JP4812893B2 - Image data compression method and decompression method - Google Patents

Description

  The present invention relates to an image data compression method and decompression method.

  In order to effectively utilize resources for processing image data, a method of compressing and further restoring image data is widely used.

  As such an image data compression method and restoration method, there is known a method in which all image elements included in image data are compressed by one algorithm and further restored. In the known compression method and restoration method of image data, image data including various types of image elements such as type, handwritten characters, handwritten drawings, free thin dots, tables, illustrations, graphics, flat nets, and photographs are obtained. Compressed or decompressed with one algorithm.

  However, with the known image data compression and restoration methods, it is difficult to suppress degradation of image quality due to image data compression for all image elements included in the image data. For example, if an image data generated from characters and lines is compressed / restored using an algorithm that does not cause deterioration in image quality when image data generated from photographs is compressed / restored, the edges of the characters and lines are It is not restored neatly. Conversely, when image data generated from characters and lines is compressed / restored using an algorithm that does not easily degrade image quality, the image of the photo tends to be corrupted when compressed / restored. It is in.

  In the image data compression method and decompression method, it is desirable to suppress degradation of image quality due to compression of image data.

  Furthermore, in the known compression method and restoration method of image data, it is possible to improve both the compression rate and suppress deterioration of image data due to compression of image data for all image elements. Have difficulty. This algorithm is effective for image data generated from photographs. When image data generated from image elements such as type, handwritten characters, handwritten drawings, tables, and illustrations is compressed and restored, the edges of the image elements are restored. Is done. Furthermore, the restored image is less focused. On the other hand, when processing is performed using a technique effective for line drawing or the like, the image quality of graphics, flat screens, photographs, etc. deteriorates. Further, the amount of compressed data increases.

  In the image data compression method and decompression method, it is desirable that the compression rate is large and that image quality deterioration due to image data compression is suppressed.

  In general, image data generated from an image drawn on a printed material is compressed and then restored. As shown in FIG. 41, the image drawn on the color printed material is composed of pixels 501. Each of the pixels 501 includes a blue halftone dot 502a, a red halftone dot 502b, a yellow halftone dot 502c, and a black halftone dot 502d. The blue plate halftone dot 502a is a halftone dot (Dot) of the blue plate (C plate). The red plate halftone dot 502b is a red plate (M plate) halftone dot. The yellow plate halftone dot 502c is a halftone dot of a yellow plate (Y plate). A black halftone dot 502d is a black halftone dot (K version). The arrangement of the blue halftone dot 502a, the red halftone dot 502b, the yellow halftone dot 502c, and the black halftone dot 502d is not limited to that shown in FIG. The blue halftone dot 502a, the red halftone dot 502b, the yellow halftone dot 502c, and the black halftone dot 502d are collectively referred to as a halftone dot 502. The halftone dots 502 may be square as shown in FIG. 42 (a), and may be other shapes, such as circular, as shown in FIG. 42 (b). There is.

As shown in FIG. 43, the halftone dots 502 included in one plate are regularly arranged on the screen lines 503 in accordance with the printing rules. The screen line 503 and the X axis intersect at an angle determined by the printing rule. The angle is different for each version. The screen lines 503 are arranged in parallel to each other and at equal intervals. Here, if the interval between the screen lines 503 is d _s , 1 / d _s is called the screen line density. The screen line density is the number of screen lines 503 that intersect with a line length of a unit length in a direction perpendicular to the screen line 503, typically 1 inch.

  The halftone dot 502 is arranged so that its center point is on the screen line 503. Here, the center point of the halftone dot 502 is a point where the diagonal lines intersect when the halftone dot 502 is a square. When the halftone dot 502 is a circle, the center point of the halftone dot 502 is the center of the circle.

  The area of each halftone dot 502 indicates a gradation. As the area of the halftone dot 502 is larger, the human eye recognizes that the density at a certain position of the halftone dot 502 is higher.

  An image composed of halftone dots having the arrangement and shape as described above is inherently highly redundant.

  However, the conventional image data compression method and decompression method do not utilize the fact that the image drawn on the printed material is composed of halftone dots. In the conventional image data compression method and decompression method, an image drawn on a printed material is not effectively compressed.

  It is desirable to provide a method for effectively compressing and decompressing image data generated from an image composed of halftone dots.

  Further, in the conventional image data compression method and decompression method, halftone dots are compressed and decompressed without being distinguished from other image elements included in the image. The halftone dot itself is not restored. At this time, if the restored image data is enlarged or reduced, the area ratio of halftone dots relative to the entire image, that is, the halftone dot percentage is not saved. For this reason, when the restored image data is enlarged or reduced, the color may deteriorate. Furthermore, when the restored image data is enlarged or reduced, moire may occur.

  When the image data generated from the image composed of halftone dots is compressed and restored, the image quality will not deteriorate even if operations such as enlargement or reduction are performed on the restored image data. It is desirable not to occur.

  In the image data compression method, it is desirable that the image data is compressed at high speed. In particular, it is desirable that compression of image data indicating an image with emphasized edges be performed at high speed.

  Also, in the image data compression method, image data that is effectively compressed and restored from image data generated from a printed material that has a small area and does not have an arrangement defined in the printing rule. It is desirable to provide a compression method and a decompression method.

  An object of the present invention is to provide a compression method and a decompression method for image data in which deterioration of image quality due to compression and decompression is suppressed.

  Another object of the present invention is to provide a method for compressing and restoring image data having a high compression rate.

  Still another object of the present invention is to provide a compression method and a decompression method of image data in which a compression ratio is large and image quality deterioration due to compression and decompression is suppressed.

  Still another object of the present invention is to provide a compression method and a restoration method for image data that effectively compresses and restores image data generated from printed matter composed of halftone dots.

  Still another object of the present invention is to provide a method for compressing image data in which the image data is compressed at high speed.

  It is still another object of the present invention to provide a method for compressing image data in which compression of image data indicating an image with emphasized edges is performed at high speed.

  Also, image data compression method and image restoration method that effectively compresses and restores image data generated from a printed material that has a small area and does not have an arrangement defined in a printing rule. Is to provide.

  Means for solving the problem is expressed as follows. Technical matters appearing in the expression are appended with numbers, symbols, etc. in parentheses. The numbers, symbols, and the like are technical matters constituting at least one of a plurality of embodiments of the present invention, in particular, technical matters expressed in the drawings corresponding to the embodiments. This corresponds to the reference number, reference symbol and the like attached to. Such reference numbers and reference symbols clarify the correspondence and bridging between the technical matters described in the claims and the technical matters of the embodiments. Such correspondence or bridging does not mean that the technical matters described in the claims are interpreted as being limited to the technical matters of the embodiments.

  The image data compression method according to the present invention extracts the image elements (31 to 41) included in the digital image (30) read from the paper surface, and uses a compression method according to the type of the image elements (31 to 41). Each extracted image element is data-compressed, and each compressed image element data (54 to 56) is stored in the storage device (3).

  Each image element (31 to 41) has a characteristic. From the feature, each image element (31 to 41) can be separated and extracted. The image element data (51 to 53) is compressed and restored by an algorithm corresponding to the type of the extracted image element (31 to 41), thereby suppressing deterioration in image quality due to compression and restoration. In addition, the compression rate is improved.

  For example, an image whose edges are to be restored beautifully is subjected to compression / decompression processing effective for the edges. An effective compression / decompression process is performed on a halftone dot image for an image or the like that neatly restores a printed image such as a graphic, flat screen, or photograph. Aggregation of free fine dots in order to restore fine and finely arranged aggregates of fine fine dots (hereinafter sometimes referred to as "free fine dots") without regularity. Effective compression / decompression processing is performed.

  As a method for determining the type of each image element, the following determination method can be used.

  In the first determination method, the type of each image element is determined by the following process. An image element composed of a collection of free thin dots is determined from the fact that the area is larger than the printing halftone dot and smaller than the predetermined area, and there is no regularity of the printing halftone dot. The printed image is a collection of fine dots with regular printing halftone dots. The print image is discriminated from the presence of the regularity of the print halftone dots. All the remaining image elements are determined to be line drawing images.

  In the second discrimination method, the type of each image element is discriminated from the difference in typesetting elements. Type characters have character features. Handwritten characters do not have character features. In addition, stamps, seals, and line drawings have the characteristics of a collection of free lines, that is, there are no character faces and no print halftone dots. A flat screen has the characteristics that regularity of printing halftone dots exists and gradation does not exist. A gradation halftone dot has regularity of printing halftone dots and has a feature that gradation exists in a halftone dot row. Photographic nets have the characteristic that regularity of printing halftone dots exists, but regularity of flat and gray scales does not exist. From these features, the type of each image element is determined.

  In the third determination method, the type of each image element is determined from the difference in display elements. That is, the text has a feature that character strings are continuously arranged. Manga is characterized by the presence of illustrations, free fine lines and fine dots. Further, the map object has a feature that the regularity of the map exists. The advertisement has a feature that there is an advertisement frame and that there is regularity in the arrangement on the paper. The surface material has a feature that it has a quadrangle composed of ruled lines. A photograph has a feature that regularity of printing halftone dots exists but regularity of flat halftone and gradation halftone does not exist. From these features, the type of each image element is determined.

  In the image data compression method, each compressed image element data is added with position information and line density information when the image element corresponding to each image element data exists in the paper. desirable.

  In the image data compression method, the digital image read from the paper surface may be a color image. In this case, image element extraction and image element data compression are preferably performed for each color component.

  According to the image data restoration method of the present invention, each image element data read and compressed from the paper surface is restored using a restoration method according to the type of the image element, and the restored image elements are superimposed and combined. The paper image is restored.

  At this time, using the position information and the line density information added to each compressed image element data, an editing process for rotating, deforming, enlarging or reducing the image element is performed to restore the paper image. Is possible.

  Each compressed image element data may be data for each color component. In this case, the image element data for each color component is restored using a restoration method corresponding to the type of the image element, and the restored image elements for each color component are superimposed and combined to restore the image. Is desirable.

An image data compression method according to the present invention includes:
Acquiring image data (50) indicating the image (30) (S01);
Extracting the first image element data (51) from the image data (50) (S02);
Extracting the second image element data (52) from the image data (50) (S02);
Compressing the first image element data (51) to generate first compressed image element data (54) (S03);
The second image element data (54) is compressed to generate second compressed image element data (55) (S04).
(See FIG. 1). At this time, the first extraction algorithm for extracting the first image element data (54) is different from the second extraction algorithm for extracting the second image element data (54). Furthermore, the first compression algorithm for generating the first compressed image element data (54) is different from the second compression algorithm for extracting the second image element data (55).

  The first image element data and the second image element data extracted by the first extraction algorithm and the second extraction algorithm which are different from each other have different characteristics. The first image element data and the second image element data having different characteristics are respectively compressed by a first compression algorithm and a second compression algorithm which are different from each other. Thereby, deterioration of the image quality due to compression and decompression is suppressed. In addition, the compression rate is improved.

  It should be noted that other image element data other than the first image element data (51) and the second image element data (52) can be extracted from the image data (50) by other extraction algorithms. In this case, other image element data is compressed by another compression algorithm to generate other compressed image element data.

In the image data compression method, acquiring the image data (63a to 63d) (S41, S42)
Obtaining color image data (62) indicating a color image (S41);
Extracting a portion indicating a predetermined color component from the color image data (62) to generate the image data (63a to 63d) (S42).
(See FIG. 32). This provides a method for compressing and decompressing the color image data (62) in which the deterioration of the image quality is suppressed. In addition, a method for compressing and decompressing color image data (62) with improved compression rate is provided.

  Further, in the image data compression method, extracting the first image element data (51) (S02) generates the first image element data (55) by extracting the first part from the image data (50). It is desirable to include (S02). This first portion corresponds to a halftone dot portion (33, 36) constituted by a halftone dot (81) in the image (30).

  At this time, generating the first compressed image element data (55) (S04) includes generating the first compressed image element data (55) based on the area of the halftone dot (81) (S04). It is desirable.

  In the image data compression method, extracting the second image element data (51) is extracting the second portion from the image data (50) to generate the second image element data (54) ( S02) is desirable. The second portion of the image (30) corresponds to a free fine dot region that includes not a halftone dot (81) and a free fine dot having an area equal to or smaller than a predetermined area.

Also, generating the second compressed image element data (54)
Dividing the free fine dot region (70) into a plurality of rectangular regions (71);
Recognizing the shape of the pattern (73) in each of the rectangular regions among the image patterns (31 to 39) of the image;
Preferably, the method includes encoding the shape to generate the second compressed image element data (54) (see FIG. 7).

