the memory B4, and the calculation of the following formula (11) is executed.

[0069]

[Mathematical formula-see original document] d (l-1, m + 1) = d (l-1, m + 1) + d '(l, m) * 3/16 ... (11) In the next step S403, the process shown in FIG. 9 is performed. Pixel (xl, y
m + 1: the pixel directly below) is calculated. That is, from the corresponding color table in the memory B4, the pixel (x
The data value d (l, m + 1) of l, ym + 1) is taken out and the calculation of the following formula (12) is executed.

[0070]

D (l, m + 1) = d (l, m + 1) + d ′ (l, m) × 5/16 (12) In the next step S404, the pixel (xl + shown in FIG. 1,
ym + 1: lower right pixel) is calculated.
That is, the data value d (l + 1, m + 1) of the pixel (xl + 1, ym + 1) is taken out from the corresponding color table in the memory B4, and the calculation of the following formula (13) is executed.

[0071]

D (l + 1, m + 1) = d (l + 1, m + 1) + d ′ (l, m) × 1/16 (13) In the next step S405, steps S401 to S40.
Each pixel data value after error distribution obtained as a result of No. 4 is returned to the corresponding column of the corresponding color table in the memory B4. When step S405 is completed, this subroutine is ended and the process is returned to the routine of FIG.

In the routine of FIG. 6, the next step S30
At 6, it is checked if there are any unprocessed pixels remaining in the corresponding color table in memory B4. If there are still pixels, step S30
In step 7, the processing target is moved to the next pixel, and step S3
The processing of 01 to S305 is executed. And step S
When it is determined in 306 that the pixel is finished, this subroutine is finished and the processing position is returned to the original processing position of the main routine.

When the binarization process described above is completed for each color (YMCK) in steps S004 to S007 in the main routine of FIG. 3, this main routine ends and binary YMCK data is obtained in the memory C5. To be <Operation of Embodiment> According to the first embodiment, the binarization and the resolution conversion can be performed at the same time by executing the print data creating process. That is, 2 as shown in the example of FIG.
When binary conversion is performed with a pattern of × 2 pixels, the resolution of the original image can be doubled vertically and horizontally as shown in FIG. Moreover, unlike the conventional binarization by the simple density pattern method, in the first embodiment, the error caused by the binarization can be diffused to other pixels in the same manner as the error diffusion method. It is possible to obtain a print result in which the gradation is faithfully reproduced with respect to the original data.

In this case, unlike the conventional simple error diffusion method, the error is calculated by comparing the original data with the binarized result, and the error is distributed to the original data before resolution conversion. Therefore, the error distribution calculation only needs to be performed for the pixels of the original data while performing the resolution conversion at the same time as the binarization.
That is, it is not necessary to calculate the error distribution for each pixel after the resolution conversion. Therefore, in addition to the binarization calculation, the resolution conversion must be calculated, and the processing time is much shorter than that of the conventional error diffusion method in which the error distribution calculation must be performed for each pixel after the resolution conversion. .

Although it is conceivable that resolution conversion is performed after error distribution even in the conventional error diffusion method, this resolution conversion simply enlarges the dots to which the error is distributed, so that the image quality is rather contradictory. It gets worse (rougher) and unrealistic. On the other hand, according to the present embodiment, it is possible to create print data that is faithful to the original data with a small amount of calculation without causing such image quality deterioration.

The following is a comparative example of the printing results between the first embodiment and the conventional example. In this comparative example, a workstation (Sun4 / 2) was used as a computer, a natural image of 799 × 533 pixels with gradually changing color (monochromatic) density was used as 8-bit RGB image data, and a color inkjet printer was used as a printer. .

FIG. 11A shows the original image data as the first image.
It is a part of the print result binarized while the resolution is enlarged according to the embodiment. It takes about 25 seconds to obtain the entire image data including the print data. FIG. 11B is a part of the print result obtained by performing the conventional error diffusion method after simply enlarging the original image data (FIG. 11A).
Corresponding to)). It takes about 40 seconds to obtain the data of the entire image including the print data. FIG. 11C is a part of the print result (the portion corresponding to FIG. 11A) obtained by binarizing the original image data while enlarging the resolution by the conventional density pattern method. To obtain the data of the entire image including this print data,
It takes about 20 seconds.

