JP2008225653A - Image processing method, image processor, program, and program storage medium - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To propose a method, device, and program capable of performing a partial line art processing (mixture of line art processing and outline vector processing) where, for a binary image formed by mixing line art portions and black block portions, the line art portions are thinned and line art-vector-processed and the black block portions are outline-vector-processed. <P>SOLUTION: This method includes a process of gaining an image as a process object, a process of obtaining the width of a thin line to process the object image as a line art, a process of extracting outline vector process target portions and line art vector process target portions based on the width of the thin line, a process of adding the outline vector processing to the outline vector process target portion, and a line process of adding line art vector processing to the line art vector process target portions. <P>COPYRIGHT: (C)2008,JPO&INPIT

Description

  The present invention is a method and apparatus for generating graphic vector information from a binary image stored in raster scan order, particularly for line graphic processing such as in drawings and document images. For the binary image, the line drawing portion is thinned and subjected to line core vector processing, and the black block portion relates to a method and apparatus for contour vector processing.

  In recent years, the demand for paperless has increased, and it has become frequent to digitize and reuse existing image data. Conventionally, image data has been reused by binarizing the image data, converting the image data into vector data using a vectorization technique, and using the vector data with CAD software or the like.

  As described above, with increasing demand for paperless printing, it is desired to digitize and reuse existing image data in business documents. Differences in thickness and area of each part of the original drawing also reflect the desired scaling factor (ie, the thick part in the original drawing is relatively thicker in the figure after scaling). For the reusable form of scaling, the outline vector of the binary figure in the original document is extracted. This can be realized by scaling the two-dimensional shape with an arbitrary enlargement / reduction ratio.

  By the way, even when reusing existing image data in a business document, a certain figure rather than an entire figure with an area, like the automatic input method of various handwritten drawings in the conventional CAD / CAM system etc. There are few cases where you want to treat the lines that make up the outline of a line as a simple line (straight line, [open] curve, [closed] curve, etc.), or a collection of such lines, without giving meaning to concepts such as thickness and area. Absent. In addition, there is a strong demand for reuse of line drawings that are originally drawn only with thin lines without being conscious of their thickness. That is, remove only some lines from a collection of lines, add another line, or only partial lines of each of these lines have a partial curvature, length, thickness and line type ( Editing operations such as making changes to a solid line, a broken line, an alternate long and short dash line, etc. are typical usages. As a solution to such needs, there is a line drawing vector processing called line core vector processing.

  Regarding the outline (outline) vector processing of the binary image, the applicant has already proposed Japanese Patent No. 3026592 (hereinafter referred to as Patent Document 1). In this Patent Document 1, “a predetermined position is defined as a point constituting the contour line by the state of the target pixel and its neighboring pixels, and a connection direction of the points constituting the contour line is determined by the state of the neighboring pixels. A step of determining a connection state between the points constituting the contour line and other points constituting the contour line, and updating the position of the pixel of interest on the image data in the order of raster scanning. The above steps are executed based on the state of neighboring pixels to extract contour points.

  In the above configuration, the state of the target pixel and its neighboring pixels in the image data is retained, the target pixel is extracted in raster scanning order, and the pixels in the horizontal and vertical directions are extracted based on the state of the target pixel and its neighboring pixels. Detect interval vectors. The connection state between these inter-pixel vectors is determined, and the contour of the image data is extracted based on the determined connection state of the inter-pixel vectors. ”Is proposed. This method can extract all the contour lines in the image only in one raster scan order and does not require an image memory for storing all the image data, so that the memory capacity can be reduced. Have. In addition, the contour extraction method has a significant width even for a thin line having a width of one pixel by extracting a contour not in the center position of the pixel of the input image but in the unit of the edge of the pixel. Furthermore, it has been introduced that not only the contour lines of the connected pixel regions connected in the four directions of the pixels in the original image but also the pixel regions connected in the eight directions can be extracted.

  In addition, the applicant discloses in Japanese Patent Laid-Open No. 05-108823 (hereinafter referred to as Patent Document 2) that efficient contour point extraction is possible by modularizing the vector extraction rule disclosed in Patent Document 1. .