The free fine dots may include a first free fine dot (141 ₁ ) and a second free fine dot (141 ₂ ) (see FIG. 37). At this time, generating the second compressed image element data (54) (S03) is based on the relative positions of the first free fine dot (141 ₁ ) and the second free fine dot (141 ₂ ). Generating image element data (54) (see FIG. 37).

Also, generating the second compressed image element data (54)
Defining a rectangular region (211) including the free fine dot (212) in the free fine dot region (210);
It is desirable to include generating the second compressed image element data data (54) based on the average value of the density inside the rectangular area (211) (see FIG. 45).

  In the image data compression method, the third image element data that is not included in the first image element data (51) or the second image element data (52) of the image data (50) is further included. It is desirable to provide extraction (S02).

  The image data compression method further includes generating batch compressed image element data (57) based on the first compressed image element data (55) and the second compressed image element data (54). desirable.

In the image data compression method, generating the first compressed image element data (S05)
Detecting the gradation of the image element (110) indicated by the first image element data (53) while scanning along the scanning line (111);
Calculating a contour position of a contour (112) of the image element (110) based on the gradation;
Generating first compressed image element data (56) based on the boundary position.

The image data compression method according to the present invention acquires image data (52) indicating an image including a halftone dot (101) (S01, S02);
Calculating the area of the dot (101);
Calculating the position of the halftone dot (101);
Generating compressed data (55) based on the area and the position.

In the image data compression method,
The dot (101) is
A first halftone dot (101 ₀ );
Including second halftone dots (101 ¹ _{1 to} 101 ¹ _n ),
The area is
A first area (S ₀ ) of the first halftone dot;
Second area of the second halftone dot (S ₁ -S _n )
Including
Said compressed data (55), said first area (S ₀₎ and the second area (S ₁ to S _n) differential area desired to be generated based on the.

In the image data compression method,
The position is
A first position of the first halftone dot (101 ₀ );
A second position of the second halftone dot (101 ¹ _{1 to} 101 ¹ _n ),
The compressed data (55) is an image data compression method generated based on a distance between the first position and the second position.

In the image data compression method,
Obtaining image data (152) indicating an image including a halftone dot is
Acquiring other image data (150) indicating other images;
Generating halftone dots based on the gradation of the other image and generating image data (152).

The image data compression method of the present invention includes:
Obtaining image data (53) indicating images (31, 32, 34, 35, 37, 39, 41) (S01, S02);
Detecting the gradation of the image (31, 32, 34, 35, 37, 39, 41) while scanning along the scanning line (111);
Calculating a contour position of the contour (112) of the image based on the gradation;
Generating compressed data (56) based on the contour position.

The image data compression method according to the present invention acquires image data indicating an image (70, 210) including free fine dots (73, 141 _{1 to} 141 ₄ , 212) having an area in a predetermined area range (S02). )When,
Based on the position of the free thin dots (73, 141 _{1 to} 141 ₄ , 212), compressed data (54) is generated (S03).
And.

At this time, the free fine dots (141 _{1 to} 141 ₄ ) include a first free fine dot (141 ₁ ) and a second free fine dot (141 ₂ ), and further generate compressed data (54). (S03) preferably includes generating the compressed data based on the relative position between the first free fine dot (141 ₁ ) and the second free fine dot (141 ₂ ) (see FIG. 37).

Further, generating the compressed data (54) (S03) includes defining a rectangular area (211) including the free fine dots (212) in the image (210);
Generating the compressed data (54) based on the average value of the density inside the rectangular area (211) (S03)
(See FIG. 45).

In addition, based on defining a rectangular area (211) including the free fine dots (212) in the image (210) and a distance between a side of the rectangular area (211) and the free fine dots (212), Generate compressed data (54) (S03)
It is desirable to include.

Further, generating the compressed data (54) includes defining a rectangular area (71) in the image (70),
Recognizing the shape of the pattern of the portion included in the rectangular area (70) of the free fine dots (73);
Preferably, the method includes encoding the shape to generate compressed data (54).

The image data extraction method of the present invention obtains image data (50) indicating an image (30) including a halftone dot (81);
Extracting a portion (55) indicating a halftone dot (81) from the image data (50).

At this time, the extracting includes scanning the image (200) to detect change positions (203a to 203c) at which gradation changes,
It is desirable to include extracting the portion (55) based on the interval between the change positions (203a to 203c) (see FIG. 44).

The image data processing method according to the present invention obtains image data (59) indicating an image including a first halftone dot (131, 235) and a second halftone dot (132, 232) having an arrangement according to a printing rule. (Step S23),
By moving the second halftone dot (132, 232) to define the virtual halftone dot (132 ′, 232 ′), the first halftone dot (131, 231 ′) and the virtual halftone dot (132 ′, 232 ′) Generating a third halftone dot (132 ″, 232 ″) located between;
Erasing virtual halftone dots (132 ′, 232 ′). Here, the virtual halftone dot positions of the virtual halftone dots (132 ′, 232 ′) are on a straight line passing through the first halftone dots (131, 235) and the second halftone dots (132, 232). Further, the virtual halftone dot (132 ′, 232 ′) is in the first direction from the first halftone dot (131, 235) to the second halftone dot (132, 232) with respect to the second halftone dot (132, 232). It is in. The virtual halftone dot area of the virtual halftone dots (132 ′, 232 ′) is the same as the second halftone dot area of the second halftone dot. The third halftone dot (132 ″, 232 ″) is on a straight line passing through the first halftone dot (131, 235) and the second halftone dot (132, 232). The third halftone dot position of the third halftone dot (132 ″) is determined in accordance with the printing rule. The third halftone dot area of the third halftone dot (132 ″, 232 ″) is the virtual halftone dot position of the virtual halftone dot (132 ′, 232 ′) and the halftone dot of the first halftone dot (131, 235). The position, the third halftone dot position of the third halftone dot (132 ″, 232 ″), the first halftone dot area of the first halftone dot (131, 235), and the virtual halftone dot (132 ′, 232 ′). ) And the virtual halftone dot area (see FIGS. 33 and 34).

The image data restoration method of the present invention obtains compressed data (57), wherein the compressed data (57)
First compressed image element data (54) compressed by a first compression algorithm and second compressed image element data (55) compressed by a second algorithm different from the first compression algorithm
Including
Decompressing the first compressed image element data (54) to generate first decompressed image element data (58);
Decompressing the second compressed image element data (55) to generate second decompressed image element data (59);
Generating restored image data (61) indicating one image from the first restored image element data (58) and the second restored image element data (59) (see FIG. 28).

The image data restoration method of the present invention includes:
1st dot (122) and area difference data indicating the area difference between the second dot (123 ¹⁾ and ([Delta] S ^1), the distance of the first dot (122) and the second dot (123 ¹⁾ Obtaining compressed data (55) including distance data indicating (x ¹ ) (S21);
Based on the area difference data and the distance data, the image data (59) is restored so as to include the first halftone dot (122) and the second halftone dot (123 ¹ ) (S23). With.

In the image data restoration method, the image data (59) further includes a third halftone dot (124 ¹ ) located between the first halftone dot (122) and the second halftone dot (123 ¹ ). Is restored and
The area of the third halftone dot (124 ¹ ) is preferably determined based on the area difference data.

The image data restoration method of the present invention includes:
Acquiring compressed data (54) including position data indicating the position of a free fine dot (212) having an area in a predetermined area range, and an image (210) comprising free fine dots (212) based on the position ) Is restored.

At this time, the compressed data (54) includes the average value of the density inside the rectangular area (211) defined in the image (210),
Restoring the image data (58)
It is desirable to include restoring the image data (58) based on the average value.

The position data includes a distance between the side (213) of the rectangular area (211) defined in the image (210) and the free thin point (212),
Restoring the image data (58)
Preferably, the method includes restoring the image data (58) based on the distance.

  According to the present invention, there are provided a compression method and a decompression method of image data in which deterioration of image quality due to compression / decompression is suppressed.

  The present invention also provides a method for compressing and restoring image data with a high compression rate.

  In addition, according to the present invention, there are provided a compression method and a decompression method for image data that have a large compression rate and suppress deterioration in image quality due to compression of image data.

  In addition, according to the present invention, there are provided an image data compression method and decompression method for effectively compressing and restoring image data generated from a printed matter composed of halftone dots.

  In addition, according to the present invention, there is provided a method for compressing image data in which image data is compressed at high speed.

  In addition, according to the present invention, there is provided a method for compressing image data in which image data indicating an image with emphasized edges is compressed at high speed.

  Further, according to the present invention, image data generated from a printed matter that is composed of fine dots having a small area, which does not have an arrangement defined in the printing rule, can be effectively compressed and restored. A method and a restoration method are provided.

FIG. 1 is a flowchart showing an image data compression method according to the first embodiment of the present invention. FIG. 2 shows a hardware resource 10 on which the image data compression method and decompression method of the first embodiment are executed. FIG. 3 shows the image 30 to be compressed. FIG. 4 shows image elements included in the free fine dot image element data 51. FIG. 5 shows image elements included in the print halftone dot image element data 52. FIG. 6 shows image elements included in the line drawing image element data 53. FIG. 7 is a diagram for explaining a free fine dot pattern compression algorithm. FIG. 8 is a diagram showing various patterns that the area patch 71 has. FIG. 9 shows a part of an image included in the print halftone dot image element data 52. FIG. 10 is a flowchart showing a printing dot pattern compression algorithm. FIG. 11 is a diagram illustrating a first method for calculating the area of halftone dots and a method for determining the center point of halftone dots. FIG. 12 is a diagram illustrating a second method for calculating the area of halftone dots. FIG. 13 is a diagram illustrating a first method of extracting screen lines. FIG. 14 is a diagram illustrating a second method of extracting screen lines. Figure 15 is a diagram showing an arrangement of halftone dots 81 _{1-81 4} can take. FIG. 16 is a diagram illustrating a third method of extracting screen lines. FIG. 17 is a diagram illustrating a method of calculating the screen line angle. FIG. 18 is a diagram illustrating a method of calculating the screen line density. FIG. 19 is a diagram illustrating a method for calculating a halftone dot vector. Figure 20, in a virtual coordinate system Q _1, is a diagram illustrating the dot 101 _0, the position of the dot 101 ¹ ₁ to 101 ¹ _n are arranged. FIG. 21 shows an image compressed by the line drawing compression algorithm. FIG. 22 shows a method for detecting the edge 112. FIG. 23 shows the edge 112. FIG. 24 shows a noise detection method. Figure 25 shows the outline vector 115 _{1-115 8.} FIG. 26 shows a contour smoothing process. FIG. 27 shows the process of contour smoothing. FIG. 28 is a flowchart illustrating the image data restoration method according to the first embodiment of this invention. FIG. 29 is a flowchart showing a printing dot restoration algorithm. FIG. 30 is a flowchart showing a process of restoring halftone dots. FIG. 31 is a flowchart showing a line drawing restoration algorithm. FIG. 32 is a flowchart showing a process of compressing color paper image data representing a color image. FIG. 33 shows a process in which the restored image is enlarged simultaneously with the restoration when the halftone dot compression data module is restored. FIG. 34 shows a process in which when the print dot compression data module 55 is restored, an image composed of print dots is reduced simultaneously with the restoration. FIG. 35 shows a process in which, when the line drawing compressed data module 56 is restored, the restored image is reduced simultaneously with the restoration. FIG. 36 shows a process in which, when the line drawing compressed data module 56 is restored, the restored image is enlarged simultaneously with the restoration. FIG. 37 shows the free fine dot vector compression algorithm. FIG. 38 shows a hardware resource 10 'that executes the image data compression method according to the second embodiment. FIG. 39 is a flowchart illustrating an image data compression method according to the second embodiment. FIG. 40 is a flowchart illustrating an image data restoration method according to the second embodiment. FIG. 41 shows the structure of the pixel 501. FIG. 42 shows the structure of the halftone dot 502. FIG. 43 shows an image composed of halftone dots. FIG. 44 shows a method for extracting a collection of halftone dots. FIG. 45 is a diagram for explaining a free fine dot data compression algorithm.

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

(First embodiment)
The image data compression method and restoration method according to the first embodiment is a method for compressing and further restoring image data generated by capturing an image drawn on a paper surface with a scanner.

  The image data compression method and decompression method according to the first embodiment are executed using hardware resources. As shown in FIG. 2, the hardware resource 10 includes a scanner 1, a CPU 2, a storage device 3, a recording medium 4, and a bus 5. The scanner 1, CPU 2, storage device 3, and recording medium 4 are connected to a bus 5. The scanner 1 takes in an image 30 drawn on a paper surface and generates paper image data 50. The CPU 2 executes a calculation for compressing or restoring the paper surface image data 50. The storage device 3 stores the paper image data 50 and data generated in the course of executing the image data compression method and decompression method of the first embodiment. The recording medium 4 stores a program in which procedures included in the image data compression method and decompression method according to the first embodiment are described. The CPU 2 operates according to the program. The bus 5 transmits data exchanged among the scanner 1, the CPU 2, the storage device 3, and the recording medium 4.

  In the image data compression method and decompression method according to the first embodiment, first, as shown in FIG. 1, an image 30 drawn on a paper surface is captured by the scanner 1 to generate paper image data 50. (Step S01).

  The image 30 captured by the scanner 1 is a monochrome image. As shown in FIG. 3, the image 30 is composed of a heading 31, a body 32, a photograph 33, a table 34, an illustration 35, a graphic 36, an advertisement character 37, a comic 38, and a photo heading 39 arranged at random. Has been. The headline 31, the body 32, and the advertisement character 37 are characters printed by type. The photograph 33 and the graphic 36 are constituted by a halftone dot group having an arrangement defined in the printing rule.

  Elements that make up the image 30 may be referred to as image elements in the following. The headline 31, the body 32, the photograph 33, the table 34, the illustration 35, the graphic 36, the advertisement character 37, the comic 38, and the photograph headline 39 constitute an image element. Furthermore, the heading 31, the body 32, the photograph 33, the table 34, the illustration 35, the graphic 36, the advertising character 37, and a part of the comic 38 may constitute the image element.

  Subsequently, the image elements of the image 30 indicated by the paper surface image data 50 are extracted and further classified (step S02).

  A portion corresponding to the fine dots arranged without following the printing rule is extracted from the paper image data 50, and free fine dot image element data 51 is generated. The fine dots arranged without following the printing rules are hereinafter referred to as free fine dots. A region that is arranged not in accordance with the printing rule, is smaller than a predetermined area, and larger than the area of the printing halftone dot is extracted as a free fine dot.

  FIG. 4 shows the contents of the free fine dot image element data 51. As shown in FIG. 4, the free fine dot image element data 51 is composed of data indicating an image element 40 that is a part of the comic 38. That is, a portion corresponding to the image element 40 in the paper surface image data 50 is extracted as the free fine dot image element data 51.

  Position information indicating the position of the image element 40 included in the free fine dot image element data 51 is added.

  Further, a portion corresponding to the halftone dot group included in the image 30 is extracted from the paper surface image data 50, and print halftone dot image element data 52 is generated (step S04). The dot group has an arrangement defined in the printing rule. A halftone dot group is extracted using the fact that the halftone dot group has an arrangement defined in the printing rule, and print halftone dot image element data 52 is generated.

  First, an aggregate composed of points having an area smaller than the maximum area of halftone dots defined in the printing rule is extracted from the paper surface image data 50. Further, it is determined whether or not the aggregate is an aggregate of printing halftone dots. FIG. 44 shows the aggregate 200 extracted from the paper surface image data 50. The aggregate 200 is composed of points 201.

  The assembly 200 is scanned along a scanning line 202 extending in the x-axis direction. The edge of the point 201 is detected from the change in gradation. It is assumed that an edge 203a of a certain point 201a is detected as a result of scanning along the scanning line 202. Further, it is assumed that the aggregate 200 is scanned along the scanning line 202, and the edges 203b and 203c at the left ends of the other points 201b and 201c are sequentially detected. Furthermore, at this time, if the first interval between the edges 203a and 203b and the second interval between the edges 203b and 203c are predetermined unit intervals, the points 201a, 201b, and 201c are halftone dots. To be judged. Similarly, it is determined whether or not the other point 201 is a halftone dot. If it is determined that almost all of the points 201 included in the aggregate 200 are halftone dots, the aggregate 200 is determined to be an aggregate of halftone dots.

The unit interval is determined by the density of the screen lines 203 defined in the printing rule and the angle that the scanning lines 202 and the screen lines 203 can take. If the points 201 included in the aggregate 200 are halftone dots, they should be arranged side by side on the screen line 203. At this time, the angle formed by the scanning line 202 extending in the x-axis direction and the screen line 203 is determined to be 0 °, 15 °, 30 °, 45 °, 60 °, 75 °, or 90 ° according to the printing rule. . Further, the distance d _s between the screen lines 203 is determined by the printing rule. Six unit intervals d _norm ^{1 to} d _norm ⁶ are determined corresponding to each of six angles other than 0 ° among the angles that the scan line 202 and the screen line 203 can form.
d _norm ⁱ = d _s cos θ _s ⁱ ,
However, θ _s ¹ = 15 °,
θ _s ² = 30 °,
θ _s ³ = 45 °,
θ _s ⁴ = 60 °,
θ _s ⁵ = 75 °,
θ _s ⁶ = 90 °.
The interval between any one of the points 201 included in the aggregate 200 and the edge of another point adjacent thereto is approximately equal to one unit interval among the ^six unit intervals d _norm ^{1 to} d _norm ^6. In this case, the aggregate 200 is determined to be an aggregate of halftone dots.

  When the angle formed by the scanning line 202 and the screen line 203 is 0 °, it cannot be determined by this method whether or not a certain aggregate 200 is an aggregate of halftone dots. However, it is possible to determine whether or not the aggregate 200 is an aggregate of halftone dots by changing the direction of the scanning line 202.

  A set 200 determined to be a set of halftone dots is extracted, and print dot image element data 52 is generated.

  Note that the direction of the scanning line is not limited to the x-axis direction. Of course, the direction of the scanning line may be another direction.

  FIG. 5 shows the contents of the print dot image element data 52. As shown in FIG. 5, the print halftone dot image element data 52 is composed of data indicating a photograph 33 and a graphic 36. That is, a portion corresponding to the photograph 33 and the graphic 36 in the paper surface image data 50 is extracted as the print halftone dot image element data 52.

  The print dot image element data 52 is added with position information indicating the positions of the photograph 33 and the graphic 36 included therein.

  Further, a portion of the paper image data 50 that has not been extracted as the free fine dot image element data 51 or the print halftone dot image element data 52 is extracted as the line drawing image element data 53 (step S05).

  FIG. 6 shows the contents of the line drawing image element data 53. As shown in FIG. 6, the line drawing image element data 53 includes a headline 31, a body 32, a table 34, an illustration 35, an advertisement character 37, an image element 40, and an image element 41 that is a part of the comic 38. It consists of the data shown. Of the image 30, a portion corresponding to a portion with a poor contrast change and a clear edge is stored in the line drawing image element data 53.

  As shown in FIG. 1, the aforementioned free fine dot image element data 51 is compressed by a free fine dot pattern compression algorithm to generate a free fine dot compressed data module 54 (step S03). In the free fine dot pattern compression algorithm, the area to be compressed is divided into area patches. Further, the pattern included in each area patch is encoded, and a free fine dot compressed data module 54 is generated.

  In the following, the free fine dot pattern compression algorithm will be described in detail.

  As shown in FIG. 7, the target area 70 to be compressed is divided into area patches 71. Each of the area patches 71 is composed of 16 small regions 72 that are four vertically and four horizontally. The number of small regions 72 included in the area patch 71 is not limited to 16 in the vertical direction and 4 in the horizontal direction. For example, each of the area patches 71 may be composed of 16 small regions 72 of 8 vertically and 8 horizontally.

  Furthermore, the pattern which each area patch 71 has is recognized. The pattern is recognized based on whether or not the image element 73 exists in each of the small regions 72 included in the area patch 71.

  FIG. 8 shows examples of various patterns that the area patch 71 has. FIG. 8A shows an area patch 71 having a zero pattern. The area patch 71 has no image element 73. FIG. 8B shows an area patch 71 having a lower right pattern. The lower right pattern is a pattern in which an image element 73 exists in four small regions 72 located at the lower right of the area patch 71. FIG. 8C shows an area patch 71 having a medium pattern. The middle pattern is a pattern in which the image element 73 exists in the four small regions 72 located at the center of the area patch 71. FIG. 8D shows an area patch 71 having an upper right pattern. The upper right pattern is a pattern in which an image element 73 exists in two small regions 72 located at the upper right of the area patch 71. FIG. 8E shows an area patch 71 having one right pattern. The right one pattern is a pattern in which the image element 73 exists in the small region 72 in the second row from the bottom of the area patch 71 and in the first column from the right. FIG. 8F shows an area patch 71 having one pattern on the right. The right one pattern is a pattern in which the image element 73 exists in the small area 72 in the second row from the bottom and the first column from the left.

  In the free fine dot pattern compression algorithm, codes different from each other are determined in advance corresponding to the various patterns of the area patch 71. Different codes are defined corresponding to the patterns shown in FIGS. 8A to 8F.

  A pattern included in the area patch 71 is encoded using a predetermined code. The encoded pattern is compressed to complete the free fine dot pattern compression algorithm.

  The free fine dot image element data 51 is compressed by the above-described free fine dot pattern compression algorithm, and a free fine dot compressed data module 54 is generated.

  On the other hand, as shown in FIG. 1, the print halftone image element data 52 is compressed by a print halftone compression algorithm to generate a print halftone compression data module 55 (step S04). In the printing halftone compression algorithm, the direction of the screen lines in which the halftone dots are arranged and the line density of the screen lines per unit length are calculated. Further, a halftone dot vector whose components are the relative position of the center point of the halftone dots included in the image and the area difference is calculated. Furthermore, the halftone dot vector is encoded. The print halftone compression data module 55 includes data indicating the encoded halftone vector, the direction of the screen lines, and the line density of the screen lines per unit length.

  In the print halftone compression algorithm, an image included in the print halftone image element data 52 is composed of halftone dots, and a high redundancy is used. Thereby, the printing dot image element data 52 is effectively compressed.

  In the following, the printing dot pattern compression algorithm will be described in detail.

  As described above, the print halftone image element data 52 is composed of data indicating an image composed of halftone dots. FIG. 9 shows a part of an image included in the print halftone dot image element data 52. The halftone dots 81 included in the print halftone image element data 52 are arranged in an arrangement determined by the printing rule. The halftone dot 81 is disposed on the screen line 82.

  FIG. 10 is a flowchart showing a printing dot pattern compression algorithm. In the printing dot pattern compression algorithm, first, as shown in FIG. 10, the area of each halftone dot 81 and the position of the center point included in the printing dot image element data 52 are calculated (step S11). ).

  The halftone dot 81 may have a broken shape. This is because the print dot image element data 52 is generated from the image 30 printed on the paper. The halftone dot 81 is printed with the intention of becoming a square when the image 30 is printed on the paper. However, in the process of printing the image 30 on the paper, the halftone dot shape collapses due to factors such as ink bleeding. The print halftone dot image element data 52 generated from the image 30 printed on the paper is composed of data indicating a halftone dot 81 whose shape has collapsed.

  The area of each halftone dot 81 whose shape has collapsed is calculated by one of the two methods described below.

  In the first method of calculating the area, first, as shown in FIG. 11, the outline of the halftone dot 81 shown in the print halftone dot image element data 52 is extracted. On the contour of the extracted halftone dot 81, inflection points are sequentially determined counterclockwise or clockwise. The inflection point is a point at which the direction in which the contour of the halftone dot 81 extends changes. Inflection points a to k are sequentially determined.

  Further, a vector connecting two adjacent inflection points is determined. Vectors 83a-83k are defined. The vectors 83 a to 83 k go around the outline of the halftone dot 81. The sum of the vectors 83a to 83k is a zero vector.

  Subsequently, a regular rectangle 84 that circumscribes a polygon having the inflection points a to k as apexes and has a minimum length of one side is determined. Here, it is assumed that the four vertices of the regular square 84 are a vertex A, a vertex B, a vertex C, and a vertex D. The area of the halftone dot 81 is obtained by subtracting the area of the part inside the regular square 84 and outside the polygon having the inflection points a to k as vertices from the area of the regular square 84. That is, it is obtained by subtracting the areas of the polygon Acbak, the triangle Bdc, the triangle eCg, the triangle hDi, and the triangle ijk from the area of the regular square 84.

  In the second method for calculating the area, first, as shown in FIG. 12, the scanning line 85 is determined. The scanning line 85 is defined so as to extend in the X-axis direction. The scanning line 85 may be defined to extend in another direction, for example, the Y-axis direction. The scanning lines 85 are arranged in parallel to each other and at equal intervals. A halftone dot 81 is scanned along the scanning line 85. A boundary 86 of the halftone dot 81 is detected from the change in gradation. The area inside the boundary 86 is the area of the halftone dot 81.