As is apparent from this comparative example, according to the present embodiment, the print result changes in density as smoothly as the original image data while faithfully reproducing the gradation while the processing time is high. There is. In addition, the striped pattern that would appear when mere error diffusion is executed does not appear. On the other hand, when the conventional error diffusion method is performed after simple enlargement, gradation reproducibility is good but delicate striped patterns are generated, and the processing time becomes slow. Further, when the conventional density pattern method is carried out, the processing time is fast, but the density changes discontinuously, so the gradation reproducibility is very poor. From this, it can be understood that the method of the present embodiment is the best in terms of both processing time and gradation reproducibility.

[0079]

Second Embodiment A second embodiment of the present invention is based on the print resolution and the resolution of original image data (8-bit RGB data).
The n-value determining unit 10 is characterized in that the resolution conversion value n is automatically calculated. The rest of the configuration and processing contents are the same as those of the first embodiment, so description thereof will be omitted. <Print Data Creation Process> FIG. 12 is a flowchart showing the contents of the resolution conversion value n / density pattern determination subroutine executed in step S001 of FIG. 3 in the second embodiment.

In the first step S501 after entering the subroutine of FIG. 12, the print resolution of the printer [dpi: do
[ts per inch] is derived. Since the print resolution is usually built into the driver software for the printer,
Read from there. When the print resolution is not incorporated in the driver software for the printer, the operator's instruction input via the input device 2 is read.

In the next step S502, it is checked whether or not there is information about the resolution of the original image data (8-bit RGB data). The resolution information of the original image data is usually included in the header file of the image, so the header file is checked. If there is information about the resolution of the original image data, step S50.
In 4, the resolution [dpi: dots per inch] is extracted.

On the other hand, when there is no information about the resolution of the original image data, the image size (x × y cm) and the number of pixels in the x direction (r) are determined in step S503.
And read out. The image size and the number of pixels are often included in the header file of the image. And
In step S504, the following equation (14) is executed to obtain the resolution [dpi: dots per inc] of the original image data.
h].

[0083]

[Formula 14] Original image data resolution [dpi] = (r × 2.54) / x (14) In step S505 executed after step S504, the print resolution derived in step S501 and step S504 are executed. The resolution conversion value n is derived from the derived resolution of the original image. Specifically, the following equation (15) is executed.

[0084]

N = printer print resolution / original image resolution (15) In the next step S506, the density pattern determination unit 11
Determines the corresponding density pattern (n × n pixel pattern) based on the resolution conversion value n derived in step S505. That is, the look-up table to be referred to in the binarization unit 13 is specified from among the look-up tables stored in the density pattern look-up table 6. When step S506 is completed, this subroutine is ended and the process is returned to the main routine of FIG. <Operation of Embodiment> According to the second embodiment, all the operations of the first embodiment can be realized, and the resolution conversion value n can be automatically obtained. Then, the density pattern (n ×
A pattern of n pixels) can be appropriately obtained. It is only necessary to prepare a plurality of types of density patterns in advance, where n is about 2 to 5.

[0085]

Third Embodiment In the third embodiment of the present invention, when the resolution conversion value n calculated from the print resolution and the resolution of the original image data (8-bit RGB data) is not an integer, the original image The feature is that adjustment is performed so that an integer resolution conversion value n can be applied by thinning out pixels. The rest of the configuration and processing contents are the same as those of the first embodiment, so description thereof will be omitted. <Print Data Creation Processing> FIG. 13 is a flowchart showing the contents of the resolution conversion value n / density pattern determination subroutine executed in step S001 of FIG. 3 in the third embodiment.

In the first step S601 after entering the subroutine of FIG. 13, the print resolution [dpi: do of the printer is displayed.
[ts per inch] is derived. Since the print resolution is usually built into the driver software for the printer,
Read from there. When the print resolution is not incorporated in the driver software for the printer, the operator's instruction input via the input device 2 is read.

