JPH0668271A - Image processor - Google Patents

Abstract

PURPOSE:To shorten processing time without lowering the effect of an anti- aliasing processing when the area surrounded by the edge of a vector image is painted out. CONSTITUTION:In the range of picture elements P2 to P7 of the Kth (scan) line K, vectors V1, V2 showing edges are crossed (A). Picture elements P2, P3, P6, P7 imparted with the oblique line crossing with the vectors (B) are divided into 16 sub-picture elements, respectively, are painted out (C), the number of painted-out parts is counted and each density value 8, 16, 13, 3 is obtained. Picture elements P4, P5 held between the picture elements P3, P6 are made a highest density value 16 as they are without dividing them. As a result, each density value (D) of the picture elements P2 to P7 is obtained. The more the number of interposed picture elements increases, the shorter the processing time becomes as compared with a conventional example.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image processing apparatus for filling an area surrounded by edges of an image formed by edges displayed by vectors.

[0002]

2. Description of the Related Art In order to print an image, which is input from a host machine such as a computer, in a PDL language (page description language) such as Postscript, on a printer such as a laser printer, There is an image processing device that performs image processing in the middle. In such image processing, a process of filling an area surrounded by edges of an image formed by edges displayed as vectors (hereinafter referred to as “vector image”) is frequently performed.

Hereinafter, the area of the image surrounded by the edges forming one closed curve is tentatively named "cell". When there is another closed curve inside one closed curve, the area sandwiched between the outer and inner closed curves is the cell, and the area surrounded by the inner closed curve is a cell with different density or color, and is not a cell. There are cases of white background.

For example, when printing a character, if the size is constant, a font expanded into a bitmap may be used, but if it is an enlarged character, a jagged appearance appears in the hatched portion of the stroke and it is unsightly, and a large bitmap font. If you reduce the size, you can easily lose the detail. A vector font may be used to print a beautiful character regardless of the size, but it is essential to black out the inside of the outline of the cell of the character formed by the edge displayed in the vector.

Characters image-processed in this way have smooth diagonal lines even when the size increases, but in the case of a printer that forms an image by line scanning, it has a high pixel density and high resolution like a laser printer. Even in the case of a printer, it is inevitable that the place where the line moves to the next line becomes discontinuous. Therefore, extremely fine jaggedness (called jaggies or aliasing) appears especially in a shaded portion near the horizontal. Therefore, visual smoothing is performed by anti-aliasing processing.

Alternatively, a color image described in the DPL language is not a problem if it can be printed by a color printer, but it is printed by a monochrome (monochrome) printer which is generally used (especially when graphs are often used). In this case, instead of filling with color, the pattern is set in advance corresponding to each of a plurality of colors.

[0007]

However, the anti-aliasing processing is performed when rasterizing an image on a frame memory (also referred to as bit map development) and filling each scan line (hereinafter also simply referred to as "line"). First, assuming that each pixel (pixel) is further subdivided vertically and horizontally into N × M (both are integers), sub-scan lines (hereinafter also referred to as “sub-lines”) composed of the sub-pixels are filled. .

After the N sub-lines have been filled, with respect to one line consisting of the sub-lines, the pixel is constructed for each pixel of the line.
A process of checking the attribute of each of the xM subpixels to determine the density of the pixel (to be exact, an anti-aliasing subpixel division method) has been used. Therefore, compared to the process of filling each pixel normally,
There is a problem that it takes almost N × M times.

Further, although there is no problem when it is possible to paint with a color, when filling with a repeating pattern instead of color, the smaller the cells to be filled, the smaller the number of unit patterns. The problem arises that the difference becomes unclear. Therefore, if you set the size of the unit pattern small, when you fill a large cell, you will feel as a difference in shading instead of the shape of the pattern.
Similarly, the difference between repetitive patterns becomes unclear, and the types of patterns that can be used are limited.

The present invention has been made in view of the above points, and a first object thereof is to shorten the processing time without reducing the effect of the anti-aliasing processing. Also, the second purpose is regardless of the size of the cell,
This is to make it possible to easily identify the type of the repeated pattern that has been filled.