  In any of the first method and the second method described above, the area of the halftone dot 81 having an arbitrary shape is calculated.

Further, the position of the center point of the halftone dot 81 is calculated as follows. First, as shown in FIG. 11, a regular square 84 circumscribing the halftone dot 81 and having the shortest one side is defined. The position of the center point of the halftone dot 81 is determined to be the intersection O of the diagonal lines AC and BD of the regular rectangle 84. At this time,
AO = BO = CO = DO,
Is established.

  The position of a halftone dot is defined as the position of the center point of that halftone dot. Hereinafter, when the halftone dot position is described at the end, the halftone dot position means the position of the center point of the halftone dot. The distance between two halftone dots means the distance between the center point of one halftone dot and the center point of another halftone dot.

  Further, as shown in FIG. 10, screen lines are extracted (step S12). Screen lines are extracted using any of the three methods described below.

  In the first method of extracting screen lines, first, among the halftone dots 81, those having an area larger than a predetermined area are extracted. In the following, among the halftone dots 81, those having an area larger than a predetermined area are referred to as screen line extraction halftone dots. FIG. 13 shows the arrangement of the center points 97 of the screen line extraction halftone dots. The center points 97 of the screen line extraction halftone dots are generally arranged in a certain direction. A straight line extending in that direction and passing through the center point 97 of the screen line extraction halftone dot is recognized as the screen line 98. For the identification of the screen line 98, a least square method is used as necessary.

In the second method of extracting screen lines, first, four halftone dots are extracted from the halftone dots 81 as shown in FIG. At this time, the four halftone dots are extracted so that the center point of the halftone dots to be extracted is substantially a vertex of a square. The extracted halftone dots 81 are hereinafter referred to as halftone dots 81 _{1 to} 81 ₄ .

The plurality of straight lines 88 and the plurality of straight lines 89 shown in FIG. 14 are recognized as screen line candidates. Here, the straight line 88, the four center points of the dot 81 _{1-81 4} extended to the side 87 ₁ of the same direction of the square 87 to the apex, and the center point of the dot 81 _{1-81 4} A straight line passing through. On the other hand, the straight line 89, then extended diagonally 87 ₂ in the direction of the square 87, and a straight line 89 passing through the center point of the dot 81 _{1-81 4} is recognized as a candidate for the screen line.

Both the straight line 88 and the line 89, can become candidates for the screen line, dot 81 _{1-81 4} is because having one of two arrangements described below. As shown in FIG. 15 (a), halftone dot 81 _{1-81 4,} two for two screen lines 90 and 91 which may be located.

Further, as shown in FIG. 15 (b), on the screen line 92, there is one of the dot 81 _{1-81 4,} on the screen line 93, dot 81 _{1-81 4} In addition, there may be the remaining two of the halftone dots 81 _{1 to} 81 ₄ on the screen line 94 between the screen lines 92 and 93.

Even four of halftone dot 81 _{1-81 4} are extracted, the dot 81 _{1-81 4,} or has a configuration shown in FIG. 15 (a), is shown in FIG. 15 (b) It is not possible to determine whether or not it has an arrangement. Therefore, both the straight line 88 and the straight line 89 are recognized as screen line candidates. Which of the straight line 88 and the straight line 89 is the true screen line is determined from the angle formed by the straight line 88 and the straight line 89 and the X axis and / or the Y axis.

In the third method of extracting the screen line, the screen line is extracted from the shape of the halftone dot 81 as shown in FIG. The halftone dot 81 is printed such that the direction in which the square side that is the outline of the halftone dot 81 extends or the direction in which the diagonal line extends coincides with the screen line direction. The printed halftone dot 81 has a generally square shape even if the shape has collapsed to some extent. In a third method of extracting screen lines, direction, extending sides 81 ₅ of the square, or extends in a direction diagonal 81 ₆ is extended, and, the straight line passing through the center point of the dot 81, the screen wire It is recognized that there is.

Further, as shown in FIG. 10, a screen line angle θ formed by the extracted screen line and the X axis is calculated (step S13). It is assumed that point A and point C are on the screen line 94 as shown in FIG. A perpendicular foot drawn from a point C to a straight line 95 passing through the point A and parallel to the X axis is defined as a point B. The screen line angle θ is
θ = tan ⁻¹ (AB / BC).
The screen line angle θ can be expressed as (n _AB , n _BC ) using the number of dots n _AB above the line segment _AB and the number of dots n _BC above the line segment BC. is there.

  The screen line angle θ is added to the print dot compression data module 55 described above. When an image is restored from the print halftone compression data module 55, the screen line angle θ included in the print halftone compression data module 55 is used.

Further, as shown in FIG. 10, the screen line density D is calculated (step S14). The screen line density D is calculated as follows. As shown in FIG. 18, when the straight line orthogonal to the screen line 96 extracted in step S12 is a straight line BC, the number of screen lines 96 intersecting the straight line BC per unit length is the screen line density D. Is calculated as The screen line density D is expressed as follows, where the distance between the screen lines 96 is d _s .
D = 1 / d _s .
The screen line density D is added to the print dot compression data module 55 described above. When an image is restored from the print halftone compression data module 55, the screen line density D included in the print halftone compression data module 55 is used.

  Further, as shown in FIG. 10, a halftone dot vector is calculated (step S15). A process of calculating a halftone vector from the halftone dots 101 arranged on the screen line 102 as shown in FIG. 19 will be described below.

  One of the halftone dots 101 is defined as a characteristic halftone dot. For the characteristic halftone dot, a halftone dot vector that is an 8-dimensional vector is obtained. At this time, a feature halftone dot determined for the first screen line of the screen lines 102 is called a reference feature halftone dot. When the determined feature halftone dot is a reference feature halftone dot, the position and area of the reference feature halftone dot are added to the print halftone dot compression data module 55.

In this embodiment, first, as a characteristic dot dot 101 _0, dot vector p ₀ is obtained. Dot 101 ₀ is a reference characteristic dot, and the location and area, is added to the print dot compression data module 55.

Subsequently, the x ¹ axis, the x ² axis, the x ³ axis, and the x ⁴ axis are determined with the center point of the characteristic halftone dot as the origin. The x ¹ axis direction is a direction parallel to the screen line 102. x ² axial direction, a screen line 102 perpendicular direction. The x ³ axis direction and the x ⁴ axis direction are directions that form an angle of 45 ° with the screen line 102. As origin dot 101 _0, x ¹ axis, x ² axis, x ³ axis, it is x ⁴ axes defined.

Of the components of the halftone dot vector p ₀ , two components determined in relation to the x ¹ axis are obtained. Among the components of the halftone dot vector p ₀ , a vector having two components defined in relation to the x ¹ axis as components is called a halftone dot small vector p ¹ ₀ . Similarly, among the components of the halftone dot vector p ₀ , vectors each having two components defined in relation to the x ² axis, the x ³ axis, and the x ⁴ axis are respectively represented by the halftone dot small vector p. ² ₀ , halftone dot small vector p ³ ₀ , halftone dot small vector p ⁴ ₀ .

First, the dot small vector p ¹ ₀ is required. The halftone dot vector p ¹ ₀ is calculated from the positions and areas of the halftone dots 101 ¹ _{1 to} 101 ¹ _n on the x ¹ axis in the halftone dot 101.

When obtaining the halftone dot vector p ¹ ₀ , first, a virtual coordinate system Q ¹ is determined. In the virtual coordinate system Q ^1, as shown in Figure 20, dot 101 ₀ a feature point is located at the origin O ^1. Furthermore, dot 101 ¹ ₀ ~101 ¹ _n are arranged in point P ^{₁ 1} ~P ¹ _n, respectively.

The coordinates of the points P ¹ _{1 to} P ¹ _n are determined as follows. Of the points P ¹ _{1 to} P ¹ _n , the x coordinate of the point P ¹ _i is x ¹ _i and the y coordinate is y ¹ _i . In this case, x-coordinate x ¹ _i of the point P ¹ _i is equal defined in the distance between the halftone dots 101 ¹ _i and dot 101 ₀ in a real space. Moreover, y-coordinate y ¹ _i, when the area of dot 101 ¹ _i and S ¹ _i, the area of dot 101 ₀ S _0, the following equation:
y ¹ _i = S ¹ _i −S ₀ ,
Determined by.

Further, let q ¹ _j be the position vector of the point P ¹ _i in the virtual coordinate system Q ¹ . The position vector q ¹ _i is
q ¹ _i = (x ¹ _i , y ¹ _i )
It is determined as Further, the adjacent halftone dot vector a ¹ _i is
a ¹ _i = q ¹ _i −q ¹ _i−1 ,
It is defined as An adjacent halftone dot vector a ¹ _i is a difference between position vectors of two adjacent halftone dots. The adjacent halftone vector a ¹ _i is
a ¹ _i = (Δx ¹ _i , Δy ¹ _i ),
here,
Δx ¹ _i = x ¹ _i −x ¹ _i−1 ,
Δy ¹ _i = y ¹ _i −y ¹ _i−1 .

The halftone dot vector p ₀ ¹ is determined to be equal to the position vector q ¹ _{k ′,} where _{k ′} is the minimum value of the integer k that satisfies the following condition.
conditions:
For all integers j between 2 and k
| X ¹ _j | ≦ x _max , (a)
| Y ¹ _j | ≦ y _max , (b)
Δx ¹ _j ≦ x _dif , (c)
Δy ¹ _j ≦ y _dif . ... (d)
Here, x _max , y _max , x _dif and y _dif are predetermined reference values.

More specifically, it is determined as follows. First, for j = 2, it is determined whether the condition (d) is satisfied from the condition (a). If any one of the conditions (a) to (d) is not satisfied, the small dot vector p ¹ ₀ is defined as the position vector q ¹ ₁ .

Subsequently, for j = 3, it is determined whether the condition (d) is satisfied from the condition (a). At this time, if any of the conditions (a) to (d) is not satisfied, the halftone dot vector p ¹ ₀ is determined as the position vector q ¹ ₂ .

Hereinafter, it is determined whether the condition (d) is satisfied from the condition (a) while j is sequentially increased. For the first time when j = k ′ + 1, when any of the conditions (a) to (d) is not satisfied, the halftone dot vector p ¹ ₀ is determined to be the position vector q _{k ′} .

In the case shown in FIG. 20, when j is 2 or more and 4 or less, all of the conditions (a) to (d) are satisfied. However, when j = 5,
| Y ¹ ₅ |> y _max
Therefore, the condition (b) is not satisfied. therefore,
k ′ = 4
It is determined. In other words, the dot small vector p ¹ ₀ is,
p ¹ ₀ = q ¹ ₄ ,
It becomes.

A halftone dot vector p ¹ ₀ equal to the position vector q _{k ′} is a vector having an origin O, that is, a point P ₀ as a start point and a point P _{k ′} as an end point. At this time,
p ¹ ₀ = (x ¹ _{k ′} , y ¹ _{k ′} )
_{^{= (X 1 k ', S}} 1 k' -S 0).
As described above, x ¹ _{k 'is} the dot 101 _0, dot 101 ¹ _k' is the distance between. Furthermore, S ¹ _k '-S ₀ is dot 101 ₀ and dot 101 ¹ _k' is the area difference between the. That is, dot small vector p ¹ ₀ is a vector of the distance between the dot ₁₀₁₀ and the dot 101 _k, and area difference between the dot ₁₀₁₀ and the dot 101 _k and components. Therefore, the halftone dot small vector p ¹ ₀ includes information about positions and areas up to halftone dots 101 _{1 to} 101 _{k ′} .

The same calculation is performed for the x ² axis, the x ³ axis, and the x ⁴ axis, and the halftone dot vector p ² ₀ , the halftone dot vector p ³ ₀ , and the halftone dot vector p ⁴ ₀ are obtained, respectively. The halftone dot vector p ² ₀ is calculated from halftone dots 101 ² _{1 to} 101 ² _n on the x ² axis among the halftone dots 101. process x ² dot small vector p ² ₀ halftone dot 101 ² _1-101 ² _n above the axes are calculated, dot 101 ¹ _1-101 dot from ¹ _n above the x ¹ axis it is similar to the process in which the small vector p ¹ ₀ is calculated.

Further, dot small vector p ³ _0, of the dot 101, is calculated from the dot 101 ³ ₁ to 101 ³ _n above the x ³ axis. x ³ dot 101 above the shaft ³ _1-101 ³ process halftone from _n small vector p ³ ₀ is calculated, dot from dot 101 ¹ _1-101 ¹ _n above the x ¹ axis it is similar to the process in which the small vector p ¹ ₀ is calculated.

Dot small vector p ⁴ _0, of the dot 101, is calculated from the dot 101 ⁴ ₁ to 101 ⁴ _n above the x ⁴ axes. x ⁴ dot 101 at the top of the shaft ⁴ _1-101 ⁴ process halftone from _n small vector p ⁴ ₀ is calculated, dot 101 ¹ _1-101 dot from ¹ _n above the x ¹ axis it is similar to the process in which the small vector p ¹ ₀ is calculated.

Dot small vector p ¹ _0, dot small vector p ² _0, dot small vector p ³ _0, and the dot small vector p ⁴ _0, dot vector p ₀ is obtained.

The halftone dot vector p ₀ includes information on the position and area of a halftone dot on the x ¹ axis and between the halftone dot 101 ₀ and the halftone dot 101 ¹ . Further, the halftone dot vector p ₀ includes information on the position and area of a halftone dot which is on the x ² axis and between the halftone dot _{10 10} and the halftone dot 101 ² . Further, the halftone dot vector p ₀ includes information on the position and area of a halftone dot which is on the x ³ axis and between the halftone dot _{10 10} and the halftone dot 101 ³ . Further, the dot vector p _0, is on the x ⁴ axes, and a dot 101 _0, the position of the dot, and the area information contained in between the dot 101 ^4.

Subsequent to the calculation of the halftone dot vector p ₀ , another halftone dot 101 ¹ _{k ′} which is the end point of the small dot vector p ¹ ₀ is determined as a characteristic halftone dot, and another halftone dot vector p _{k ′} is calculated. . Hereinafter, toward the + x ¹ axially, sequentially, the calculation of the dot vector is performed.

  The dot vector is calculated in the same manner for other screen lines. A halftone dot vector is calculated for all halftone dots included in the vector print halftone dot image element data 52.

The halftone dot vector p generated in this way is an 8-dimensional vector, and its components are
p = (x ¹ , ΔS ¹ , x ² , ΔS ² , x ³ , ΔS ³ , x ⁴ , ΔS ⁴ )
It is expressed. However,
x ¹ : distance between the feature halftone dot and another halftone dot x ¹ halftone dot on the x ¹ axis ΔS ¹ : difference in area between the feature halftone dot and the aforementioned x ¹ halftone dot x ² : and wherein dot, x ² distance between x ² dot is another dot above the axis [Delta] S ^3: the characteristic dot, difference x of the area of the x ³ dots of the foregoing ^3: wherein dot When, x ³ distance x ³ dot is another dot above the axis [Delta] S ^3: the characteristic dot, difference x ⁴ area of the x ³ dots of the foregoing: the characteristic dot, x ⁴ the distance between the x ⁴ halftone is another dot at the top of the shaft [Delta] S ^4: the characteristic dot, which is the difference in area between the x ⁴ dot above.

  The calculated halftone dot vector is encoded, and the print halftone dot compression data module 55 is calculated (step S16). At this time, the halftone vector is encoded while being compressed, so that the compression rate is increased.

  Through the above process, the print dot image element data 52 is compressed by the print dot pattern compression algorithm, and the print dot compression data module 55 is generated.

  On the other hand, as shown in FIG. 1, the line drawing image element data 53 is compressed by a line drawing compression algorithm, and a line drawing compression data module 56 is generated (step S05). In the line drawing compression algorithm, an edge of an image element is detected, and a vector indicating the direction of the edge is calculated. Further, the vector is encoded, and a line drawing compressed data module 56 is generated.

  In the following, the line drawing compression algorithm will be described in detail.

  The line image compression algorithm will be described by taking as an example the case where the original image 110 shown in FIG. 21 is compressed by the line image compression algorithm. First, as shown in FIG. 22, the original image 110 is scanned along the scanning line 111, and the gradation of the original image 110 is detected. The scanning line 111 is parallel to the X axis. An edge 112 of the original image 110 is detected from the amount of change in gradation. The edge 112 is at a position where the gradation changes rapidly.

  The direction of the scanning line 111 is not limited to the direction parallel to the X axis. The scan line 111 can be parallel to the Y axis, and can be in other directions.

  Thus, detecting the edge 112 by scanning the original image 110 along the scanning line 111 speeds up the detection of the edge 112 of the original image 110. This is preferable in that the compression of the data indicating the image shown in the line drawing is accelerated.

FIG. 23 shows the detected edge 112. The detected edges 112 are linked to generate a contour line. First, the edge 112 ₁ closest to the origin O is selected. Further, of the edges 112, the edge 112 ₂ having the point farthest from the origin O is selected. The edge 112 ₁ and the edge 112 ₂ are linked to generate a contour line.

Further, an edge 112 _{3 that} is second closest to the origin O and an edge 112 _{4 that} is second closest to the origin O are selected. Edge 112 ₃ and the edge 112 ₄ and the linked contour is generated.

  When other edges exist, they are linked in the same manner to generate a contour line.

However, as shown in FIG. 24, when the area a of the region 113 inside the contour line generated by linking the edge 112 ₅ and the edge 112 ₆ is smaller than a predetermined value η, the edge 112 ₅ and the edge 112 ₆ is determined to be noise. An edge 112 ₅ and 112 ₆ are discarded.

FIG. 25 shows the generated contour line. The contour line 114 ₁ is generated by linking the edge 112 ₁ and the edge 112 ₂ . The contour 114 ₂ is generated by linking the edge 112 ₃ and the edge 112 ₄ .

Along the contour line 114 _1, the contour vector 115 _{1-115 4} is determined. Along the contour line 114 _2, contour vector 115 _{5-115 8} is determined. Further, position vectors 116 ₁ and 116 ₂ indicating the positions of the contour lines 114 ₁ and 114 ₂ are defined, respectively.

  The contour line is smoothed as necessary to reduce the number of contour vectors.

  As shown in FIG. 26, it is assumed that contour vectors OA, AC, CD, and DB are defined along the contour line. This corresponds to the case where a convex contour line is locally defined. At this time, whether the contour vectors OA, AC, CD, and DB are left as they are or whether the contour vectors OA, AC, CD, and DB are integrated and only the contour vector OB is left is determined as follows. It is done.

A straight line 116 passing through the point O and parallel to the X axis is defined. A perpendicular foot drawn from the point B to the straight line 116 is defined as a point B ′. At this time, the length l _AC of the line segment _AC and the length l _{BB ′} of the line segment BB ′ are
l _{BB ′} −l _AC ≦ α ₁ , (e)
When satisfying, the contour vectors OA, AC, CD, and DB are integrated to generate a contour vector OB. α ₁ is a predetermined reference value. If the condition (e) is not satisfied, the contour vectors OA, AC, CD, and DB are left as they are. The case where the condition (e) is satisfied is a case where the convex portion existing on the contour line is small. When the condition (e) is satisfied, it is determined that the convex portion existing on the contour line is small, and the convex portion is ignored.

Whether the contour vectors OA, AC, CD, and DB are left as they are or only the contour vector OB is left, where the area of the triangle ACD is S _ACD and the area of the triangle OBB ′ is S _{OBB ′} , the following condition:
S _OBB'− S _ACD ≦ α ₂ (f)
It is also possible to judge by α ₂ is a predetermined reference value. When the condition (f) is satisfied, the contour vectors OA, AC, CD, and DB are integrated to generate a contour vector OB. When the condition (f) is not satisfied, the contour vectors OA, AC, CD, and DB are left as they are. The case where the condition (f) is satisfied is a case where the convex portion existing on the contour line is small. When the condition (f) is satisfied, it is determined that the convex portion existing on the contour line is small, and the convex portion is ignored.

  Further, as shown in FIG. 27, it is assumed that contour vectors OA and AB are determined along the contour line. At this time, whether the contour vectors OA and AB are left as they are or whether the contour vectors OA and AB are integrated into the contour vector OB is determined as follows.

A straight line 117 passing through the point O and parallel to the X axis is defined. Let the feet of the perpendicular line drawn from the point A and the point B to the straight line 117 be the point A ′ and the point B ′, respectively. Furthermore, the area of the triangle OAA ′ is S _{OAA ′} and the area of the triangle OBB ′ is S _{OBB ′} .
S _{OBB ′} −S _{OAA ′} ≦ α ₃ (g)
Is satisfied, the contour vectors OA and AB are integrated to generate the contour vector OB. When the condition (g) is not satisfied, the contour vectors OA and AB are left as they are. Satisfying the condition (g) corresponds to a case where the curve of the contour line is local and small. When the condition (g) is satisfied, the curve of the contour line is ignored.

  The contour vector and the position vector generated by the above process are encoded. Further, gradation data indicating the gradation of the image element existing between the contour lines is encoded. At this time, the number of gradations may be two, or may be more than that, for example, 256.

  The encoded contour vector and gradation are compressed image data. Through the above process, image compression by the line drawing compression algorithm is completed. The line drawing image element data 53 is compressed by the above-described line drawing compression algorithm, and a line drawing compression data module 56 is generated.

  As shown in FIG. 1, the free fine dot compression data module 54, the print halftone dot compression data module 55, and the line drawing compression data module 56 are combined into one data, and a batch compression data module 57 is generated. (Step S06). The batch compressed data module 57 can be used by being recorded on a recording medium.

  Through the above process, the compression of the paper image data 50 is completed. The free fine dot compression data module 54, the print halftone dot compression data module 55, and the line drawing compression data module 56 can be stored as separate files without being integrated.

  Subsequently, a process of restoring the original image from the batch compressed data module 57 will be described. First, as shown in FIG. 28, the free fine dot compressed data module 54, the print halftone dot compressed data module 55, and the line drawing compressed data module 56 are restored from the batch compressed data module 57 (step S21). If the free fine dot compression data module 54, the print halftone dot compression data module 55, and the line drawing compression data module 56 are not integrated and stored as separate files, step S21 is not performed.

  The free fine dot compressed data module 54 is restored by a free fine dot pattern restoration algorithm, and free fine dot temporary data 58 is generated (step S22). In the free fine dot pattern restoration algorithm, the inverse transformation of the transformation performed by the above-described free fine dot pattern compression algorithm is performed.

  That is, the free fine dot compressed data module 54 includes data obtained by encoding and compressing the pattern of the area patch 71 described above. First, the code indicating the pattern is restored, and further, the pattern included in the area patch 71 is reproduced. The patterns of the area patches 71 are arranged as they are, and free fine-point temporary data 58 is generated. The free fine spot temporary data 58 includes data indicating the free fine spot portion of the original image 30.

  The print dot compression data module 55 is restored by the print dot restoration algorithm, and print dot temporary data 59 is generated (step S23).

  As described above, the halftone dot vector p obtained when the print halftone dot compression data module 55 is determined to be a characteristic halftone dot is encoded.

The dot vector p is as described above,
p = (x ¹ , ΔS ¹ , x ² , ΔS ² , x ³ , ΔS ³ , x ⁴ , ΔS ⁴ )
It is expressed. However,
x ¹ : distance between the feature halftone dot and another halftone dot x ¹ halftone dot on the x ¹ axis ΔS ¹ : difference in area between the feature halftone dot and the aforementioned x ¹ halftone dot x ² : and wherein dot, x ² distance between x ² dot is another dot above the axis [Delta] S ^3: the characteristic dot, difference x of the area of the x ³ dots of the foregoing ^3: wherein dot And the distance between the x ³ halftone dot and the other halftone dot on the x ³ axis ΔS ³ : difference in area between the characteristic halftone dot and the aforementioned x ³ halftone dot x ⁴ : the characteristic halftone dot and x ⁴ the distance between the x ⁴ halftone is another dot at the top of the shaft [Delta] S ^4: the characteristic dot, which is the difference in area between the x ⁴ dot above.

  FIG. 29 is a flowchart showing a printing dot restoration algorithm. First, the printing dot compression data module 55 is decrypted (step S31).

  The screen line density D and the screen line angle θ are extracted from the decoded print halftone dot compression data module 55 (step S32). The direction and the number of screen lines defined for the restored image are determined.

  The position and area of the reference feature halftone dot are extracted from the decoded print halftone dot compression data module 55 (step S33).

  Further, a halftone dot vector p defined for the reference feature halftone dot is extracted. Further, the position and area of another halftone dot are determined by interpolation based on the halftone dot vector p (step S34).

  FIG. 30 shows a process in which the positions and areas of other halftone dots are determined. The screen line 121 is restored from the screen line density D extracted in step S32 and the screen line angle θ.

Further, the reference feature halftone dot 122 is restored based on the position and area of the reference feature halftone dot 122 extracted in step S32. Subsequently, the x ¹ axis, x ² axis, x ³ axis, and x ⁴ axis are determined using the reference feature halftone dot 122 as the origin, as shown in FIG.

Further, from the component x ¹ of the halftone dot vector p defined for the reference feature halftone dot 122 and ΔS ¹ , the point position and the area of the center of the feature halftone dot 123 ¹ on the x ¹ axis are determined. It is done. The feature halftone dot 123 ¹ is restored. Further, based on the position and area of the reference feature halftone dot 122 and the feature halftone dot 123 ¹ , the position and area of the halftone dot 124 ¹ located between them is based on the component x ¹ and the component ΔS ^1. , Obtained by interpolation. The area of the halftone dot 124 ¹ is in a range between the area of the reference feature halftone dot 122 and the area of the feature halftone dot 123 ¹ . The halftone dot 124 ¹ is restored.

Further, the position and area of the feature halftone dot 123 ² on the x ² axis are determined from the component x ² of the halftone dot vector p defined for the reference feature halftone dot 122 and ΔS ² . The feature halftone dot 123 ² is restored. Based on the position and area of the reference feature halftone dot 122 and the feature halftone dot 123 ² , the position and area of the halftone dot 124 ² located between them is interpolated based on the component x ² and the component ΔS ^2. Is required. The area of the halftone dot 124 ² is in a range between the area of the reference feature halftone dot 122 and the area of the feature halftone dot 123 ² . The halftone dot 124 ² is restored.

Furthermore, the dot vector p components x ³ that have been determined for reference features dot 122, the [Delta] S ³ Prefecture, the position of the feature dot 123 ³ above the x ³ axis is determined and the area. The feature halftone dot 123 ³ is restored. Based on the position and area of the reference feature halftone dot 122 and the feature halftone dot 123 ³ , the position and area of the halftone dot 124 ³ located between them is interpolated based on the component x ³ and the component ΔS ^3. Is required. The area of the halftone dot 124 ³ is in a range between the area of the reference feature halftone dot 122 and the area of the feature halftone dot 123 ³ . Dot 124 ³ is restored.

Furthermore, the dot vector p components x ⁴ of which are determined for the reference characteristic dot 122, the [Delta] S ⁴ Prefecture, the position of the feature dot 123 ⁴ above the x ⁴ axis is determined and the area. Wherein dot 123 ⁴ is restored. Based on the position and area of the reference feature halftone dot 122 and the feature halftone dot 123 ⁴ , the position and area of the halftone dot 124 ⁴ located between them is interpolated based on the component x ⁴ and the component ΔS ^4. Is required. The area of the halftone dot 124 ⁴ is in a range between the area of the reference feature halftone dot 122 and the area of the feature halftone dot 123 ⁴ . Dot ¹²⁴⁴ is restored.

Subsequently, other feature halftone dots and other halftone dots are restored from the other halftone dot vectors determined for the feature halftone dots 123 ¹ . Similarly, other feature halftone dots and other halftone dots are restored from other halftone dot vectors determined for feature halftone dots on the same screen line 121 as the reference feature halftone dot 122.

  Further, the same calculation as described above is performed for all the reference feature halftone dots on the other screen lines 121, and all other feature halftone dots and halftone dots are restored. The restoration of the image element composed of the print halftone dots is completed (step S35). The restored image element is stored as print halftone dot temporary data 59.

  On the other hand, as shown in FIG. 28, the line drawing compressed data module 56 is restored by the line drawing restoration algorithm, and the line drawing temporary data 60 is generated (step S24).

As described above, the line drawing compressed data module 56 encodes gradation data indicating the gradation of the image element existing between the outline vector, the position vector, and the outline. First, an outline vector 115 _{1-115 8,} the position vector 116 _1, 116 ₂ are decoded. The contour vectors 115 _{1 to} 115 ₈ are arranged at positions indicated by the position vectors 116 ₁ and 116 ₂ as shown in FIG. Disposed contour vector 115 _{1-115 8} constitutes the contour line 114 _1, 114 _2.

Further, the region 117 between the contour lines 114 ₁ and 114 ₂ is filled with the gradation indicated by the gradation data encoded in the line drawing compressed data module 56, and the restoration of the image element composed of the line drawing is completed. . The restored image element is stored as line drawing temporary data 60. At this time, the region 117 between the contour lines 114 ₁ and 114 ₂ can be filled with another pattern. By embedding another pattern in the region 117 between the contour lines 114 ₁ and 114 ₂ , special image processing becomes possible. At this time, data such as music and voice can be put in the area 117 as a digital watermark.

  As shown in FIG. 28, the free fine dot temporary data 58, the print halftone dot temporary data 59, and the line drawing temporary data 60 are combined to generate restored image data 61 (step S25). The restored image data 61 shows an image that is substantially the same as the original paper image data 50.

  In the image data compression method and restoration method of the present embodiment, the image on the paper surface captured by a scanner or the like is sorted into image elements and extracted. Further, each image element is compressed and decompressed with a corresponding algorithm. As a result, the compression rate is improved, and further, deterioration of image quality due to compression and decompression is suppressed.

  Further, in the image data compression method and decompression method of the present embodiment, a halftone vector is generated from halftone dots included in an image. Redundancy of halftone dots is effectively utilized. Thereby, the compression rate is improved.

  In step S02 of the present embodiment, the print halftone dots are extracted by the process described below, and the print halftone image element data 52 can be generated.

  First, a portion corresponding to a collection of point regions having an area smaller than the maximum area of printing halftone dots determined in the printing rule is extracted from the paper surface image data 50. The dot area can be both a print halftone dot and a non-print halftone dot. Subsequently, the position of each central point of the point area is calculated. The calculation method is the same as the method in which the position of the center point of the printing halftone dot is calculated in the above-described printing dot compression algorithm.

  Further, it is determined whether or not screen lines can be defined at equal intervals so as to pass through the vicinity of the center point of the point area. If the screen line can be defined, it is determined that the collection of the dot areas is a collection of printing halftone dots. A collection of the dot areas is extracted, and print dot image element data 52 is generated.

  In the present embodiment, it is also possible to compress and further restore the color image. In this case, as shown in FIG. 32, the paper surface image data is separated for each color.

  Similar to the case where the monochrome image is compressed, the color image printed on the paper surface is taken in, and the color paper surface image data 62 is generated (step S41).

  The color paper image data 62 is separated for each color (step S42). The cyan (C) component is extracted from the color paper surface image data 62, and blue plate paper image data 63a is generated. The magenta (M) component is extracted from the color paper surface image data 62, and red plate paper image data 63b is generated. The yellow (Y) component is extracted from the color paper surface image data 62, and the yellow paper surface image data 63c is generated. The black (K) component is extracted from the color paper surface image data 62, and the black paper surface image data 63d is generated. That is, the color paper surface image data 62 is separated into CMYK systems.

  Image elements are extracted in the same manner as in step S02 shown in FIG. 1 for each of blue plate paper image data 63a, red plate paper image data 63b, yellow plate paper image data 63c, and black plate paper image data 63d. Sorting is performed (step S43). From the blue paper image data 63a, the red printing paper image data 63b, the yellow printing paper image data 63c, and the black printing paper image data 63d, respectively, the blue printing free fine dot image data 64a and red representing an image composed of free thin printing dots, respectively. Plate free fine dot image data 64a, yellow free free dot image data 64c, and black free fine dot image data 64d are generated.

  Further, from the blue printing paper surface image data 63a, the red printing paper surface image data 63b, the yellow printing paper surface image data 63c, and the black printing paper surface image data 63d, respectively, blue printing printing dot image data indicating an image composed of printing halftone dots. 65a, red printing dot image data 65b, yellow printing dot image data 65c, and black printing dot image data 65d are generated.

  Further, from the blue plate paper image data 63a, the red plate paper image data 63b, the yellow plate paper image data 63c, and the black plate paper image data 63d, respectively, blue plate image data 66a indicating an image composed of images with strong edges. , Red line image data 66b, yellow line image data 66c, and black line image data 66d are generated.

  The blue plate free fine dot image data 64a, the red plate free fine dot image data 64a, the yellow plate free fine dot image data 64c, and the black plate free fine dot image data 64d are compressed by the above-described free fine dot pattern compression algorithm. Free fine dot temporary data 67a, red free fine dot temporary data 67b, yellow free free dot temporary data 67c, and black free fine dot temporary data 67d are generated (step S44).

  The blue printing halftone image data 65a, the red printing halftone image data 65b, the yellow printing halftone image data 65c, and the black printing halftone image data 65d are compressed by the above-described printing halftone compression algorithm. Printing halftone dot temporary data 68a, red printing halftone dot temporary data 68b, yellow printing halftone dot temporary data 68c, and black printing halftone dot temporary data 68c are generated (step S45).

  The blue print line drawing image data 66a, the red print line drawing image data 66b, the yellow print line drawing image data 66c, and the black print line drawing image data 66d are compressed by the above-described line drawing compression algorithm, respectively. Data 69b, yellow print line drawing temporary data 69c, and black print line drawing temporary data 69c are generated (step S46).

  Blue plate free fine dot temporary data 67a, Red plate free fine dot temporary data 67b, Yellow plate free fine dot temporary data 67c, Black plate free fine dot temporary data 67d, Blue plate halftone dot temporary data 68a, Red plate halftone dot Temporary data 68b, yellow printing halftone dot temporary data 68c, black printing halftone dot temporary data 68c, blue printing line drawing temporary data 69a, red printing line drawing temporary data 69b, yellow printing line drawing temporary data 69c, and black printing line drawing temporary data 69c Are integrated to generate a batch compressed data module 57 ′ (step S47). The compression of the color paper surface image data 62 is completed.

  Note that the color paper image data 62 is not separated from the CMYK system, but may be separated into other color systems, for example, an RGB system in which red (R), green (G), and blue (B) are the three primary colors. Of course it is possible.

In this embodiment, halftone dot vectors are calculated for all of the x ¹ axis, x ² axis, x ³ axis, and x ⁴ axis, but the x ¹ axis, x ² axis, x ³ axis, x It is not always necessary to calculate the dot vector p for all ^four axes. However, the calculation of the halftone dot vector for a plurality of axes among the x ¹ axis, the x ² axis, the x ³ axis, and the x ⁴ axis as in the present embodiment improves the compression ratio. Is preferable.

  In the present embodiment, when the restored image data 61 is generated, the image can be enlarged and reduced. In this case, the free fine dots included in the free fine dot temporary data 58 generated by restoring the free fine dot compressed data module 54 are enlarged at the enlargement ratio α or reduced at the reduction ratio β.

  Further, the print halftone dot temporary data 59 is subjected to an operation for enlarging or reducing the image element as described below.

  A case where an image element included in the print halftone dot temporary data 59 is enlarged will be described. It is assumed that the halftone dot temporary data 59 includes halftone dots 131 to 139 as shown in FIG. The halftone dots 131 to 139 are assumed to be located at points A to H, respectively.

Consider a case where an image element including halftone dots 131 to 139 is enlarged at an enlargement ratio α with the point A as the center of enlargement. As shown in FIG. 33, first, the halftone dot 132 is virtually moved to a point B ₁ on a straight line connecting the point A that is the center point of the enlargement and the point B where the halftone dot 132 is located. .

At this time,
α = AB ₁ / AB.
The virtually moved halftone dot 132 is hereinafter referred to as a virtual halftone dot 132 ′. The area of the virtual halftone dot 132 ′ is the same as the area of the halftone dot 132. The virtual halftone dot 132 ′ is a virtually moved halftone dot, and the virtual halftone dot 132 ′ is not actually arranged.

  Subsequently, among the points between the halftone dot 131 adjacent to the opposite side to the direction in which the halftone dot 132 is moved and the virtual halftone dot 132 ′, the printing rule determines that the halftone dot exists. At that point, a new halftone dot is generated. The generated new halftone dot is denoted as halftone dot 132 ''. In the case shown in FIG. 33, the position of the halftone dot 132 ″ matches the position of the halftone dot 132. The area of the new halftone dot 132 ″ is the area of the halftone dot 131 that is on the opposite side to the direction in which the halftone dot 132 is moved, and the virtual halftone dot 132 ′. Are interpolated. In this interpolation, the positions of the halftone dot 131, the virtual halftone dot 132 ', and the new halftone dot 132 "are referred to.

  Data indicating the area of the new halftone dot 132 ″ is recorded in the print halftone dot temporary data 59 that is subjected to the calculation for enlarging the image element. At this time, data indicating the area of the virtual halftone dot 132 'is discarded.

Other halftone dots are virtually moved in the same manner, and new halftone dots are generated. Data indicating the area of the generated new halftone dot is recorded in the print halftone dot temporary data 59. The halftone dot 133 is virtually moved to the point C ₁ , and the halftone dot 134 is virtually moved to the point D ₁ , thereby defining virtual halftone dots 133 ′ and 134 ′.
At this time,
α = AC ₁ / AC = AD ₁ / AD.
Further, new halftone dots 133 ″ and 134 ″ are generated at the same positions as the halftone dots 133 and 134.

  Further, the same calculation is performed for other halftone dots, and the area of newly generated halftone dots is sequentially obtained. Through the above process, the enlargement of the image element is completed.

  At this time, the enlargement ratio α can be partially changed. As a result, a deformed image element can be generated.

  Next, a case where an image element included in the print dot temporary data 59 is reduced will be described. The print halftone dot temporary data 59 includes halftone dots 231 to 239 as shown in FIG. The halftone dots 231 to 239 are assumed to be located at points A to H, respectively.

Consider a case where an image element including halftone dots 231 to 239 is enlarged at a reduction ratio β with the point A as the center of reduction. As shown in FIG. 34, first, the halftone dot 232 is virtually moved to a point B ₁ on a straight line connecting the point A which is the central point of reduction and the point B where the halftone dot 232 is located. A virtual halftone dot 232 ′ is defined.

At this time,
β = AB ₁ / AB.
Further, the area of the virtual halftone dot 232 ′ is the same as the area of the halftone dot 232.

Subsequently, among the halftone dots adjacent to the halftone dot 232, printing is performed out of the dots between the halftone dot 235 that is opposite to the direction in which the halftone dot 232 is moved and the virtual halftone dot 232 ′. A new halftone dot is generated at a point where the rule defines that a halftone dot exists. The generated new halftone dot is denoted as halftone dot 232 ″. In the case shown in FIG. 34, the position of the halftone dot 232 ″ matches the position of the halftone dot 232. The area of the new halftone dot 232 ″ is determined by interpolating the halftone dot 235 adjacent to the opposite side to the direction in which the halftone dot 232 is moved and the area of the virtual halftone dot 232 ′.
In this interpolation, the positions of the halftone dot 235, the virtual halftone dot 232 ′, and the new halftone dot 232 ″ are referred to.

  Data indicating the area of the new halftone dot 232 ″ is recorded in the print halftone temporary data 59 on which the image element reduction operation is performed. At this time, data indicating the area of the virtual halftone dot 232 'is discarded.

Other halftone dots are virtually moved in the same manner, and new halftone dots are generated. Data indicating the area of the generated new halftone dot is recorded in the print halftone dot temporary data 59. The halftone dot 233 is virtually moved to the point C ₁ , and the halftone dot 234 is virtually moved to the point D ₁ , so that virtual halftone dots 233 ′ and 234 ′ are determined.
At this time,
β = AC ₁ / AC = AD ₁ / AD.
Further, new halftone dots 233 ″, 234 ″ are generated at the same positions as the halftone dots 233, 234.

  Further, the same calculation is performed for other halftone dots, and the area of newly generated halftone dots is sequentially obtained. Through the above process, the reduction of the image element is completed.

  At this time, the reduction ratio β can be partially changed. This makes it possible to create a deformed image element.

  Further, by adding various calculation functions other than enlargement and reduction to the print halftone restoration algorithm, other deformation restoration can be performed.

  Further, the line drawing temporary data 60 is subjected to an operation for enlarging or reducing the image element as described below.

  When the image element is reduced, as shown in FIG. 35, the outline vector and the position vector included in the line drawing temporary data 60 are multiplied by the reduction ratio β, and the outline vector 117 and the position vector 118 are generated. Is done. The area 117a on the left side in the direction toward the contour vector 117 is filled with the gradation indicated by the gradation data included in the line drawing temporary data 60, and the reduced image element is restored.

  Similarly, when the image element is enlarged, as shown in FIG. 36, the outline vector and the position vector included in the line drawing temporary data 60 are multiplied by the enlargement factor α to obtain the outline vector 119 and the position vector. 120 is generated. The area 119a on the left side in the direction toward the contour vector 119 is filled with the gradation indicated by the gradation data included in the line drawing temporary data 60, and the enlarged image element is restored.

  In the embodiment of the present invention, it is also possible to restore the image element while rotating the image element using the position information stored in the compressed data.

  As described above, in the present embodiment, a free fine dot pattern compression algorithm is used to compress the free fine dot image element data 51. In this embodiment, instead of the free fine dot pattern compression algorithm, the free fine dot vector compression algorithm described below can be used to generate the free fine dot compressed data module 54.

Consider the case where the free fine dots 141 _{1 to} 141 ₅ shown in FIG. 37 are compressed. First, the positions of the center points of the free fine dots 141 _{1 to} 141 ₅ are determined in the same manner as the process of determining the position of the center point of the print halftone dot described above. The positions of the free fine dots 141 _{1 to} 141 ₅ are represented by the positions of the center points. Hereinafter, the position of the free Hosoten 141 _{1-141 5} means the position of the center point of the free Hosoten 141 _{1-141 5.}

Of the free fine dots 141 _{1 to} 141 ₅ , the coordinates where the free fine dots 141 _i are located are (x _i , y _i ). Furthermore, let S _i be the area of the free fine dot 141 _i .

Free fine dot vectors r _{1 to} r ₃ are obtained as follows. First, the free thin spot 141 ₁ is selected. The position and area of the free fine dot 141 ₁ are added to the free fine dot compressed data module 54. Free Hosoten vector r ₁ is a vector free Hosoten 141 ₁ and the relative position between the free Hosoten 141 _2, free Hosoten 141 ₁ free Hosoten 141 ₂ and the area difference and the components. That is,
r ₁ = (x ₂ −x ₁ , y ₂ −y ₁ , S ₂ −S ₁ ).

Similarly, the free fine dot vector r ₂ is a vector having as its components the relative position between the free fine dot 141 ₂ and the free fine dot 141 ₃ and the area difference between the free fine dot 141 ₁ and the free fine dot 141 ₂ . ,
r ₂ = (x ₃ -x ₂ , y ₃ -y ₂ , S ₃ -S ₂ ).

Similarly, the free fine dot vector r ₃ is
r ₃ = (x ₄ −x ₃ , y ₄ −y ₃ , S ₄ −S ₃ ).
Free fine dot vectors r _{1 to} r ₃ are encoded, and a free fine dot compressed data module 54 is generated.

  Furthermore, in this embodiment, instead of the above-described free fine dot pattern compression algorithm, the free fine dot image element data 51 is compressed by a free fine dot data compression algorithm described below, and free fine dot compression is performed. A data module 54 can be generated.

  In the free fine dot data compression algorithm, the area 210 including the free fine dots 212 is divided into rectangular areas 211. Two sides of the rectangular area 211 are oriented in the x-axis direction, and the other two sides are oriented in the y-axis direction. Compressed data is generated for each rectangular area 211.

  A method of generating the compressed data will be described by taking as an example a case where the compressed data is generated for the rectangular area 211a of the rectangular areas 211. First, the positions where the free thin dots 212a to 212c included in the rectangular area 211a that is the target for generating the compressed data are recognized. Furthermore, the distance between the position where the free fine dots 212a to 212c exist and one of the four sides of the rectangular area 211a is calculated.

In the present embodiment, distances d _a , d _b and d _c between the side 213 extending in the y-axis direction and the positions where the free thin points 212a to 212c exist are calculated. The distance d _a, d _b, d _c is, x ₀ x-coordinate of the side 213, free Hosoten 212a-212c x respectively the x coordinate of the position where there is _a, x _b, as x _c,
d _a = x _a −x ₀ ,
d _b = x _a −x ₀ ,
d _c = x _a −x ₀ .
The calculated distance d is a component of the compressed data generated for the rectangular area 212a. At this time, the distance from the side extending in the x-axis direction can also be calculated.

  Furthermore, the average value of the density of the area inside the rectangular area 211a is calculated. This average value corresponds to the sum of the areas of the free thin spots 212a to 212c on a one-to-one basis. As will be described later, the average value of the density of the area inside the rectangular area 211a is used to restore the area of the free thin dots 212a to 212c. The average value becomes another component of the compressed data generated for the rectangular area 211a. The generation of the compressed data generated for the rectangular area 211a is thus completed.

  Similarly, compressed data is generated for the other rectangular areas 211. The generated compressed data is integrated, and a free fine dot compressed data module 54 is generated.

  The free thin point compressed data module 54 generated as described above is restored as follows. First, the compressed data generated for each rectangular area 211 is extracted from the free fine dot compressed data module 54. As described above, the compressed data includes the distance between the free fine dot included in each rectangular area 211 and the side of the rectangular area. Furthermore, the average value of the density of the area inside each rectangular area 211 is included.

  From the compressed data, the distance between the free fine dot included in each rectangular area 211 and the side of the rectangular area is recognized. Based on the distance, the position of the free fine point is restored.

  Furthermore, the average value of the density of the area inside each rectangular area 211 is recognized from the compressed data. As described above, the area of the free fine dots included in each rectangular area 211 is determined based on the average value. At this time, the free fine dots included in each rectangular region 211 are determined to have the same area. Free fine dots included in each rectangular area 211 are restored. Through the above process, the free fine point temporary data 58 is restored from the free fine point compressed data module 54.

  In the present embodiment, the image element included in the paper image data 50 is subjected to the calculation described below, and the calculated image element can be compressed. Further, when the free fine dot temporary data 58, the print halftone dot temporary data 59, and the line drawing temporary data 60 are combined, the following calculation can be performed.

When all the image elements included in the free fine dot temporary data 58, the print dot temporary data 59, and the line drawing temporary data 60 are restored, an OR operation is performed. For example, it is assumed that the image elements A, B, C, and D are included in the free fine dot temporary data 58, the printing halftone dot temporary data 59, and the line drawing temporary data 60. When all of these are restored, these ORs are generated as restored image data 61. Assuming that the restored image data 61 is X,
X = A OR B OR C OR D.

When all the image elements included in the paper image data 50 are compressed, an OR operation is performed. For example, it is assumed that the image elements A, B, C, and D are included in the paper surface image data 50. When all of these are compressed, these ORs become image data to be compressed. Let X 'be the image data to be compressed,
X ′ = A OR B OR C OR D.D.

When only the common portion of the image elements included in the free fine dot temporary data 58, the print halftone dot temporary data 59, and the line drawing temporary data 60 is restored, an AND operation is performed. It is assumed that the image elements A, B, C, and D are included in the free fine dot temporary data 58, the print halftone dot temporary data 59, and the line drawing temporary data 60. When it is desired to restore the common part of the image elements A and B as the restored image data 61, the restored image data 61 is set as X.
X = A AND B.

Further, when only the common part of the image elements included in the paper surface image data 50 is compressed, an AND operation is performed. For example, it is assumed that the image elements A, B, C, and D are included in the paper surface image data 50. When the common part of the image elements A and B is compressed, the logical product of the image elements A and B becomes image data to be compressed. Let X 'be the image data to be compressed,
X ′ = A AND B.

When the image elements included in the free fine dot temporary data 58, the print halftone dot temporary data 59, and the line drawing temporary data 60 are restored, a NOR operation is performed. For example, it is assumed that the image elements A and C are included in the free fine dot temporary data 58, the print halftone dot temporary data 59, and the line drawing temporary data 60. When restoring image elements other than the image element A and the image element C, the restored image data 61 is set as X,
X = A NOR C.I.

When a portion other than a plurality of image elements among the image elements included in the paper surface image data 50 is compressed, a NOR operation is performed. For example, it is assumed that the image elements A and C are included in the paper surface image data 50. When compressing image elements other than image element A and image element C, the image data to be compressed is X ′,
X ′ = A NOR C.I.

In addition, when restoring a portion other than a common portion of a plurality of image elements among the image elements included in the free fine dot temporary data 58, the print halftone dot temporary data 59, and the line drawing temporary data 60, a NAND operation is performed. . That is, for example, it is assumed that the image elements A and C are included in the free fine dot temporary data 58, the print halftone dot temporary data 59, and the line drawing temporary data 60. When restoring all but the common part of the image element A and the image element C, the restored image data 61 is set as X,
X = A NAND C.I.

When compressing a portion other than the common portion of the plurality of image elements among the image elements included in the paper surface image data 50, a NAND operation is performed. For example, it is assumed that the image elements A and C are included in the paper surface image data 50. When compressing all but the common part of image element A and image element C, the image data to be compressed is X ′,
X ′ = A NAND C.I.

In addition, the image elements included in the free fine dot temporary data 58, the print halftone dot temporary data 59, and the line drawing temporary data 60 can be restored by calculating an exclusive OR. It is assumed that the image elements A and C are included in the free fine dot temporary data 58, the print halftone dot temporary data 59, and the line drawing temporary data 60. When the restored image data 61 is X,
X = A XOR C,
Can be determined.

In addition, the image elements included in the paper image data 50 can be compressed after calculating an exclusive OR. Assume that the image elements A and C are included in the paper surface image data 50. Let X 'be the image data to be compressed,
X ′ = A XOR C,
Can be determined.

  In addition, it is assumed that the image element A and the image element B are included in the free fine dot temporary data 58, the print halftone dot temporary data 59, and the line drawing temporary data 60. At this time, consider a case where the image element B overlaps the image element A. In this case, it is possible to restore the image element A so that the image element A can be seen in the portion where the image elements A and B overlap by restoring the image element A by the transparent process. Further, by restoring the image element A by the opaque process, it is possible to restore the image element A so that only the image element B can be seen in the portion where the image element A and the image element B overlap.

  Among the image elements included in the paper image data 50, the selection of the image element to be compressed is made by selecting the name given to each image element, the size of the image of each image element, the shape of the image of each image element, and each image element. Based on the color of the image and the amount of image data of each image element. Similarly, among the image elements in the free fine dot temporary data 58, the print halftone dot temporary data 59, and the line drawing temporary data 60, the image element to be compressed is selected by the name assigned to each image element and the image element. It can be performed based on the size of the image, the shape of the image of each image element, the color of the image of each image element, and the amount of image data of each image element.

  By the selection / calculation processing as described above, necessary image elements and characteristic image elements can be extracted and restored from the paper image. For example, it is effective for filing and database construction to compress only a photograph, only a sentence, and only a table from the page. In addition, restoring only specific image elements is effective in reducing the amount of information processing when a large number of image elements are distributed and viewed on the Internet.

  In the present embodiment, as described above, the page image data 50 is generated from the image 30 on the page, and the page image data 50 is compressed and restored. In the present embodiment, other image data that is not generated from the paper surface can be compressed and restored instead of the paper surface image data 50.

  In the present embodiment, in step S02, image element data can be sorted and extracted based on other criteria. For example, separation / extraction based on the composition element can be performed. As a result, type letters, handwritten characters, seals, line drawings, graphics, flat nets, gradation nets, and photo nets are separated and further extracted. Further, it is possible to perform sorting / extraction based on the image type. Thereby, the document material, the cartoon material, the map material, the advertisement material, the surface material, and the photograph material are separated and further extracted.

Second embodiment:
The image data compression method and decompression method according to the second embodiment separates an image included in the image data into a region where gradation continuously changes and a region where gradation hardly changes, and the image data is divided. It is a method of compressing and decompressing. The image data compression method and restoration method according to the second embodiment will be described below.

  The image data compression method and decompression method according to the second embodiment are executed using hardware resources. As shown in FIG. 38, the hardware resource 10 ′ includes an input unit 11, a CPU 2, a storage device 3, a recording medium 4, and a bus 5. The input unit 11, CPU 2, storage device 3, and recording medium 4 are connected to a bus 5. Image data 150 is input to the input unit 11. The CPU 2 executes an operation for compressing or restoring the image data 150. The storage device 3 stores the image data 150 and data generated in the course of executing the image data compression method and decompression method according to the second embodiment. The recording medium 4 stores a program in which procedures included in the image data compression method and decompression method according to the second embodiment are described. The CPU 2 operates according to the program. The bus 5 transmits data exchanged among the scanner 1, the CPU 2, the storage device 3, and the recording medium 4.

  FIG. 39 shows an image data compression method according to the second embodiment. First, the image data 150 is input to the input unit 11. The image indicated by the image data 150 includes a region where the gradation changes continuously and a region where the gradation hardly changes. An image element composed of halftone dots is arranged in an area where gradation continuously changes. In an area where the gradation hardly changes, image elements not composed of halftone dots are arranged.

  The image data 150 is binarized and binary data 151 is generated (step S51). Further, the difference between the above-described image data 150 and binary data 151 is calculated, and multi-value data 152 is generated (step S52).

  The image data 150 is classified into binary data 151 and multi-value data 152. A region of the image data 150 where the gradation hardly changes is extracted as binary data 151, and a portion of the image data 150 corresponding to a region where the gradation continuously changes is extracted as multi-value data 152. Is done. As described above, image elements composed of halftone dots are arranged in the region where the gradation continuously changes. Multi-value data 152 is composed of data indicating halftone dots.

  The multi-value data 152 is compressed by the printing dot compression algorithm described in the first embodiment, and the printing dot compression data module 154 is generated (step S53). Further, the binary data 151 is compressed by the line drawing compression algorithm described in the first embodiment, and the line drawing compression data module 155 is generated (step S54).

  The print dot compression data module 154 and the line drawing compression data module 155 are integrated, and the batch compression data module 156 is generated (step S55). The compression of the image data 150 is completed through the above process. The batch compressed data module 156 can be recorded on a recording medium and used.

  Next, a process of restoring the batch compressed data module 156 will be described.

  As shown in FIG. 40, the batch compression data module 156 is divided, and the print dot compression data module 154 and the line drawing compression data module 155 are restored (step S61).

  The print halftone dot compression data module 154 is restored by the print halftone dot restoration algorithm described in the first embodiment, and print halftone dot temporary data 157 is generated (step S62). In the print halftone dot temporary data 157, an image composed of halftone dots is restored.

  Further, the line drawing compressed data module 155 is restored by the line drawing restoration algorithm described in the first embodiment, and line drawing temporary data 158 is generated (step S63).

  Further, the print halftone dot temporary data 157 and the line drawing temporary data 158 are combined to generate restored halftone dot data 160 (step S64).

  The image compression method and the decompression method according to the second embodiment may be modified as described below, and may be applied when the image data 150 does not include any printing halftone dots.

  First, similarly to the image compression method and the decompression method of the second embodiment described above, the image data 150 is binarized (step S51), and further, the difference between the image data 150 and the binary data 151 is calculated and calculated. Value data 152 is generated. At this time, the image indicated by the multi-value data 152 does not include printing halftone dots.

  In this case, after a halftone dot is generated from the image indicated by the multilevel data 152, the multilevel data 152 is compressed by a printing halftone compression algorithm. First, the gradation at each position of the image indicated by the multi-value data 152 is calculated. Further, halftone dots having an area proportional to the gradation of the position are generated at each position of the image. Based on the position and area of the halftone dot, the multi-value data 152 is compressed by the print halftone compression algorithm, and the print halftone compression data module 154 is generated. Further, the batch compression data module 156 is generated by integrating with the line drawing compression data module 155.

  When the batch compressed data module 156 generated in this way is restored, the image indicated by the restored image data 160 to be restored includes halftone dots that were not included in the image indicated by the original image data 150. ing.

  In this case, the print halftone dot temporary data 157 indicating an image composed of halftone dots is converted into image temporary data that is not an image composed of halftone dots and then combined with the binary temporary data 158. Is possible. The image temporary data is generated as follows. First, the positions and areas of the halftone dots included in the print halftone temporary data 157 are recognized. An image is generated in which a region in the vicinity of a position where a halftone dot exists is filled with a gradation corresponding to the area of the halftone dot. Data indicating the image is generated as image temporary data.

  In the restored image data 160 generated from the image temporary data and the binary temporary data 158 generated in this way, the original image that does not include a halftone dot is almost restored.

  Restoring the restored image data 160 so as not to include halftone dots is effective when it is desired to prevent the occurrence of moire.

  In the image data compression method and decompression method of the present embodiment, image data is classified into image elements and extracted, as in the first embodiment. Further, each image element is compressed and decompressed with a corresponding algorithm. As a result, the compression rate is improved, and further, deterioration of image quality due to compression and decompression is suppressed.

  Furthermore, in the image data compression method and decompression method of the present embodiment, halftone dots are generated from an image that does not include halftone dots. Further, a halftone dot vector is generated from the halftone dots. Redundancy of halftone dots is effectively utilized. Thereby, the compression rate is improved.

  Note that the image data compression method and decompression method of the present embodiment can also compress and decompress a color image, as in the first embodiment. In this case, as in the first embodiment, color image data indicating a color image is separated, and separated image data is generated for each color. Each of the separated image data is compressed and restored by the same method as the image data compression method and restoration method of the present embodiment.

1: Scanner 2: CPU
3: Storage device 4: Recording medium 5: Bus 10: Hardware resource 11: Input unit 50: Paper image data 51: Free fine dot image element data 52: Print halftone dot image element data 53: Line drawing image element data 54: Free Fine dot compression data module 55: Print halftone dot compression data module 56: Line drawing compression data module 57: Batch compression data module 58: Free fine dot temporary data 59: Print halftone dot temporary data 60: Line drawing temporary data 61: Restored image data 62 : Color paper surface image data 70: Target area 71: Area patch 72: Small area 73: Image element 81, 101: Halftone dot 82, 102: Screen line

Claims (7)

Acquires image data indicating an image including printing halftone dots arranged according to a printing rule, and free fine dots that are points arranged not according to the printing rule and having an area in a predetermined area range To do
Separating the printing halftone dots and the free fine dots contained in the image of the image data;
An image data compression method comprising: generating free fine-point compressed data obtained by compressing an image portion corresponding to the free fine point based on the position of the free fine point,
Generating the free fine-point compressed data includes:
Defining a rectangular region including the free fine dots in the image;
An image data compression method comprising: generating the free thin-point compression data based on an average value of density inside the rectangular region. Acquires image data indicating an image including printing halftone dots arranged according to a printing rule, and free fine dots that are points arranged not according to the printing rule and having an area in a predetermined area range To do
Separating the printing halftone dots and the free fine dots contained in the image of the image data;
An image data compression method comprising: generating free fine-point compressed data obtained by compressing an image portion corresponding to the free fine point based on the position of the free fine point,
Generating the free fine-point compressed data includes:
Defining a rectangular region including the free fine dots in the image;
An image data compression method comprising: generating the free fine dot compressed data based on a distance between a side of the rectangular area and the free fine dot. Acquires image data indicating an image including printing halftone dots arranged according to a printing rule, and free fine dots that are points arranged not according to the printing rule and having an area in a predetermined area range To do
Separating the printing halftone dots and the free fine dots contained in the image of the image data;
An image data compression method comprising: generating free fine-point compressed data obtained by compressing an image portion corresponding to the free fine point based on the position of the free fine point,
Generating the free fine-point compressed data includes:
Defining a rectangular region including the free fine dots in the image;
Recognizing the shape of the pattern of the portion included in the rectangular region of the free fine dots;
An image data compression method comprising: encoding the shape to generate the free fine dot compressed data. The image data compression method according to any one of claims 1 to 3,
The image data compression method, wherein the free thin dots have an area larger than an area of the printing halftone dot. On the computer,
Acquires image data indicating an image including printing halftone dots arranged according to a printing rule, and free fine dots that are points arranged not according to the printing rule and having an area in a predetermined area range And the steps to
A procedure for separating the printing halftone dots and the free fine dots contained in the image of the image data;
A computer-readable recording medium storing a program for executing a procedure for generating free fine-point compressed data in which an image portion corresponding to the free fine point is compressed based on the position of the free fine point, ,
The procedure for generating the free fine dot compressed data is as follows:
A procedure for defining a rectangular region including the free fine dots in the image;
A procedure for generating the free thin-point compressed data based on an average density value inside the rectangular area. On the computer,
Acquires image data indicating an image including printing halftone dots arranged according to a printing rule, and free fine dots that are points arranged not according to the printing rule and having an area in a predetermined area range And the steps to
A procedure for separating the printing halftone dots and the free fine dots contained in the image of the image data;
A computer-readable recording medium storing a program for executing a procedure for generating free fine-point compressed data in which an image portion corresponding to the free fine point is compressed based on the position of the free fine point, ,
The procedure for generating the free fine dot compressed data is as follows:
A procedure for defining a rectangular region including the free fine dots in the image;
A recording medium including a procedure for generating the free fine dot compressed data based on a distance between a side of the rectangular area and the free fine dot. On the computer,
Acquires image data indicating an image including printing halftone dots arranged according to a printing rule, and free fine dots that are points arranged not according to the printing rule and having an area in a predetermined area range And the steps to
A procedure for separating the printing halftone dots and the free fine dots contained in the image of the image data;
A computer-readable recording medium storing a program for executing a procedure for generating free fine-point compressed data in which an image portion corresponding to the free fine point is compressed based on the position of the free fine point, ,
The procedure for generating the free fine dot compressed data is as follows:
A procedure for defining a rectangular region in the image;
Recognizing the shape of the pattern of the portion included in the rectangular region of the free fine dots;
A procedure for encoding the shape and generating the free thin-point compressed data.

Images