In the next step S602, it is checked whether or not there is information about the resolution of the original image data (8-bit RGB data). The resolution information of the original image data is usually included in the header file of the image, so the header file is checked. If there is information about the resolution of the original image data, step S50.
In 4, the resolution [dpi: dots per inch] is extracted.

On the other hand, when there is no information about the resolution of the original image data, the image size (x × y cm) and the number of pixels in the x direction (r) are determined in step S603.
And read out. The image size and the number of pixels are often included in the header file of the image. And
In step S604, the above equation (14) is executed to obtain the resolution [dpi: dots per inc] of the original image data.
h].

In step S605 executed after step S604, a resolution conversion value n is derived from the print resolution derived in step S601 and the original image resolution derived in step S604. Specifically, the above equation (15) is executed.

In the next step S606, step S6
It is checked whether the resolution conversion value n calculated in 05 is an integer. Then, if it is an integer, this n value can be used as it is, and therefore the processing is performed in step S613.
To jump to.

When it is determined in step S606 that the resolution conversion value n is not an integer, the resolution conversion value n calculated in step S605 is calculated in step S607.
Check whether the number after the decimal point of is greater than or equal to 0.5. Then, if the number below the decimal point is 0.5 or more, the number below the decimal point is rounded up in step S609, and if the number below the decimal point is less than 0.5, the number below the decimal point is rounded down.

In the next step S610, the following equation (1
6) is executed to calculate the resolution correction value (o).

## EQU16 ## Resolution correction value (o) = resolution of original image-print resolution / n (16) The resolution correction value (o) can have both positive and negative polarities.
That is, the resolution correction value (o) becomes positive when the rounding up in step S609 is executed, and becomes negative when the rounding up is executed in step S608.

In the next step S611, step S6
The resolution correction value (o) calculated in 10 is multiplied by the image size value (x, y) to calculate ox, oy.
In the next step S612, pixels for ox columns and pixels for oy rows are deleted from the original image. In addition, ox, o
When the polarity of y is negative, dummy pixels for ox columns and dummy pixels for oy rows are added to the original image. When the correction of the original image is completed in this way, the process proceeds to step S613.

In the next step S613, the density pattern determination unit 11 determines the resolution conversion value n derived in step S605, or step S608 or step S608.
Based on the resolution conversion value n corrected in 609, a corresponding density pattern (n × n pixel pattern) is determined. That is, the look-up table to be referred to in the binarization unit 13 is specified from among the look-up tables stored in the density pattern look-up table 6. When step S613 is completed, this subroutine is terminated and the process is returned to the original main routine. <Operation of Embodiment> According to the third embodiment, all the operations of the first and second embodiments can be realized, and even if the resolution conversion value n cannot be calculated as an integer, the original image can be obtained. By modifying the number of pixels of, the binarization can be performed using the integer resolution conversion value n.

[0095]

Fourth Embodiment A fourth embodiment of the present invention is characterized in that the density pattern type used in the pattern replacement in step S302 is switched to the Bayer type or the fattening type according to the print resolution. The rest of the configuration and processing contents are the same as those of the first embodiment, so description thereof will be omitted. <Print Data Creation Process> FIG. 14 is a flow chart showing the contents of the resolution conversion value n / density pattern determination subroutine executed in step S001 of FIG. 3 in the fourth embodiment.

In the first step S701 after entering the subroutine of FIG. 14, the print resolution [dpi: do of the printer is displayed.
[ts per inch] is derived. Since the print resolution is usually built into the driver software for the printer,
Read from there. When the print resolution is not incorporated in the driver software for the printer, the operator's instruction input via the input device 2 is read.

In the next step S702, it is checked whether or not there is information about the resolution of the original image data (8-bit RGB data). The resolution information of the original image data is usually included in the header file of the image, so the header file is checked. If there is information about the resolution of the original image data, step S70.
In 4, the resolution [dpi: dots per inch] is extracted.

On the other hand, if there is no information about the resolution of the original image data, the image size (x × y cm) and the number of pixels in the x direction (r) are determined in step S703.
And read out. The image size and the number of pixels are often included in the header file of the image. And
In step S704, the above equation (14) is executed to obtain the resolution [dpi: dots per inc of the original image data.
h].

In step S705 executed after step S704, the resolution conversion value n is derived from the print resolution derived in step S501 and the resolution of the original image derived in step S704. Specifically, the above equation (15) is executed.

In the next step S706, it is checked whether the print resolution is 180 [dpi] or 360 [dpi]. If it is 180 [dpi], the process proceeds to step S707 and 360 [dpi].
If so, the process proceeds to step S708 (corresponding to the density pattern type changing unit).

In step S707, the density pattern determination unit 11 selects the Bayer type suitable for low resolution as the type of density pattern used for the pattern replacement in step S302. Then, based on the resolution conversion value n derived in step S705, the corresponding density pattern (n × n pixel pattern) is determined. That is, the look-up table to be referenced by the binarization unit 13 is specified from among the Bayer look-up tables stored in the density pattern look-up table 6. FIG. 15 shows a Bayer type 3 × 3 pixel pattern. When step S707 is completed, this subroutine is ended and the process is returned to the main routine of FIG.

In step S708, the density pattern determination unit 11 selects a fatting type suitable for high resolution as the type of density pattern used for pattern replacement in step S302. Then, step S70
Based on the resolution conversion value n derived in 5, the corresponding density pattern (n × n pixel pattern) is determined. That is, the look-up table to be referenced by the binarization unit 13 is specified from among the fattening type look-up tables stored in the density pattern look-up table 6. FIG. 16 shows a fatting type 3
A pattern of × 3 pixels is shown. When step S708 is completed, this subroutine is ended and the process is returned to the main routine of FIG. <Operation of Embodiment> According to the fourth embodiment, all the operations of the first embodiment and the second embodiment can be realized, and the optimum density pattern type is automatically determined according to the level of resolution. Can be selectively selected and binarized.

The instruction of the printer resolution is based on the following reasons. For example, even if high-quality printing at 360 [dpi] is the standard setting, printing is performed at 180 [dpi] for trial printing or when a quick print result is desired. This enables high-speed printing. This instruction is given by the operator.

Then, the type of pattern to be used is determined based on this instruction. The Bayer type is selected when the printing dot density is low (180 [dpi]), and the fattening type is selected when the printing dot density is high (360 [dp]).
i]).

As a result, the optimum pattern is selected according to the printing resolution. Therefore, even if the resolution changes from high resolution to low resolution or vice versa, the image quality of the print result does not deteriorate.

As the density pattern, n patterns of about 2 to 5 are prepared in advance for each of a plurality of types of density patterns (Bayer type, fattening type, etc.). In each of the embodiments described above, step S20 of FIG.
The γ correction executed in 2 may be read from the lookup table instead of being calculated by the equation (1).

Further, in each of the embodiments described above, YMCK is calculated by the matrix calculation shown in the following equation (17) instead of steps S203 to S205 of FIG.
Data may be obtained.

[0108]

[Equation 17]

Each of the counts A0 to D2 is a value experimentally obtained.

[0110]

As described above, according to the first aspect of the present invention, when the binarization process and the resolution conversion process are performed, the error between the binarized data and the original image data is reflected. It is possible to obtain print data with high image quality that is faithful to the original image that has been processed in a relatively short time.

Further, according to the second aspect of the present invention, since the density pattern type can be selected even if the resolution after the resolution conversion processing changes, it is possible to obtain printing image data without image quality deterioration.

[Brief description of drawings]

FIG. 1 is a principle diagram of the present invention.

FIG. 2 is a block diagram of an image processing system to which the first embodiment of the present invention is applied.

FIG. 3 is a flowchart showing the content of print data creation processing executed in the image processing system of FIG.

FIG. 4 is a flowchart showing the contents of an n-value / density pattern determination subroutine executed in step S001 of FIG.

5 is an RG executed in step S002 of FIG.
Flowchart showing the contents of the B-YMCK conversion subroutine

FIG. 6 is a flowchart showing the contents of a binarization subroutine executed in steps S004 to S007 of FIG.

FIG. 7 is a flowchart showing the contents of an error distribution subroutine executed in step S305 of FIG.

8 is an explanatory diagram of the contents of a density pattern lookup table of 2 × 2 pixels stored in a density pattern lookup table storage unit 6 of FIG.

9 is an explanatory diagram of the processing of FIG. 7.

FIG. 10 is an explanatory diagram of a resolution conversion operation according to the first embodiment of the present invention.

FIG. 11 is a diagram showing a comparative example of the first embodiment of the present invention and a conventional example.

FIG. 12 is a flowchart showing the contents of an n-value / density pattern determination subroutine executed in step S001 of FIG. 3 in the second embodiment of the present invention.

13 is a flowchart showing the contents of an n-value / density pattern determination subroutine executed in step S001 of FIG. 3 in the third embodiment of the present invention.

FIG. 14 is a flowchart showing the contents of an n-value / density pattern determination subroutine executed in step S001 of FIG. 3 in the fourth embodiment of the present invention.

FIG. 15 is an explanatory diagram of a Bayer type density pattern composed of 3 × 3 pixels.

FIG. 16 is an explanatory diagram of a fatting type density pattern composed of 3 × 3 pixels.

[Explanation of symbols]

1 CPU 2 input devices 3 memory A 4 memory B 5 memory C 6 Look-up table storage for density pattern 7 printer 10 n value determination unit 11 Density pattern determination unit 12 RGB-YMCK converter 13 Binarization unit

Continuation of front page (56) Reference JP-A-2-122764 (JP, A) JP-A-6-164903 (JP, A) JP-A-6-62253 (JP, A) JP-A-7-38767 (JP , A) JP-A-6-284292 (JP, A) Actual development Sho 63-93136 (JP, U) (58) Fields investigated (Int.Cl. ⁷ , DB name) G06F 3/12 B41J 2/52 H04N 1/387 101 H04N 1/60

Claims (4)

(57) [Claims] 1. Based on image data obtained by arranging pixels showing a color intensity with a digital value of a plurality of bits in a plane.
In a print data creation apparatus that creates print data in which pixels indicated by values are arranged in a plane, a fixed number of pixels to which dark areas or bright areas are respectively allocated are arranged in a plane and the number of pixels to which dark areas are allocated is changed. A table in which each value of the digital value is made to correspond to any of a plurality of density patterns configured as follows, based on the digital value of each pixel in the image data,
A conversion unit that reads out the corresponding density pattern from the table and writes it in the print data, and calculates an error between the intensity of the density pattern written in the print data by the conversion unit and the intensity of the digital value. comprising an error calculating unit, and an error distribution means for adding error calculated by the error calculating means to said digital values of other pixels adjacent in the said image data, said conversion means, wherein the error is added Of the other pixels
Based on the digital value, the corresponding concentration from the table
A print data creating apparatus, which reads a degree pattern and writes it in the print data. 2. The table is provided with density patterns of a plurality of sizes having different numbers of constituent pixels, and a plurality of densities formed by changing the number of pixels to which the dark area is allocated for each size. 2. The printing according to claim 1, further comprising density pattern size changing means for changing the size of the density pattern read by the converting means by associating each value of the digital value with a pattern. Data creation device. 3. The density pattern size changing means changes the size of the density pattern read by the converting means based on the resolution of the image data and the resolution required for the print data. Item 2. The print data creation device according to item 2. 4. The table is provided with a plurality of types of density patterns in which the positions of the dark portions are different from each other, and a plurality of pixels are formed by changing the number of pixels to which the dark portions are allocated for each type. 2. The density pattern type changing means for changing the type of the density pattern read by the converting means by associating each value of the digital value with a density pattern, respectively. Print data creation device.