[0011]

In order to achieve the above object, the present invention provides an image for performing a process of filling an area surrounded by edges of an image formed by edges displayed as vectors. In the processing device, a belonging area determination unit that determines whether or not each pixel forming an image is in an edge portion, and an edge of the pixel only for a pixel that is determined to be in an edge portion by the belonging area determination unit Pixel density determining means for determining the density according to the ratio of the area included in the area surrounded by the.

A second aspect of the invention is an image in which an area surrounded by edges of an image formed by edges displayed as vectors is filled with a repeating pattern of a single color preset corresponding to a designated color. The processing apparatus is provided with area detection means for detecting the area of the region surrounded by the edges, and size determination means for determining the size of the unit pattern of the repeating pattern in accordance with the area detected by the area detection means. Is.

[0013]

In the image processing apparatus according to the first aspect of the present invention, the pixel density determination unit determines the area included in the region surrounded by the edge of the pixel only for the pixel determined by the belonging region determination unit at the edge portion. Since the density of the pixel is determined according to the ratio, the processing time is extremely shortened.

In the image processing apparatus according to the second aspect of the present invention, the area detecting means detects the area of the area surrounded by the edge, and the size determining means fills the area in accordance with the detected area. Since the size is determined, the type of repeating pattern can be easily identified regardless of the size of the area.

[0015]

FIG. 2 is a block diagram showing the relationship between the host machine 10 and the printer 15. A host machine 10 such as a computer is provided with a keyboard 11 which is an input device and a CRT display 12 which is a display device. The image information described in the PDL language input from the keyboard 11 is displayed on the CRT display 12 and edited. Output to the printer 15.

The printer 15 is composed of a controller 20 and an engine 30. The controller 20 processes the image information described in the PDL language input from the host machine 10 and rasterizes it for each page, and outputs it as a video signal to the engine. Output to 30. Engine 30 which is an output device
Converts each line into an image in accordance with an input video signal, prints the formed image for one page on paper, and outputs it.

FIG. 3 is a circuit diagram showing the configuration of the controller 20 which is an embodiment of the image processing apparatus according to the present invention shown in FIG. The controller 20 includes a receiving device 21,
CPU 22, font ROM 23, RAM 24, ROM
25, a frame memory 26, and a transmitter 27, which are connected to each other by bus lines such as a data bus, an address bus, a control bus, and the like.

One page consisting of image data and pixel density, multivalued level (indicating pixel density), page size, enlargement or reduction ratio of output image, etc., input from the host machine 10 via the receiving device 21. Image information of RAM2 once
4 is stored.

Next, the CPU (central processing unit) 22, which is the belonging area determination means and the pixel density determination means, follows the program stored in the ROM 25 in advance, and the character code is a vector font stored in the font ROM 23. The image data stored in the RAM 24 is image-processed and raster-expanded in the frame memory 26 with reference to.

In accordance with a command from the CPU 22 according to the designated pixel density, the transmission device 27 outputs one page of multi-valued image data rasterized in the frame memory 26.
The image formed on the engine 30 is printed on the paper by converting the video signal for each line into a video signal synchronized with the image clock and outputting the video signal to the engine 30.

FIG. 1 is a flow chart showing a routine of a first embodiment in which the CPU 22 rasterizes image data consisting of white and black according to a program stored in the ROM 25. FIG. 4 shows each pixel by the routine. FIG. 5 is an explanatory diagram showing an example of a process of raster expansion of the image.

FIG. 4 shows the X-axis from left to right and the Y-axis from top to bottom as coordinate axes. The coordinate axes are set according to the order of image writing. The Y axis is opposite to the normal coordinate axis. The Y-axis coordinate indicates the line (scan line) number, and the X-axis coordinate indicates the pixel number in each line in the order of writing. Also, the coordinates indicating the pixel are Y
Since the coordinate value of is displayed first and the coordinate value of X is displayed later, the coordinate of a certain pixel P is indicated as P (Y, X), for example. When the line to which it belongs is clear, it is abbreviated as P (X).

FIG. 4 is an enlarged view showing a part of a pixel group forming an image. Pixels of X = 2 to 7, that is, P (2) to P (7) forming a line K of Y = K by a solid line, for example. (A) to (D) of FIG. 4 show two (straight line) vectors V1 and V2 each indicating an edge crossing each pixel and the line K, and (A) to (D) of FIG. E) shows multi-valued level data indicating the density developed in the frame memory 26 as a result of the image processing, that is, the anti-aliasing processing by the sub-pixel division method.

Further, in FIGS. 4A to 4D, each pixel has M pixels in the X direction, as shown by a broken line.
It is divided into N pieces in the Y direction and is composed of N × M subpixels. In FIG. 4, with M = N = 4, one pixel is divided into 16 sub-pixels, and one line K is divided into four sub-lines (sub-scan lines) K1 to K4. For example pixel P
The second sub-pixel from the top of (K, 4) and the third sub-pixel from the left is labeled SP (K2, 4-3), and sub-line K2 is set in advance.
If it is known, it is abbreviated as SP (4-3).

Before explaining the routine shown in FIG. 1, the flow chart of the routine of the conventional example shown in FIG. 9 will be explained in order to clarify the main part of the present invention. In the following description of each flow, for example, “step 3” is “S
3 ”is abbreviated.

When the routine of the conventional example shown in FIG. 9 starts, a large number of vectors for displaying the edges forming the image are input in S1, and it is determined in S2 whether or not the input vector is a curve. If no, that is, if it is a straight line, it jumps to S4 as it is, and if it is a curve, it proceeds to S3 and executes linear approximation to decompose it into a plurality of approximate straight lines, and then proceeds to S4.

In step S4, data indicating the starting point, the ending point (each coordinate value) of each straight line vector, etc., is converted into an edge table (hereinafter referred to as "E").
(T)). For vector registration, one of the both ends of the straight line vector having the smaller Y coordinate value is the starting point, and if the Y coordinate values are the same, the one having the smaller X coordinate value is the starting point.
When all the vectors have been registered, start point Y
Perform vector sorting in ascending order of coordinates,
Organize the data in ET.

Next, the pixel density is determined by anti-aliasing processing for each line (for line K, for example). For this purpose, for example, 1 in the RAM 24
An area for one line is prepared with the sub-pixel as one bit, and is cleared at the start of one line. For each sub-line to be filled in S6 (for example, sub-line K
1) Active edge table (hereinafter “AET”)
Update).

At S7, the intersections with all the vectors (V1, V2) on the sub-line are obtained, and they are arranged in order from the one with the smallest X coordinate value to form two edge pairs, and the sub-pixel including the intersections and one line between them is one line. Fill over the minute area (set to 1). When the sub-pixels on one sub-line have been filled, it is judged in S9 whether or not N (= 4) sub-lines, that is, one line has ended. If not, the process returns to S6 and one line ends. If so, proceed to S10.

In S10, for each pixel of one line,
Count the number of subpixels that are filled, ie 1
The values of 0 or 1 of the 6 sub-pixels are summed, and the density of the pixel is determined in S11 according to the count number. For example, when W subpixels out of 16 are filled, if the density is 0 for white and 16 for the highest density of black, the density of the pixel is W as it is.

In the case of the line K shown in FIG. 4, SP (2-4) to (6-2) in the sub-line K1 and SP (2-
3) to (6-3), K3 SP (2-3) to (7-1), K
4, SP (2-2) to (7-2) are painted out, and therefore, as shown in FIG.
The values of W in (7) are 8, 16, 16, 16, and 1, respectively.
It becomes 3,3.

If the densities of pixels for one line are determined and stored in the frame memory 26, the process proceeds to S12, where it is determined whether all the lines have been completed.
Return to, and if it ends, end. That is, the above 1
By repeating the pixel density determination for each line for all the lines for one page, raster expansion of the entire image is completed on the frame memory 26, but all pixels to be filled are decomposed into sub-pixels and filled. Approximately N × compared to the case without aliasing processing
A processing time of M times (16 times in this example) is required.

The first invention shortens this processing time,
Moreover, in order to obtain the same image quality as the conventional one, the density is determined by dividing the pixels of the edge portion into sub-pixels and painting them, and the maximum density of the pixels inside the edge is determined as it is, for example 16. Is. Explaining the example shown in FIG. 4, (A) in FIG.
As shown in FIG. 2, the two vectors V1 and V2 crossing the line K form an edge pair, and the range between them is painted black.

Calculating the coordinates X1 and X2 of the points where the vectors V1 and V2 having the slopes dX1 and dX2 respectively cross the upper side of the line K, as shown in FIG. 4B, the vectors V1 and V2 are calculated. Since the interval between the upper and lower sides is 1, the coordinates of the point where X intersects with the lower side of the line K are calculated as (X1 + dX1) and (X2 + dX2), respectively. Here, the slope dX is dX = ΔX / ΔY.

From now on, as shown by the sparse hatching in FIG. 4B, the pixel at the edge portion is P
It can be seen that they are (2), P (3) and P (6), P (7). The anti-aliasing sub-pixel division method is performed only for the pixels at this edge part,
As shown in (C) of FIG. 4, P (2), P (3) and P (6), P (7) are divided into sub-pixels and filled in, respectively. And 13,3 are obtained.

Next, all the pixels sandwiched by the pixels in the edge portion of the edge pair are filled in pixel units without being divided into subpixels. That is, as shown in FIG. 4D, P (3), P at the edge portion
Fill P (4) and P (5) sandwiched by (6). However, in practice, it is not necessary to paint P (4) and P (5) of the area for one line prepared in the RAM 24, and P (4) and P (P) of the line K on the frame memory 26 are filled.
The values of W in (5) may be set to 16 as shown in (E) of FIG.

The flow chart of the first embodiment shown in FIG. 1 summarizes the above processing as a flow, and the same step numbers are assigned to the same parts as those in the flow chart of the conventional example shown in FIG. And detailed description is omitted. The newly added steps are S20 to S26. In FIG. 1, the process from the start to the creation of the edge pair in S7 is exactly the same as the conventional example.

After the edge pair is created in S7, S20 is executed.
Whether or not the sub-line to be processed in 1 is the first sub-line obtained by dividing the line to which the sub-line belongs to, for example, line K
If so, it is determined whether or not it is the subline K1, and if not, the process jumps to S22, and if it is the first subline, S
In step 21, the pixel at the edge of the line is determined from the information of the edge pair, and the information is stored until the processing of the line is completed.

In S22, it is determined whether or not the pixel is in the edge portion. If not, the process jumps to S23, and if it is in the edge portion, the subpixel of the pixel is filled in in S8 and the process proceeds to S23.

In S23, it is judged whether or not the painting of the pixels in the edge portion for one line is completed. If not, the process returns to S6, and if completed, the process proceeds to S24 for each pixel in the edge part. After counting the number of filled sub-pixels, the process proceeds to S11, determines the pixel density according to each count number, and proceeds to S25. S23, S
In No. 24, the processing is limited to the pixels in the edge portion, and the contents are almost the same as S9 and S10 (FIG. 9).

In S25, the density of the pixel sandwiched by the pixels in the edge portion of the pair is set to the maximum value, for example, 16 according to the pixel information in the edge portion stored in S21.
Then, by repeating the processing until it is determined in S26 that the processing for one line is completed, the densities of all the sandwiched pixels become the maximum value (black). Finally, in S12, it is determined whether or not all the lines are completed. If not, the process returns to S6, and if completed, the process ends.

As described above, the sub-pixel division method, which requires about N × M times, is executed only for the pixels in the edge portion, and the pixels in the area surrounded by the edge are directly determined as the maximum density value. Therefore, the processing time is significantly reduced as compared with the conventional processing. In the example shown in FIG. 4, the number of pixels in the edge portion is four, but the number of pixels in the sandwiched area is two. Therefore, the processing time is only reduced by about 2/3. The greater the number of pixels to be filled in, the greater the effect. When 1/8, 1/4, and 1/2 of the screen are black, the processing time is reduced to approximately 1/2, 1/4, and 1/8, respectively. It

FIG. 5 is a functional block diagram showing the configuration of the second embodiment of the image processing apparatus according to the second invention, and is mechanically a part of the controller 20 shown in FIG. Figure 6
FIG. 6 is a flowchart showing an example of a routine of the second embodiment shown in FIG. FIG. 7 shows an example of a pattern used for it, and FIG. 8 shows a cell (a figure surrounded by an edge) processed by using the pattern shown in FIG. 7 and a processed result, respectively.

Of the images described in the DPL language, it is often easy to identify them by color-coding them with colors showing their attributes, such as maps and graphs. The display device of the computer is a color CRT or color LC.
Since color display devices such as D (liquid crystal display) are often used, there is no problem in displaying.

However, since the color printer is expensive and the printing time is long when the image is printed on the paper, the monochrome printer is used in almost all cases. Therefore, a plurality of printers corresponding to a plurality of colors are used. Will be filled with the pattern.

The pattern shown in FIG. 7 is one of many types, and in this embodiment, patterns A to D of the same type but different in size are prepared. The pattern A is used for processing cells having an area of 16 or more,
The pattern B is used for treating cells with an area of 15 or less and 11 or more, the pattern C is used for treating cells with an area of 10 or less and 6 or more, and the pattern D is used for treating cells with an area of 5 or less. Conventionally, a pattern of one type and one size, such as the pattern A, has been used regardless of the cell area.

8A is a cell before pattern filling processing (hereinafter simply referred to as "pattern processing"), and FIGS. 8B and 8C are pattern processing in the second embodiment and the conventional example, respectively. The resulting cell is (A) in the figure,
In (B) and (C), similar cells A1, B1, C1 and A2, B2, C2 having different sizes from each other are shown.

In the conventional pattern processing, since only the prepared pattern A is used, as shown in FIG. 8C, the type of pattern can be easily identified in the cell C1 having a large size, but In the small cell C2, the type of pattern is difficult to understand, and for example, it is easy to confuse it with the pattern formed by the upper right diagonal line. If the pattern D is prepared, the small cell C2 can be identified, but the large cell C1 is too fine to identify.

In the functional block diagram of the second embodiment shown in FIG. 5, the pattern determining section 40 includes an area detecting section 41 as an area detecting section, a color / pattern converting section 42, a pattern storing section 43, and a size. It is composed of a pattern selecting section 44 which is a determining means. Corresponding to the circuit diagram shown in FIG. 3, for example, the area detection unit 41 and the pattern selection unit 44 are the CPU 22, and the color / pattern conversion unit 42 is the RA.
The nonvolatile RAM in M24 and the pattern storage unit 43 correspond to the font ROM 23, respectively.

The area detection unit 41 inputs graphic information such as the number of pixels contained in the cell A1 or A2, detects the area of the graphic, and outputs an area signal indicating the area to the pattern selection unit 44. The color / pattern conversion unit 42 inputs a color signal indicating a color for filling the cell A1 or A2, determines the type of pattern corresponding to the designated color, and outputs it as a pattern signal to the pattern selection unit 44.

The pattern selection unit 44 inputs the area signal and the pattern signal, determines a pattern having a size corresponding to the area of the figure among the designated types of patterns, and selectively selects the corresponding pattern from the pattern storage unit 43. , And output as a decision pattern. Depending on the respective conditions, the decision pattern may be a unit pattern or a developed pattern in which the unit patterns are two-dimensionally arranged.

Before explaining the pattern processing routine in the second embodiment, a flow chart of the conventional routine shown in FIG. 10 will be described in order to clarify the main part of the present invention. When the routine of the conventional example shown in FIG. 10 starts, a vector indicating an edge is input in S31, and S
At S32, S31 is repeated until one path is closed, that is, the edge forms a closed curve to form one cell.

When the path is closed, the fill information following the vector data, that is, the information of the designated color including the black (solid pattern) and the white (white) for filling the formed cells is input in S33, and the blank information is input in S34. If it is blank, it jumps to the end. If not, that is, if the pattern is filled, the process proceeds to S35, a pattern of the type corresponding to the designated color is set, and the cell is filled with the pattern set in S36 to end.

In the pattern processing routine of the second embodiment shown in FIG. 6, the same steps as those of the routine of the conventional example shown in FIG. 10 are designated by the same step numbers and their detailed description is omitted. Instead of S35 in FIG. 10, newly provided steps are S40 to S42.

If it is determined in S34 that the area is not white but filled, the process proceeds to S40 (the area detection unit 41) detects the area to be filled in the cell, and in S41 (color
A pattern of a size corresponding to the area is selected from patterns of a type corresponding to the designated color (by the pattern conversion unit 42 and the pattern selection unit 44). After the pattern selected in S42 is set, the cell is filled with the pattern set in S36 to end.

The graphic processed in this way is shown in FIG.
As shown in (B) of FIG. 3, the cell B1 of the same color and of a large size has the cell B1 of a small size due to the rough pattern A.
2 is filled with a finer pattern C, respectively. Therefore, the cells B1 and B2 are identified as having the same color, and there is no fear of being confused with another pattern (color).

That is, even if the size of the figure is changed, it is easy to identify the pattern. Therefore, it is possible to increase the number of types of the pattern and cope with more colors than in the conventional case. Moreover, since the capacity of the font memory for one pattern is significantly reduced by using the repeated pattern, even if a large number of patterns having different sizes are prepared for each type, the font RO
The capacity of M23 will not increase.

[0058]

As described above, the image processing apparatus according to the first invention can significantly reduce the processing time without deteriorating the effect of the anti-aliasing processing. Further, the image processing device according to the second aspect of the invention, regardless of the size of the cell (the figure surrounded by the edge),
An image that can easily identify the type of the repeated pattern that has been filled is output.

[Brief description of drawings]

FIG. 1 is a flowchart showing a processing routine in a first embodiment of an image processing apparatus according to the first invention.

FIG. 2 is a block diagram showing a relationship between a host machine and a printer according to the present invention.

FIG. 3 is a circuit diagram showing an example of a configuration of the controller shown in FIG.

FIG. 4 is an explanatory diagram showing an example of a process in which each pixel is raster-developed by the processing routine shown in FIG.

FIG. 5 is a functional block diagram showing the configuration of a second embodiment of the image processing apparatus according to the second invention.

FIG. 6 is a flowchart showing a processing routine in the second embodiment shown in FIG.

FIG. 7 is a diagram showing an example of a pattern used in the second embodiment shown in FIG.

FIG. 8 is a diagram showing a graphic processed by using the pattern shown in FIG. 7 and a processed result.

FIG. 9 is a flowchart showing a processing routine of a conventional example corresponding to the flow shown in FIG.

10 is a flowchart showing a processing routine of a conventional example corresponding to the flow shown in FIG.

[Explanation of symbols]

10 Host Machine 15 Printer 20 Controller (Image Processing Device) 22 CPU (Affiliated Area Determining Means, Pixel Density Determining Means) 23 Font ROM 26 Frame Memory 30 Engine 40 Pattern Determining Section 41 Area Detecting Section (Area Detecting Means) 44 Pattern Selecting Section (Size determination means)

Claims (2)

[Claims] 1. An image processing apparatus for performing a process of filling an area surrounded by an edge of an image formed by edges displayed as vectors, it is determined whether or not each pixel forming the image is at an edge portion. Belonging area determining means, and only for pixels determined by the belonging area determining means to be in an edge portion, the density is determined according to the ratio of the area included in the area surrounded by the edge of the pixel. An image processing apparatus comprising: a pixel density determining unit. 2. An image processing apparatus for performing a process of filling a region surrounded by the edge of an image formed by edges displayed in a vector with a repeating pattern of a single color set in advance corresponding to a designated color. In the above, an area detecting means for detecting the area of the region surrounded by the edge, and a size determining means for determining the size of the unit pattern of the repeating pattern according to the area detected by the area detecting means are provided. An image processing device characterized by: