JPH0457175A - Graphic processor - Google Patents

Abstract

PURPOSE:To find an are ratio at high speed by providing a coordinate value approximation means, a storage means, and an approximate area ratio decision means. CONSTITUTION:When vector data passes a closed interval, intersections Xa, Xb show input/output coordinate values for the edge part picture element of the vector data. Firstly, plural coordinate value approximate points are provided on the edge part picture element, and the coordinate values Xa, Xb are approximated to the nearest coordinate value approximate points. For example, the input/output coordinate value Xa is approximated to a coordinate value approximate point P4 by comparing the distance of the approximate point P4 near to Xa with that of a point P8. Thence, the coordinate value Xb is approximated to an approximate point P14 nearer to Xa. The area of an image part is calculated as the area of a triangle formed with the coordinate value approximate points P4, P14, and P16. The area of the edge part picture element is calculated, and is stored in a LUT as an approximate area ratio (k). Thereby, the approximate area ratio (k) of the edge part picture element can be easily obtained from the LUT.

Description

DETAILED DESCRIPTION OF THE INVENTION [Field of Industrial Application] The present invention relates to a graphic processing device for removing jagged edges of an output image, and more particularly, to a graphic processing device that can perform anti-aliasing processing at high speed. Regarding.

[Conventional technology]

In the field of computer graphics, when displaying an image on a CRT, which is an output medium, a technique called anti-aliasing processing is used to make the displayed image more beautiful. This process is performed on the jagged part (called alias) on the stairs as shown in Fig. 25(a).
Figure 25(b) visually displays the displayed image by applying brightness modulation to
It purifies the body as shown in the figure.

The anti-aliasing processing method is shown below.
■Uniform averaging method, ■weighted averaging method, zero convolution integral method, etc. are known.

■The uniform averaging method calculates each pixel (picture element) to N*M (N,
After decomposing the image into subpixels (M is a natural number) and performing rask calculation at high resolution, the brightness of each pixel is determined by taking the average of N*M subpixels. Figure 26(a)
, (b), anti-aliasing processing using the uniform averaging method will be specifically explained. If the edge of the image overlaps a certain pixel (here, it is assumed that the image is connected to the bottom right of the diagonal line), and when anti-aliasing processing is not performed, as shown in Figure (a),
The brightness kid of this pixel is assigned the highest brightness of the displayable gradations (for example, kid=255 for 256 gradations). When performing anti-aliasing processing on this pixel using the uniform averaging method with N=M=7, as shown in the same figure (b), the pixel is decomposed into 7 and 7 sub-vixels, and sub-pixels covered by the image are Count the numbers. The count number (28) is divided by the total number of subvixels in one pixel (49 in this case), normalized (averaged), and multiplied by the maximum brightness (255) to calculate the brightness of that pixel. In this way, in the uniform averaging method, the brightness of each pixel is determined by taking into account how the image differs from each pixel.

■Weighting is based on the averaging method.The averaging method is a partial modification of the uniform averaging method. In contrast, the weighted averaging method assigns a weight to each subpixel, and the effect on the brightness of that subpixel depends on which subpixel the image falls on. Trying to be different. still,
The weight at this time is determined using a filter.

With reference to FIGS. 27(a) and (b), FIG. 26(a)
An example is shown in which the weighting is performed using the same dividing method (N=M=7) and the averaging method on the same image data.

FIG. 27(a) shows a filter (here, conef
i I ter ), and the corresponding sub-pixel is given the same weight as this characteristic. For example, the weight of the upper right corner subpixel is 2. When an image is applied to each subpixel, the weight value given by the filter characteristics becomes the count value of that subpixel. FIG. 6B shows different display patterns of the image depending on the weight of the subpixels. In this case, if you count the subpixels in the image with weight, it will be 199. This value is divided by the sum of the filter values (33G in this case) corresponding to the uniform averaging, averaged, and multiplied by the maximum brightness to calculate the brightness of this pixel. In addition, the filter shown in Fig. 28 (a
), (b), (c), and (d) are known.

0-fold convolutional integral method The convolutional integral method is a method that also refers to the appearance of surrounding pixels when determining the brightness of one pixel. That is, the area around one pixel whose brightness is to be determined is N
``XN'' pixel is considered to correspond to a pixel of the average-average method or the weighted-average method. Figure 29 shows the integration method of convolution with a 3x3 pixel reference. In this figure, the luminance The pixel for which we are trying to determine the
The subpixel is the subpixel that is counted.

Each pixel is divided into 4*4. Therefore, in this case, a 12*]2 filter should be used. This method has the effect of removing high frequency components contained in a vector image.

On the other hand, a publishing system using a personal computer,
With the spread of so-called DTP (desk top publishing), systems for printing vector images, such as those used in computer graphics, have become widely used. As a typical example, there is a system using Adobe's Post Softlip 1. PostScript is a page description language (Page Descriptor).
scriptionLan'guage:Hereafter, P
It belongs to a language genre called DL (described as DL), and describes the form of the contents of a single document, including the text (letter part), graphics, and their arrangement and appearance. It is a programming language for writing text, and in such systems, vector fonts are used as character fonts. Therefore, even if characters are scaled, the print quality can be significantly improved compared to systems that use pit map fonts (for example, conventional word processors, etc.). There is an advantage that printing can be performed in a mixed manner.

However, the resolution of the laser printers used in these systems is at most 240 dpi to 400 dpi.
There are many things (, computer graphics CRT
As with display, there is a problem in that aliasing occurs due to the low resolution. For this reason, even in printing using a laser printer, there is a need to perform anti-aliasing processing to improve the quality of the printed image.