  Furthermore, the applicant has already proposed Japanese Patent No. 3026592 (hereinafter referred to as Patent Document 3). This Patent Document 3 introduces an image processing apparatus that obtains a high-quality zoomed image using the contour information of a binary image. The proposal extracts an outline vector from a binary image, creates an outline vector smoothly scaled at a desired magnification (arbitrary) in a state of the extracted outline vector expression, and the smoothly scaled outline By regenerating a binary image from a vector, a high-quality digital binary image scaled at a desired magnification (arbitrary) is obtained. Here, as an example of a method for extracting an outline vector from a binary image, the method disclosed in Patent Document 1 (Patent No. 3026592) and Patent Document 2 (Japanese Patent Laid-Open No. 05-108823) is used as an example.

  On the other hand, for line core vector processing (hereinafter referred to as “line art vector processing” or “line art vector processing”), image processing called thinning processing has been often used. . Thinning processing is processing in which image data obtained by reading with a scanner or the like is binarized and then thinned so that the line width becomes one. Then, the obtained binary image with a line width of 1 is converted into a line core vector for each independent line or closed curve connecting between the end points and the intersections.

However, there are many binary images to be processed in which a line drawing portion and a black block portion are mixed, and the line drawing portion is thinned and processed with a line core vector processing. (Outline) Vector processing may be preferable. Up to now, it is sufficient to perform line core vector processing for thin line parts and line vector processing for black images, and to perform outline (outline) vector processing for binary images containing both line drawing parts and black block parts. The actual situation was that no proper response was taken.
Japanese Patent Registration No. 3026592 JP 05-108823 A Japanese Patent Registration No. 3049772 JP 2005-346137 A Sakai Yukiichi "Basics and Applications of Digital Image Processing" 2nd Edition, P.51-P.54, ISBN4-7898-3707-6, CQ Publisher, issued February 1, 2004

  In the present application, in view of the problems in the above-described conventional example, the line drawing portion is thinned and subjected to the line core vector processing for the binary image in which the line drawing portion and the black lump portion are mixed. An object of the present invention is to propose a method, an apparatus, and a program that enable partial line art processing (mixed line art processing and contour vector processing).

  Based on an image acquisition step for acquiring an image to be processed, a thinning target line width acquisition step for obtaining a width of a thin line for processing the processing target image as a line drawing, and a width of a thin line for processing the target image as a line drawing, A processing target area extracting step for extracting a contour (outline) vector processing target portion and a line core (line art) vector processing target portion, and a contour (outline) vector processing is applied to the contour (outline) vector processing target portion. A contour (outline) vector processing step, and a line core (line art) vector processing step of applying a line core (line art) vector processing to the line core (line art) vector processing target portion.

  Even in a line drawing that includes a black block part in a part of the image, the line core (line art) vector processing is performed on the part other than the black block portion, and the outline (outline) vector processing (or no vector processing) is performed on the other portions. However, it is not vectorized by a uniform method as in the prior art, but there is an effect that adaptive vectorization is possible.

<Embodiment 1>
A configuration example of the image processing apparatus according to the present embodiment will be described with reference to the block diagram of FIG. In the figure, reference numeral 7 denotes a central processing unit (CPU) that controls the entire apparatus. A read only memory (ROM) 6 stores programs and parameters that do not need to be changed. A random access memory (RAM) 5 temporarily stores programs and data supplied from an external device. Reference numeral 1 denotes a scanner for photoelectrically scanning a document or the like to obtain electronic image data. Reference numeral 3 denotes an image input / output interface for connecting the scanner 1 and an image processing apparatus. An image memory 2 holds image data read by the scanner 1. Reference numeral 12 denotes an external storage device including a hard disk and a memory card that are fixedly installed, an optical disk such as a removable flexible disk (FD) and a Compact Disk (CD), a magnetic or optical card, an IC card, a memory card, and the like. . Reference numeral 13 denotes an input / output (I / O (Input / Output)) interface between the external storage device 12 and the computer device. Reference numeral 15 denotes an interface with an input device such as a pointing device 10 such as a mouse or a keyboard 9 for receiving data from a user and inputting data. Reference numeral 14 denotes an interface with the display monitor 8 for displaying data held by the image processing apparatus and supplied data. Reference numeral 4 denotes a network interface for connecting to a network line such as the Internet. A system bus 11 connects the units 1 to 15 so that they can communicate with each other.

  Hereinafter, a processing procedure for realizing the present invention by a program executed on the CPU 7 will be described with reference to the flowchart of FIG.

  FIG. 1 is a flowchart showing the overall operation flow in the apparatus for carrying out the invention according to the present application. In the figure, when processing is started, in step S110, image data including an image region to be processed is input. Regarding image input, the image data read by the scanner 1 is input to the image memory 2 via the image input / output I / O 3. Further, an image including the image area to be processed may be input from the outside of the apparatus via the communication I / F 4, or image data stored in advance in the H / D apparatus 12 may be input via the I / O 13. May be read. The obtained input image is held on the image memory 3.

  Next, in step S120, the image data input in step S110 is binarized using a threshold value stored in advance in an area (not shown) on the ROM 6, thereby obtaining a binary image to be thinned. If the image input in step S110 is already a binary image, in step S120, the binary image itself input in step S110 is actually used as a thinning target binary image. The threshold value used for binarization is first displayed on the display monitor 8 through the video I / O and then through the I / O 15 while viewing the image data obtained in step S110. An instruction may be input from the operator using the keyboard 9 or the mouse 9.

Next, in step S130, and inputs the maximum line width w _k of the figure to be thinning target previously stored in the area (not shown) on the ROM 6. Regarding the information about the maximum line width wk of the figure to be thinned, first, the binary image data obtained in step S120 is displayed on the display monitor 8 via the video I / O, and this is displayed. An instruction may be input from an operator using the keyboard 9 or the mouse 9 via the I / O 15 while visually recognizing.

Next, in step S140, the binary image obtained in step S120 is contracted according to a known contraction method. That is, the target binary image area is raster-scanned in a 3 × 3 window including the pixel at the target pixel position as the central pixel and the surrounding eight pixels. In the window consisting of 9 pixels of 3 × 3, if one of the surrounding 8 pixels is a white pixel, the pixel of interest is also a white pixel (deleted), and if all of the surrounding 8 pixels are black pixels, attention is paid. The pixel value is not changed. The target pixel position is moved to the next pixel position in the raster scan within the vector processing target range of the binary image, and the same processing is repeated for all the pixels in the vector processing target region. Then, a series of contraction processing by the raster scanning is performed by the number k of rounding up the decimal part of (w _k / 2) from the information of the maximum line width w _k of the figure to be thinned obtained in step S130. repeat. In one raster scan, the boundary pixels of the white area of the black area are deleted one by one. Basically, the black area is reduced by 2 × k pixels in the vertical and horizontal directions, originally 2 × k pixels. The black area of the following thickness will disappear. When step S140 is completed, the process proceeds to step S150.

FIG. 3A shows an example of the binary image obtained in step S120. In step S130, if the maximum line width w _k of the figure to be thinning target is a 3, k is shrunk at 2 next step S140, is repeated by two raster scan. FIG. 3B shows a processing result image at the time when the first raster scan of the contraction process in step S140 is completed. FIG. 3C shows the second raster with FIG. 3B as an input. The processing result image at the time when the contraction processing by scanning is completed is shown. When k = 2, this FIG. 3C is the output result of step S140.

  Concerning shrinkage processing, for example, Yukiichi Sakai “Basics and Applications of Digital Image Processing” 2nd Edition, ISBN 4-7898-3707-6, CQ Publisher, published on February 1, 2004, P.50- It is described in P.51 etc.

  Next, in step S150, the binary image subjected to the contraction process obtained in step S140 is expanded according to a known expansion method. That is, the target binary image area is raster-scanned in a 3 × 3 window including the pixel at the target pixel position as the central pixel and the surrounding eight pixels. In the window consisting of 9 pixels of 3 × 3, if one of the surrounding 8 pixels is a black pixel, the pixel of interest is also made a black pixel (expanded), and if all the surrounding 8 pixels are white pixels, attention is paid. The pixel value is not changed. The target pixel position is moved to the next pixel position in the raster scan within the vector processing target range of the binary image, and the same processing is repeated for all the pixels in the vector processing target region. In step S140, the series of shrinking processes by raster scanning is repeated the same number of times k as the series of shrinking processes by raster scanning. In the expansion process by one raster scan, the boundary pixels of the white region of the black region are expanded by one pixel, and basically the black region is thickened by 2 × k pixels in the vertical direction and the horizontal direction, respectively. For the portion that has not disappeared in the contraction process, the amount cut in step S140 is given again. When step S150 is completed, the process proceeds to step S160.

  When the contraction process in step S140 is repeated by two raster scans, the expansion process in step S150 is also repeated by two raster scans. FIG. 3D shows a processing result image at the time when the first raster scan of the expansion process in step S150 is completed. FIG. 3E shows the second raster with FIG. 3D as an input. The processing result image at the time when the expansion processing by scanning is completed is shown. When k = 2, this FIG. 3 (e) is the output result of step S150.

  Regarding expansion processing, for example, Sakai Yukiichi "Basics and Applications of Digital Image Processing" 2nd Edition, ISBN 4-7898-3707-6, CQ Publisher, published on February 1, 2004, P.50- It is described in P.51 etc.

  In step S160, a component image to be subjected to contour (outline) vector processing is extracted from the binary image obtained in step S120 and the contraction / expansion processing result image obtained in steps S140 and S150. That is, with the image obtained by ANDing each pixel at the corresponding position when the binary image obtained as a result of step S150 and the binary image obtained in step S120 are overlaid, A component image to be subjected to contour (outline) vector processing. In the example of FIG. 3, the logical product is obtained for each pixel of FIG. 3A which is the binary image obtained in step S120 and FIG. 3E which is the output result of step S150. FIG. 3F, which is an image, is generated, and this FIG. 3F is used as a component image to be subjected to contour (outline) vector processing.

  In step S170, the component to be subject to line core vector processing from the binary image obtained in step S120 and the component image to be subject to contour (outline) vector processing obtained in step S160. Extract images. That is, an image obtained by taking an exclusive OR for each pixel at a corresponding position when the binary image obtained as a result of step S160 and the binary image obtained in step S120 are superimposed. Are component images to be subjected to line core vector processing. In the example of FIG. 3, the exclusive OR for each pixel of the binary image obtained in step S120 and FIG. 3 (f) which is the output result of step S160 is obtained. FIG. 3G, which is an obtained image, is generated, and FIG. 3F is used as a component image to be subjected to contour (outline) vector processing.

  Next, in step S180, outline (outline) vector processing is performed on the component image to be subjected to the outline (outline) vector processing obtained in step S160. Regarding the outline (outline) vector processing, for example, vectorization according to Patent Document 3 (Japanese Patent No. 3049772) is performed. That is, an outline vector is extracted from a binary image, and an outline vector that is smoothly scaled at a desired magnification (arbitrary) in the state of the extracted outline vector expression is created. Here, as an example of a method for extracting an outline vector from a binary image, a method disclosed in Patent Document 1 (Patent No. 3026592) or Patent Document 2 (Japanese Patent Laid-Open No. 05-108823) is used.

  In step S190, a thinning process is performed on the component image to be subjected to the line core (line art) vector processing obtained in step S170. Thinning processing is processing in which image data obtained by reading with a scanner or the like is binarized and then thinned so that the line width becomes one.

  For the thinning process, a thinning technique using a known Hilditch method is used. In other words, the pixel at the target pixel position is determined as a pixel to be deleted by thinning by comparing a 3 × 3 window consisting of the surrounding 8 pixels with a mask pattern prepared in advance. In the case of a deletion target pixel, the pixel at the target pixel position (x, y) is deleted. That is, the black pixel is replaced with the white pixel. On the other hand, if it is not a deletion target pixel, the target pixel position is moved to the next pixel position in raster scanning within the thinning processing range, and the same processing is repeated for all pixels in the thinning target area. Then, a series of processing by the raster scanning is repeated until no pixel to be deleted is generated in one raster scanning. The thinning process is completed when no pixels to be deleted are generated in one raster scan. Regarding the Hilditch method, for example, Sakai Yukiichi "Basics and Applications of Digital Image Processing" 2nd Edition, ISBN 4-7898-3707-6, CQ Publisher, published on February 1, 2004, P.51-P. 54 mag.

  In step S200, the binary image already thinned in step S190 is input, and line art vectorization is performed. That is, vectorization is performed for each independent line or closed curve connecting the end points and intersections constituting the thinned binary image. That is, the line cores between the end points corresponding to the line components obtained from each of the independent lines and closed curves that connect between the end points and intersections that make up the thinned binary image have been made When the vector is smoothed (function approximation), the starting point that clearly indicates the part corresponding to the end point part so that the vector corresponding to the end point part is integrated with other vectors and the end point position is not unknown. Generate end point information. Then, an auxiliary vector is inserted so that a portion corresponding to the end point portion is stored as an end point (becomes an anchor point of a Bezier curve). For the obtained (circular) vectors between auxiliary points between the end points, for example, a quadratic or cubic Bezier curve approximation is performed by the method disclosed in JP-A-2005-346137, and the end points and the intersections are connected. By leaving independent lines and closed curve portions, the obtained binary image with a line width of 1 is converted into a line vector for each independent line or closed curve connecting between the end points and intersections.

  In step S210, the contour (outline) vector for the component image to be subjected to the contour (outline) vector processing obtained in step S180 and the line core (line art) vector processing obtained in step S200. The line core (line art) vectors for the component images to be processed are integrated into the vector data of the binary image that is the vector processing target obtained in step S120.

  In step S220, the vector data obtained by the integration in step S210 is output, and the series of processes is completed.

<Embodiment 2>
In the first embodiment, after extracting the component image to be subjected to the outline (outline) vector processing in step S160, the component image to be subjected to the line core (line art) vector processing is immediately selected in step S170. Although extracted, the present invention is not limited to this. That is, immediately after step S160, the contour (outline) vector processing is performed on the component image to be subjected to the contour (outline) vector processing in step S180 in the first embodiment, and then the steps in the first embodiment are performed. The component image to be subjected to the line core (line art) vector processing in S170 is extracted, and then the thinning process in step S190 in the first embodiment is performed, and the line core (line art) vector processing in step S200 is performed. You may comprise so that the line core (line art) vector process may be performed with respect to the component image which should be made into object.

<Embodiment 3>
In the first and second embodiments, first, in step S160, contour (outline) vector processing is performed from the binary image obtained in step S120 and the contraction / expansion processing result image obtained in steps S140 and S150. We extracted the component images that should be the target. That is, with the image obtained by ANDing each pixel at the corresponding position when the binary image obtained as a result of step S150 and the binary image obtained in step S120 are overlaid, The component image to be subjected to the contour (outline) vector processing is used. Thereafter, in step S170, the object of line core vector processing is obtained from the binary image obtained in step S120 and the component image to be subjected to contour (outline) vector processing obtained in step S160. It is configured to extract a component image to be taken. That is, an image obtained by taking an exclusive OR for each pixel at a corresponding position when the binary image obtained as a result of step S160 and the binary image obtained in step S120 are superimposed. Thus, the component image to be subjected to the line core vector processing is used.

  However, the present application is not limited to this configuration. That is, first, a component image to be subjected to the line core vector processing in step S170 in the first embodiment may be extracted. That is, an image obtained by taking an exclusive OR for each pixel at a corresponding position when the binary image obtained as a result of step S150 and the binary image obtained in step S120 are superimposed. To be a component image to be subjected to the line core vector processing, and later, when the binary image obtained in step S170 is overlaid on the binary image obtained in step S120. An image obtained by taking an exclusive OR for each pixel at a position may be used as a component image to be subjected to contour (outline) vector processing.

  In the example of FIG. 3, the exclusive OR for each pixel of the binary image obtained in step S120 and FIG. 3E, which is the output result of step S150, is obtained. FIG. 3 (g), which is the obtained image, is generated, and this FIG. 3 (g) is used as a component image to be subjected to the line core (line art) vector processing. Also, FIG. 3 (f), which is an image obtained by taking the exclusive OR of each pixel of FIG. 3 (g) and FIG. 3 (a), is generated. Art) It may be a component image to be subjected to vector processing.

<Embodiment 4>
An object of the present invention is to supply a recording medium on which a program code of software for realizing the functions of the above-described embodiments is recorded to a device, and a program code stored in the recording medium by a CPU (or MPU) constituting the device. Needless to say, this can also be achieved by reading and executing. In this case, the program code itself read from the storage medium realizes the functions of the above-described embodiment, and the storage medium storing the program code constitutes the present invention.

  As a storage medium for supplying the program code, for example, a flexible disk, a hard disk, an optical disk, a magneto-optical disk, a CD-ROM, a CD-R, a magnetic tape, a nonvolatile memory card, a ROM, a DVD, or the like is used. it can.

  Further, by executing the program code read by the CPU, not only the functions of the above-described embodiments are realized, but also an operating system (OS) or the like operating on the CPU based on an instruction of the program code. It goes without saying that a case where the function of the above-described embodiment is realized by performing part or all of the actual processing and the processing is included.

  Furthermore, after the program code read from the storage medium is written in the memory provided in the function expansion board inserted into the image processing apparatus or the function expansion unit connected to the image processing apparatus, the program code is instructed. Based on this, it goes without saying that the CPU of the function expansion board or function expansion unit performs part or all of the actual processing and the functions of the above-described embodiments are realized by the processing.

A flowchart showing a series of processing procedures for realizing the present invention. Block diagram of an apparatus configuration example for carrying out the present invention Example of a series of processing stage images obtained when the present invention is implemented

Claims (8)

  Obtained from an image acquisition step for acquiring a vectorization processing target image, a line width information acquisition step for obtaining line width information for converting the vectorization processing target image into a line core vector, and the line width information acquisition step. Based on the obtained line width information, a line core vector processing component extraction step for extracting a line core vector processing target component from the vectorization target image, and a thinning step for thinning the binary image And the thinned image obtained in the thinning process step from the line core (line art) vector processing target component from the vectorization target image extracted in the line core (line art) vector processing component extraction step. An image processing method comprising: a line core (line art) vector processing step of converting the line core (line art) into a vector.   2. The image processing method according to claim 1, further comprising a contour (outline) vector processing step for converting a binary image into a contour (outline) vector, wherein a line core vector is obtained from the vectorized image. An image processing method comprising: converting a component other than a line core (line art) vector processing target component extracted in a processing component extraction step into a contour (outline) vector in the contour (outline) vector processing step.   3. The image processing method according to claim 1, wherein the line core vector processing component extraction step is based on line width information obtained from the line width information acquisition step, and a binary image contraction process is performed. And an expansion process to extract a line core vector processing target component.   Image acquisition means for acquiring a vectorization processing target image, line width information acquisition means for acquiring line width information for converting the vectorization processing target image into a line core vector, and line width information acquisition means Line core vector processing component extraction means for extracting a line core vector processing target component from the vectorization target image based on the obtained line width information, and thinning means for thinning the binary image And a thinned image obtained by the thinning processing means from the line core (line art) vector processing target component from the vectorization target image extracted by the line core (line art) vector processing component extraction means. An image processing apparatus comprising: a line core (line art) vector processing means for converting the line core (line art) into a vector.   5. The image processing apparatus according to claim 4, further comprising contour vector processing means for converting a binary image into a contour (outline) vector, wherein a line core vector is obtained from the vectorization target image. An image processing apparatus, wherein a component other than a line core (line art) vector processing target component extracted by a processing component extraction unit is converted into a contour (outline) vector by the contour (outline) vector processing unit.   6. The image processing apparatus according to claim 4 or 5, wherein the line core vector processing component extraction means is based on the line width information obtained from the line width information acquisition means, and a binary image contraction process. And an expansion process to extract a line core vector processing target component.   A program that can be executed by a computer apparatus, and that causes the computer apparatus that executes the program to function as the image processing apparatus according to any one of claims 4 to 6.   A program storage medium storing the program according to claim 7.

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