[Problem to be solved by the invention]

However, according to conventional graphic processing devices, one pixel is divided into multiple subpixels (for example, 49 subpixels), and the area ratio (brightness) is calculated by counting the number of subpixels that are filled. Therefore, there is a problem in that it takes time to calculate the area ratio, which hinders improvement in display speed or printing speed. In particular, the convolution method has problems in that it requires a large amount of calculation and affects multiple pixels, making it difficult to improve processing speed.

The present invention has been made in view of the above, and an object of the present invention is to quickly obtain an area ratio without dividing subpixels or counting the number of filled pixels.

[Means to solve the problem]

In order to achieve the above object, the present invention adjusts the output of edge pixels of vector data based on the area ratio to be filled, and performs anti-aliasing processing to smoothly express jagged edges (aliases) of the output image. In the graphic processing device that executes the processing, a plurality of approximate coordinate values are provided on the edge pixel, and the input/output coordinate values for the edge pixel of vector data and the coordinate values of the end points within the edge pixel are converted into a plurality of coordinate values. The coordinate value approximation means approximates the closest coordinate value approximate point among the approximate points, and the edge storage means that stores approximate area ratios set for each classification of edge pixels, the presence or absence of coordinate approximate points 5 end points approximated by the coordinate value approximation means, and the storage based on the type of edge. An object of the present invention is to provide a graphic processing device comprising approximate area ratio determining means for reading a corresponding approximate area ratio from the means and determining the approximate area ratio of edge portion pixels.

[Effect]

The graphic processing device of the present invention uses the coordinate value approximation means to approximate the input/output coordinate values for the edge portion pixels of vector data and the coordinate values of the end points within the edge portion pixels to the nearest coordinate value approximation point. Thereafter, the approximate area ratio determination means stores the approximate area ratio set in advance for each classification of edge pixels based on the coordinate approximate point approximated by the coordinate value approximation means, the presence or absence of an end point, and the type of edge. The corresponding approximate area ratio is read from , and the approximate area ratio of the edge portion pixel is determined.

〔Example〕

Hereinafter, an image forming system to which the graphic processing device of the present invention is applied as a PDL controller will be described as an example. ■ Overview of anti-aliasing processing (main part of the present invention), ■ Block diagram of the image forming system, ■ PDL controller (the present invention). (Graphic processing device), ■Configuration of image processing device, ■Configuration of multivalued color laser printer, ■Configuration and operation of developing section of multivalued color laser printer, ■
A detailed explanation will be given in the order of multi-value driving of the driver.

■Outline of anti-aliasing processing of the present invention The graphic processing device (hereinafter referred to as PDL controller) of the present invention (referred to as roller 200) processes input and output coordinate values for edge pixels of vector data, and end points within edge pixels. The coordinate values of are each approximated to the coordinate value approximate point, and the coordinate value approximate point, and
Based on the edge type, approximate area ratio of edge pixels (
concentration). Below, Figures 1(a) to (
The anti-aliasing process in the graphic processing apparatus of the present invention will be explained in detail with reference to h).

As shown in Fig. 1(a), if one pixel (i.e., an edge pixel) through which vector data on a Yo-Y scan line passes is a closed interval, then when vector data passes through a closed interval, , and the four sides (top, bottom, left and right sides) forming the closed section, two intersections Xa and xb are formed as shown in the figure. These two intersections Xa and Xb are the input/output coordinate values for the edge pixel of the vector data.

First, a plurality of coordinate value approximate points are provided on the edge pixel, and the aforementioned input/output coordinate values Xa and Xb are each approximated to the coordinate value approximate point among the coordinate value approximate points, and the coordinate value approximate points are A method for determining the area ratio of the corresponding edge pixel will be explained. In this embodiment, as shown in FIG. 1(b), the coordinate value approximate points are gate, P2. P3...PI
Set 16 coordinate value approximate points of 3. The coordinate value of the coordinate value approximate point is the X'y゛ coordinate (sub-coordinate on the edge part pixel)
The above are shown in the table below.

For example, the input/output coordinate values Xa as shown in FIG. 1(c)
, Xb, the area ratio of the edge pixels is determined as follows. The input/output coordinate value Xa is approximated to the closer coordinate value approximate point P4 by comparing the distances between the coordinate value approximate points P4 and P8, which are closer to Xa. Next, the input/output coordinate value xb is determined by comparing the distance between the coordinate value approximate points PI3 and PI3 close to xb.
It is approximated to the closer coordinate value approximation point P14. Here, since the edge part pixel is the left edge (the right side of the straight line is the image part), the area of the image part is the coordinate value approximate point P4. PI/l,
It is calculated as the area of the triangle formed by the three points of PI3.

In addition, as shown in FIG. 1(d), the input/output coordinate values Xa,
For the edge pixel of Xb, the input/output coordinate value Xa is approximated to the closer coordinate value approximate point P3 by comparing the distances between the coordinate value approximate points P3 and P4, which are closer to Xa. next,
The input/output coordinate value xb is approximated to the closer coordinate value approximate point P14 by comparing the distance between the coordinate value approximate point P13 and PI3, which are closer to xb. Here, since the edge portion pixel is the left edge (the right side of the straight line is the image portion), the area of the image portion is the coordinate value approximate point P3. PI3. PI3. P4
It is calculated as the area of the trapezoid formed by the four points.

Furthermore, input and output coordinate values Xa, as shown in FIG. 1(e),
For the edge pixel of Xb, the input/output coordinate value Xa! ,t,
By comparing the distances between coordinate value approximation points P2 and P3 that are closer to Xa, the coordinate value approximation point +13 is approximated. Next, the input/output coordinate value xb is approximated to a closer coordinate value approximate point P15 by comparing the distance between the coordinate value approximate point P14 near xb and PI3. Here, since the edge pixel is the left edge (the right side of the straight line is the image part),
The area of the image portion is determined by the coordinate value approximate point P3. PI3. I'
16. It is calculated as the area of the rectangle formed by the four points P4.

In the present invention, a combination of coordinate value approximate points that divide a pixel into two as shown in FIGS. 1(C), (d), and (e),
The area of the edge pixel is calculated in advance based on the left and right sides of the edge, and is stored in the LUT (Look Up Table) as an approximate area ratio as shown in FIG.

As a result, for example, the approximate area ratio of the edge pixel in FIG. 1(d) is determined by the coordinate value approximate point P3. P14. And, based on the left edge, approximate area ratio 5/ from L U T 1
9 can be easily obtained.

On the other hand, as shown in FIG. 1(f), when there is an end point Xc in the edge pixel, the input and output coordinate values Xa,
Xb is the coordinate value approximate point P15. By approximating PI3 and approximating the end point Xc to the coordinate value approximation point P6,
The area of the image part is determined by the coordinate value approximate point P6°PI3. PI5
It can be calculated as the area of the triangle formed by the three points. Therefore, in the present invention, as shown in FIG. 1(h), the input/output coordinate value Xa.

An approximate area ratio k of the edge pixel is determined by a combination of the coordinate value approximate point of xb and the coordinate value approximate point of the end point Xc, and is stored as LUT2.

As a result, for example, the approximate area ratio of an edge pixel where the coordinate value approximate point of the input/output coordinate value is PI, P8, and the coordinate value approximate point of the end point is P5, is obtained from LUT2 in Figure 1 (b). 3/9 can be easily obtained.

As described above, the area ratio is calculated by providing a plurality of coordinate value approximate points and storing the approximate area ratio k of the edge portion pixel obtained based on the coordinate value approximate points in the LUT in advance. Approximate area ratio k can be obtained immediately from LUT without having to do so.

■Block diagram of the image forming system The image forming system of this embodiment uses the Page Description Language output from DTP (Desk Top Publishing).
e: hereinafter referred to as PDL language)) and image information read by an image reading device. The configuration of the image forming system of this embodiment will be described below with reference to FIG.

The image forming system includes a host computer 100 that creates a document written in PDL language (Postscript language is used in this embodiment);
A PDL controller (graphic processing device of the present invention) that applies anti-aliasing processing to the PDL language sent page by page from ) 200, an image reading device 300 that reads image information via an optical system unit, and a PDL controller 200. Or.

An image processing device 400 that inputs the image output from the image reading device 300 and performs image processing (details will be described later), and a multi-value color laser printer that prints the multi-value image data output from the image processing device 400. printer 50
0, PDL controller 2001 image reading device 30
01 Image processing device 400. and a system control section 600 that controls the multivalued color laser printer 500.

■The configuration and operation of the PDL controller is shown in Figure 3.
The configuration of the DL controller 200 is shown as follows: a receiving device 201 that receives the PDL language sent from the host computer 100; a CPU 202 that controls storage of the PDL language received by the receiving device 201 and executes anti-aliasing processing; An internal system bus 203, a RAM 204 that stores the PDL language to be transferred from the receiving device 201 via the internal system bus 203, a ROM 205 that stores anti-aliasing programs, etc., and multi-value RGB image data that has been subjected to anti-aliasing processing. Page memory 206 to store and page memory 2
The RGB image data stored in 06 is processed by image processing device 4.
00, and the system control unit 60.
0, and an I10 device 208 that performs transmission and reception with 0.

Here, the CPU 202 receives the P received by the receiving device 201.
The DL language is stored in the RAM 204 via the internal system bus 203 according to the program stored in the ROM 205. After that, you will receive one page of PDL language,
Once stored in the RAM 204, the graphic elements in the RAM 204 are subjected to anti-aliasing processing based on the flowchart described later, and the multivalued RGB image data is stored in the plain memory section of the page memory 206. (consisting of a memory section and a feature information memory section).

The data in the page memory 206 is then transferred to the transmitter 2
07 to the image processing device 400.

The operation of the PDL controller 200 will be described below with reference to FIGS. 4(a) and 4(b).

FIG. 4(a) shows a flowchart of processing performed by the CPU 202. As described above, the PDL controller 200 performs anti-aliasing processing on the PDL language sent page by page from the host 1-computer 100, and converts it to red (R).

Developed into three-color images: green (G) and blue (B).

In the PDL language, all graphics and characters are written in hectares, and as the name "page writing language" indicates, image information is processed in units of pages. Furthermore, one page is made up of at least one bus, with each path being made up of one or more elements (graphic elements and text elements).

First, when the PDL language is input, it is determined whether the element is a curved line, and if it is a curved vector, it is approximated to a straight line vector and registered as a straight line element (line) in the work area. This is performed for all graphic and character elements within one path, and linear elements are registered in the work area for each path (processing 1).

Then, the linear elements of the work area registered in this path unit are sorted by the starting X coordinate of the straight line (Processing 2
).

Next, in process 3, while updating the X coordinate one by one,
Performs filling processing using scanning lines. For example, in Figure 4 (
When performing the bus filling process shown in b), the elements on the side across which the scanning line yc to be processed and the real value of the X coordinate across the scanning line yc (x, x2x1χ shown in Figure 5)
) and AET (Active Edge Table
: A table that records the X coordinate of the edge portion appearing on the scanning line). Here, since the order of the elements registered in the work area is the order in which they were registered in process 1, they are not necessarily registered in order of decreasing X coordinate across the scanning line yc. For example, in the processing IQ, if a straight line element passing through scanning lines yc and X3 in FIG. will be registered. Therefore, after the AET is registered, the elements on each side within the AET are sorted in descending order of X coordinate. Then, pair the first two elements of AET and fill in between them (filling process using scanning lines). Anti-aliasing processing is achieved in this filling processing by adjusting the density and brightness of the pixels in the edge portion according to the approximate area ratio. Then remove the processed edge from the AET, update the scanline (update the Repeat the process.

Above processing 1. Processing 2. The work in process 3 is executed pass by pass and repeated until all passes for one page are completed.

Next, the anti-alias song process executed during the scan line filling process of process 3 described above will be described in detail with reference to the flowchart of FIG. 4(C).

Here, for example, in process 1 of FIG. 4(a),
), this figure has the following elements.

(a) Hector of the five lines AB, BC, CD, DE, and EA (represented by real numbers) (b) Color and brightness values inside the figure This figure is created as shown in Figure 5 (b) by the above-mentioned operation. , is divided into seven straight line vectors (expressed as real numbers) extending in the main scanning direction. At this time, in this embodiment, the following information is added to the starting and ending points of the seven straight line heters.

That is, (c) the starting point coordinate value (real number expression) of the vector element composing the starting point and ending point of the straight line vector ((a) above) (d) the vector element composing the starting point and ending point of the straight line vector Slope information (*) Characteristic information of the start point and end point of a straight line vector (right edge, left edge, end point of a figure, line of 1 dot or less, intersection of straight lines, etc.) In the scan line filling process, edge part pixels When detected, anti-aliasing processing shown in the flowchart of FIG. 4(C) is executed. Figure 1 (a
) to (h), in the present invention, the corresponding approximate area ratio k is obtained from the LUTI and LUT2 based on the coordinate value approximate point.

First, it is determined whether an end point of vector data (straight line element) exists in an edge pixel (S401). If there is no end point, the input/output coordinate values of the edge pixels are set to the coordinate value approximate point (
5402), and based on the coordinate value approximation point of the approximated input/output coordinate values and the left and right sides of the edge, the corresponding approximate area ratio from the LUTI (see Figure 1 (g)). Input k (5403). On the other hand, if an end point exists, the input/output coordinate values of the edge pixel and the coordinate values of the end point are approximated to the coordinate value approximate point 5404), and the coordinate value approximate point of the approximated input/output coordinate value and the coordinate value of the end point are approximated. Based on the value approximate point, the corresponding approximate area ratio k is input from LUT2 (see FIG. 1(h)) (S405). Thereafter, an approximate area ratio k is set as the area ratio of the edge portion pixels, and the process ends (S406).

The process shown in the flowchart of FIG. 4(C) is called as a subroutine when an edge pixel is detected in the scan line filling process of process 3.

The CPU 202 repeats the above processing up to the last pixel of the scanning line (y coordinate), and at the same time updates the contents of (c) above using the information of (2) above. The approximate area ratio of the figure in FIG. 5(a) obtained by the anti-aliasing process in this way has a value as shown in FIG. 6.

Here, if the figure in FIG. 5(a) has a white background color (
The figure color is red (maximum brightness: 25) on top of (maximum brightness: 255)
5), from the approximate area ratio k (see Figure 6), the brightness values for each color of the figure are (red), (red), (
Kb (green) and Kb (blue) are obtained based on the following formula.

Kr −KR+Xk + KR2X(1k)K9
= Kr + Xk + KG2X (1k) Kb - Kn
+Xk + KB□x (1k) However, K, ll+
K c + and K 8+ are respectively the above (II
) represents the brightness value of the color (red, green, blue, respectively) of the figure given by KR□, Kcz, Kn□ represents the brightness value of each previously painted color. Furthermore, KR□, KG2 K
oz refers to data in each plane memory section corresponding to RGB of the page memory 206.

The brightness value obtained in this way is ,K.

The brightness value of K is stored as RGB image data in the corresponding plane memory section of the page memory 206, as shown in FIGS. 7(a), (b), and (C). For comparison, RGB image data without anti-aliasing processing is shown in Figure 8(a).
b), shown in (C).

(2) Configuration of Image Processing Apparatus The configuration of the image processing apparatus 400 will be explained with reference to FIG. 9.

CC in the image processing device 400 and the image reading device W300
The three-color image signals read by D7r, 7g, and 7b are converted into black (BK), yellow (Y), magenta (M), and cyan (C) recording signals necessary for recording. Similarly, the RGB image data given from the PDL controller 200 described above is converted into black (BK).
, yellow (Y), magenta (M), and cyan (C
) into each recording signal. Here, the image reading device 3
The mode for inputting image signals from 00 is copy machine mode, P
The mode in which RGB image data is input from the DL controller 200 is called a graphics mode.

The image processing device 400 includes CCDs 7r, 7g, and 7b.
The color gradation data obtained by A/D converting the output signal of
a shading correction circuit 401 that performs correction for sensitivity variations, etc. of internal terminal elements of 7r, 7g, and 7b;
a multiplexer 402 that selectively outputs either the color gradation data output from the shading correction circuit 401 or the color gradation data (RGB image data) output from the PDL controller 200 according to the above-described mode;
A T correction circuit 40 inputs the 8-bit data (color gradation data) output from the multiplexer 402, changes the gradation according to the characteristics of the photoreceptor, and outputs it as 6-bit data.
3, and the (R) and green (G) output from the T correction circuit 403.
), a complementary color generation circuit that converts 6-bint gradation data indicating the gradation of blue (B) into gradation data (6-bint) of cyan (C), magenta (M), and yellow (Y), which are the respective complementary colors. 405, Y output from the complementary color generation circuit 405,
A masking processing circuit 406 that performs predetermined masking processing on each of M and C gradation data, and a masking processing circuit 406 that performs predetermined masking processing on each gradation data of M and C, and
, a UCR processing/black generation circuit 407 that inputs each gradation data of C and executes OCR processing and black generation processing;
The 6-bit gradation data of Y, MC9, and BK outputted from the processing/black generation circuit 407 is converted into 3-bit gradation data Yl, Ml, CL, and BKI, and is used in a multi-value color laser printer. A gradation processing circuit 408 outputting to the laser drive processing unit 502 inside the image processing device 500 and a synchronization control circuit 40 for synchronizing each circuit of the image processing device 400.
It consists of 9.

Although the details are omitted, the T correction circuit 403 has a configuration in which the gradation can be changed arbitrarily using the operation buttons on the console 700.

Further, as an algorithm used in the gradation processing circuit 408, a multi-value dither method, a multi-value error diffusion method, etc. can be applied. For example, a dither matrix of the multi-value dither method is
x3, multilevel color laser printer 500
The number of gradations is the product of the area gradation of 3×3 and the multilevel level of 3 focuses (that is, 8 levels), and becomes 3×3×3=72 (gradations).

Next, the processing of the masking processing circuit 406 and the UCR processing/black generation circuit 407 will be explained.

Generally, the arithmetic expression for the masking process of the masking process circuit 406 is as follows: Y, , Ml, C,: data before masking process Yo,
M o, Co : Data 2 days after masking process Also, the arithmetic expression for UCR processing of the UCR processing/black generation circuit 407 is generally expressed by the following equation.

Therefore, in this embodiment, new coefficients are obtained using the product of both coefficients.

In this embodiment, a new coefficient (such as "all") for performing this masking process and OCR process simultaneously is calculated and obtained in advance, and further, using the new coefficient, the masking process circuit 4
06 scheduled input values Y,,M.

Output value (yo', etc.: U) corresponding to C8 (6 bits each)
A value that is the calculation result of the CR processing/black generation circuit 407 is obtained and stored in a predetermined memory in advance.

Therefore, in this embodiment, the masking processing circuit 406 and U
The CR processing/black generation circuit 407 is composed of a set of ROMs, and the data at the address specified by the manual input Y, M, and C of the masking processing circuit 406 is given as the output of the UCR processing/black generation circuit 407.

In addition, for boat fishing, the masking processing circuit 40G has Y,
The M and C signals are corrected, and the UCR processing/black generation circuit 407 performs correction for color balance in the superimposition of each color (・ner). , black component data BK is generated by manually combining three color data of Y, M, and C, and the output data of each color component of Y, M, and C is corrected to the value obtained by subtracting the black component data BK. Ru.

In the above configuration, the γ correction circuit 403 executes processing based on the T correction conversion graph shown in FIG. 10, and the complementary color generation circuit 405 generates complementary colors shown in FIGS. Suppose that the processing is executed based on the conversion graph for
Figure 7(a).

The RGB image data shown in (b) and (C) is γ
Correction circuit 403. Complementary color generation circuit 405. Masking processing circuit 406. Then, through the UCR processing/black generation circuit 407, it is converted as shown in FIGS. 12(a), (b), (C), and (d).

Furthermore, if the gradation processing circuit 408 uses a Bayer-type 3×3 multilevel dither matrix shown in FIG. 13, Y in FIGS. ,M
.

The data for C and BK are shown in Figure 14 (a) and (b), respectively.
, (C).

It is converted into the data shown in (d).

For comparison, when data without anti-aliasing processing (data in FIGS. 8(a), (b), and (C)) is processed by the image processing device 400, the first
It is converted as shown in Figures 5 (a), (b), (cl, and (d)).

■Configuration of multi-value color laser printer (configuration and operation of developing section of multi-value color laser printer) First, with reference to the control block diagram shown in FIG. Explain.

A photoreceptor development processing unit 501 uniformly charges the surface of a photoreceptor drum (described later), exposes the charged surface to a laser beam to form a latent image, develops the latent image with toner, and transfers it to recording paper. The details will be explained later, but the development and development of BK data is
A black developing/transfer section 501bk that performs transfer, a cyan developing/transfer section 501C that develops and transfers C data,
Cyan development/transfer section 501 that develops/transfers M data
m, and a cyan developing/transfer section 501y that develops and transfers Y data.

The laser drive processing unit 502 includes the image processing device 4 described above.
It outputs a laser beam by inputting the 3-bit data of Y, M, C, and BK output from 00 (in this case, image density data). Input buffer memory 503y,! 503
a laser diode 504 that outputs laser beams corresponding to Y, M, C, and BK;
y.

504m, 504c, 504bk and laser diode 504y, 5'04m, 504c.

Drivers 505y each drive 504bk.

It consists of 505m, 505c, and 505b.

In addition, the black developing/transfer section 5 of the photoreceptor development processing section 501
01bk, the laser drive processing unit 502, the laser diode 504bk, and the driver 505bk are called a black recording unit BKU (see FIG. 17). Similarly, a cyan developing/transfer section 501c, a laser diode 504c, a driver 505c, and
The buffer memory 503c is combined with a cyan recording unit CU (see FIG. 17) and a magenta developing/transfer section 501m.
, laser diode 504m, driver 50
5m and a buffer memory 503m are combined into a magenta recording unit MU (see Fig. 17), a yellow developing unit, and a buffer memory 503m.
Transfer section 501y, laser diode 504y,
The combination of the driver 505y and the buffer memory 503y is called a yellow recording unit (YU) (see FIG. 17). As shown in the figure, these recording units are arranged around a conveyor belt 506 that conveys the recording paper in the following order in the conveying direction of the recording paper: a rough rack recording unit (BKU), a cyan recording unit CU, a magenta recording unit MU, and a yellow recording unit YU. It is arranged.

Due to this arrangement of each recording unit, the laser diode 5 for black exposure starts exposure first.
04bk, and the laser diode 504y for yellow exposure starts exposure last. Therefore,
There is a time difference in the order of exposure start between each laser and diode 1,
Data recorded during the time difference (output of the image processing device 400)
In order to hold the data, the laser drive processing section 502 is equipped with the three sets of buffer memories 503y, 503m, and 503c described above.

Next, the configuration of the multivalued color laser printer 500 will be specifically explained with reference to FIG.

The multivalued color laser printer 500 includes a channel heald 506 (for conveying recording paper) and recording units 1-YU, M disposed around the conveyor belt 506 as described above.
Paper cassette 5 containing U, CU, BKU and recording paper
07a, 507b and paper feed cassettes 1507a, 507b
Paper feed rollers 508a and 50 that feed the recording paper from
8b, a registration roller 509 that aligns the recording paper sent out from the paper feed cassettes 507a and 507b, and a conveyance bell h506 to transport the recording units 1 to BKU,
It consists of a fixing roller 5]0 that sequentially transports CU, MU, and YU and fixes the transferred image on the recording paper, and a paper discharge roller 511 that discharges the recording paper to a predetermined discharge section (not shown). be done. Here, each recording unit 1 to YU MU, C
U, BKU are photosensitive drums 512y, 512m, 51
2c, 5] 2bk and photoreceptor drums 5], 2y, respectively.
, 512m.

Charger 51 that uniformly charges 512c 51.2bk
3y, 513m, 513c, 513bk, and polygon mirrors 514y, 514m for guiding the laser beam to the photosensitive drums 512y, 5]2m, 512c, 512bk.
, 5], 4c514bk and motor 515y, 515m
515c, 515bk and photosensitive drum 512y512
toner developing devices 516y, 51.6m, 516c, and 516bk that develop the electrostatic latent images formed on the respective 1-toners of the corresponding colors;
Transfer charger 517 that transfers the developed toner image onto recording paper
y, 517m, 517c, and 517bk, and a cleaning device 5]8y that removes toner remaining on the photoreceptor drum wide 512y, 512m, 512c, and 512bk after transfer;
It consists of 518m, 518c, and 518bk. Note that 519y, 519m, 519c, and 519bk are the photosensitive drums 5]2y, 512m, 512c, and 51, respectively.
A COD line sensor for reading a predetermined vacuum provided on the 2bk is shown, and although the details are omitted, the process status of the multi-color laser printer 500 is detected by this sensor.

In the following configuration, the operations of the yellow recording unit I-YU will be explained using exposure, development, and transfer as an example.

Figure 18 (a) and (b) are yellow recording units) YU
The configuration of the exposure system is shown. In the figure, a laser beam emitted from a laser diode 504y is reflected by a polygon mirror 514y, passes through an f-theta lens 502y, is further reflected by a mirror 521y522y, and is irradiated onto a photoreceptor F ram 512y through a dustproof glass 523y. be done. At this time, the laser beam is
4y is driven to rotate at a constant speed by the motor 515y, so it moves in the direction along the axis of the photosensitive drum 512y (main scanning direction). Further, in this embodiment, a photosensor 524y is provided to detect the base point for tracking the scanning position of the main scan, so that the laser beam at the non-exposed position is detected. Since the laser diode 504y is activated to emit light based on the recording data (3-bit data from the image processing device 400), multilevel exposure corresponding to the recording data is performed on the surface of the photoreceptor drum 504y. The surface of the photosensitive drum 504y is uniformly charged in advance by the charger 513y as described above, and an electrostatic latent image corresponding to the original image is formed by the exposure. The electrostatic latent image is developed by a yellow developing device 516y to become a yellow toner image. This toner image is transferred from the cassette 507a (or 507b) to the paper feed roller 508a (or 508) as shown in FIG.
b), and is transferred by the registration roller 509 to the recording paper conveyed by the conveyance bell l-506 in synchronization with the formation of the 1 to toner images of the black recording unit BKU.

The other recording units BKU, CU, and MU have similar configurations and perform similar operations, but the black recording unit BKU is equipped with a black toner developing device 516bk and forms and transfers a black toner image, and the cyan recording unit C
U includes a cyan toner developing device 516c, which forms and transfers a cyan toner image, and a magenta recording unit M.
U includes a magenta toner developing device 516m, which forms and transfers a magenta toner image.

(2) Multi-value drive of the driver The driver 505y, 505m, 505c 505b drives the corresponding laser diode 504y, 504m based on the 3-bit data of Y, M, C, and BK sent from the image processing device 400.

It performs control for multi-value driving of 504c and 504bk, and power modulation, pulse modulation, etc. are generally used as the driving method.

Hereinafter, multi-value drive by power modulation applied in this embodiment will be explained in detail with reference to FIGS. 19(a), (b), (C), and (d). In addition, drivers 505y, 505m
.

505c, 505b, and laser diode 504
y, 504m, 504c, and 504bk each have the same configuration, so here, the driver 505y and laser diode 504y will be explained as an example.

As shown in FIG. 19(a), the driver 505y has a laser diode ON/OFF @ path 550 which is applied to a predetermined LD drive circuit and turns the laser diode 504y ON/OFF. A D/A converter 551 converts 3-bit image density data (here, Y data) into an analog signal, and an analog signal based on the image density value is input from the D/A converter 551 to drive the laser diode 504y. Current (LD drive current) Id to laser diode on10f
The constant current circuit 552 supplies the f circuit 550.

Here, the LD drive clock is turned on “0” at °′1゛.
As shown in FIG. 19(b), the laser diode on10f, f circuit 550 turns off the laser diode 504y accordingly. Furthermore, since the LD drive current Id and the laser beam power are in a proportional relationship, by generating the LD drive current Id based on the image density data value, the laser beam power output corresponding to the image density data value can be obtained. become.

For example, as shown in FIG. 19(b), when the image density data value is "4" (data N-1 in the same figure), the corresponding LD drive current 1d is supplied by the constant current circuit 552, The laser beam power of the laser diode 504y is level 4. Furthermore, when the image density data value is "7'' (data N in the same figure), the constant current circuit 552
The corresponding LD drive current Id is supplied, and the laser beam power of the laser diode 504y becomes level 7.

Next, referring to FIG. 19(C), the laser diode o
n10ff circuit 550. A specific circuit configuration of the D/A converter 551 and the constant current circuit 552 is shown. The laser diode on10ff circuit 550 includes TTL inverters 553 and 554, differential switching circuits 555 and 556 that perform onloff toggle operation, and VGl>
When VO2, differential switching circuit 555 is on, differential switching circuit 556 is off, VGI<V
At O2, the differential switching circuit 555 is off.

Resistors R2 and R form a voltage dividing circuit that generates VO2 that satisfies the conditions for the differential switching circuit 556 to be turned on.
It consists of 3. Therefore, when the LD drive clock is "1", the output of the inverter 554 generates VGl, satisfying the above condition (VGi>VO2), the differential switching circuit 555 is on, and the differential switching circuit 556 is off. Then, turn on the laser diode 504y.

Conversely, when the LD drive clock is "'O", there is no output from the inverter 554, so the above condition (MC
I<VO2), and the differential switching circuit 555
is off, the differential switching circuit 556 is on,
Turn off the laser diode) = 504y.

The D/A converter 551 includes a latch 557 that latches the input image density data while the LD drive clock is 1°, a generator 558 that provides the maximum output value V ref, and a generator 558 that latches the input image density data. Maximum output value V re
3-bit D that outputs analog data Vd based on f
/A controller 559. Incidentally, the relationship between Vd, image density data, and maximum output values ■, □ is expressed by the following equation.

The constant current circuit 552 includes the laser diode 504 in the laser diode ON10ff circuit 550 as described above.
It supplies a current of y, 1 to Runsister 5
60, and resistors R4 and R5. The output Vd from D/A converter 551 is applied to the base of transistor 560 to determine the voltage applied to resistor R4. In other words, since the current flowing through the resistor R4 is approximately equal to the collector current of the l·Lancy star 560, the current Id flowing through the laser diode 504y is controlled by Vd.

FIG. 19(d) shows the output VGI of the latch 557 mentioned above.
, Vd, and ld. Here, Vd is image density data (3-bit data:
Based on the 8th floor 8 lap data from 0 to 7), ■r□×077
Values are taken in 8 steps from 7/7 to 7/7, and Id is 1. - Shows 8 levels of I7. Laser diode 504y 8 levels of Id (Io
-Level o, r, -Levelt..., I7-Level 7)
Accordingly, a latent image as shown in FIG. 20 is formed on the photosensitive drum 512y.

In the graphic processing apparatus of the present invention, the l-ner image shown in FIG. 21 is finally formed on the recording paper for the pentagon ABCDE shown in FIG. 5(a) by the configuration and operation described above. -Resolution of laser printer for boat fishing is 240
Considering that the resolution is ~400 dpi, the density of the edges of the figure becomes visually thinner due to the anti-aliasing process. FIG. 22 shows a toner image of pentagon ABCDE without anti-aliasing processing;
As is clear from a comparison between the figure (toner image of the present invention) and FIG.
becomes visually smoother.

Further, in this embodiment, multi-value drive using power modulation is applied, but it goes without saying that the same effect can be obtained by using multi-value drive using mid-pulse modulation.

For reference, FIG. 23 shows the change in latent image form depending on the level of modulation during pulses, and also shows the toner image when modulation during pulses is applied to the pentagon ABCDE shown in FIG. 5(a). It is shown in FIG.

〔Effect of the invention〕

As explained above, the graphic processing device of the present invention adjusts the output of the edge portion pixels of the vector deck based on the area ratio to be filled, and smoothly expresses the jaggedness (alias) at the edge portion of the output image. In a graphic processing device that performs anti-aliasing processing, input and output coordinate values for edge pixels of hector data and coordinate values of end points within edge pixels are set in a plurality of approximate coordinate values on edge pixels. , a coordinate value approximation means for approximating the closest coordinate value approximate point among a plurality of coordinate value approximate points, and a combination of a plurality of coordinate value approximate points, the presence or absence of an end point in an edge pixel, and the type of edge. The edge area pixels are classified based on the storage means that stores the approximate area ratio set for each classification of edge area pixels, the presence or absence of the coordinate approximate point end point approximated by the coordinate value approximation means, and the type of edge. based on,
Since the approximation area ratio determination means reads the corresponding approximate area ratio from the storage means and determines the approximate area ratio of the edge pixel, the area ratio can be determined at high speed without dividing subpixels or counting the number of filled pixels. You can ask for it.

[Brief explanation of the drawing]

FIGS. 1(a) to (h) show the graphic processing device of the present invention &J.
Explanatory diagram showing an overview of anti-aliasing processing, Part 2
The figure is an explanatory diagram showing the configuration of the image forming system of this embodiment,
Figure 3 is an explanatory diagram showing the configuration of the PDL controller;
FIG. 4(a) is a flowchart showing the operation of the PDL controller, FIG. 4(b) is an explanatory diagram showing bus filling processing, FIG. 4(C) is a flowchart showing antialiasing processing of the present invention, Figures (a) and (b) are explanatory diagrams showing the linear hector division of a figure, Figure 6 is an explanatory diagram showing the approximate area ratio after anti-aliasing processing, and Figures 7 (a), (b), ( c) is an explanatory diagram showing the ROB image data stored in the plain memory section of the page memory, Figures 8(a), 2(b), and (C) are the plain memory of the page memory when anti-aliasing processing is not performed. FIG. 9 is an explanatory diagram showing the configuration of the image processing device, FIG. 10 is an explanatory diagram showing the γ correction conversion graph of the γ correction circuit, and FIG. 11 (a ), (b), and (C) are explanatory diagrams showing conversion graphs for complementary color generation used in the complementary color generation circuit,
Figure 12(a). (b), (c), (d) are shown in Figure 7 (a), (b)
, Explanatory diagram showing the state in which the RC, B image data shown in (C) is output from the UCR processing/black generation circuit, 1st
Figure 3 is an explanatory diagram showing a Bayer type 3 x 3 multilevel dither matrix, Figure 14 (a), (b), (C), (
d) is Fig. 12 (a), (b), (C). FIG. 15(a) is an explanatory diagram showing the state in which the data of Y, M, C, NY3 in (d) is converted by the gradation processing circuit. (b), (c), (d) are shown in Figure 8 (a), (b).
, FIG. 16 is a control block diagram showing a multi-value color laser printer, and FIG. 17 is a multi-value color laser printer.
Explanatory diagram showing the configuration of a laser printer, Fig. 18 (a)
), (b) is an explanatory diagram showing the configuration of the exposure system of the yellow recording unit, FIGS. 19(a), (b), (C),
(d) is an explanatory diagram showing multi-value drive by power modulation, the second
Figure 0 is an explanatory diagram showing the state of the latent image depending on the level of power modulation, and Figure 21 is the pentagon ABCDE shown in Figure 5 (a).
FIG. 22 is an explanatory diagram showing the final toner image of pentagon ABCDE without anti-aliasing processing. FIG. 23 is an explanatory diagram showing the state of the latent image depending on the level of pulse width modulation. Figure 24 is Figure 5 (
An explanatory diagram showing a toner image when pulse width modulation is applied to the pentagonal ABCDE shown in a), FIG. 25(a), (
b) is an explanatory diagram showing conventional anti-aliasing processing;
FIGS. 26(a) and 26(b) are explanatory diagrams showing anti-aliasing processing using the uniform averaging method, and FIG. 27(a),
(b) is an explanatory diagram showing anti-aliasing processing using weighted averaging method; Fig. 28 (a), (b), (C
), (d) is an explanatory diagram showing an example of a filter used in the weighted averaging method, and FIG. 29 is an explanatory diagram showing a convolution method with reference to 3×3 pixels. Description of symbols Post computer PDL controller Receiving device 202 ・Internal system bus RAM 205 Page memory I10 device Image reading device Image processing device OM Transmitting device PU 20 B-m= 300-・Multinary color laser printer system control unit

Claims (1)

[Claims] A graphic processing device that adjusts the output of edge pixels of vector data based on the area ratio to be filled, and executes anti-aliasing processing to smoothly express jagged edges (aliases) of an output image. A plurality of coordinate value approximate points are provided on the edge pixel, and input/output coordinate values for the edge pixel of the vector data are set;
and a coordinate value approximation means for approximating the coordinate value of an end point in the edge pixel to the closest coordinate value approximate point among the plurality of coordinate value approximate points, and a combination of the plurality of coordinate value approximate points in advance; a storage means that classifies the edge pixels based on the presence or absence of an end point in the edge pixel and the type of edge, and stores an approximate area ratio set for each classification of the edge pixel; and the coordinate value approximation. Approximate area ratio determining means reads the corresponding approximate area ratio from the storage means based on the coordinate approximate point approximated by the means, the presence or absence of an end point, and the type of edge, and determines the approximate area ratio of the edge portion pixel; A graphic processing device characterized by comprising: