JPH07288679A - Image processing unit - Google Patents

Abstract

PURPOSE:To segment an area and to discriminate the attribute of the area with a small memory capacity at a high speed accurately by discriminating the attribute of each block based on picture element data belonging to each block and discriminating the attribute of the area larger than the block through the use of the discriminated attribute of each block. CONSTITUTION:An image sensor of an image input section 10 reads an original image for each picture element and stores it to a matrix memory 12 via a line buffer 11. Then an original image is divided into blocks of a prescribed size and a characteristic quantity specific to each block is calculated respectively by a dot detection section 13, a MAX-MIN detection section 14 and an average density detection section 15 to discriminate the attribute such as dot, photograph, character and background. After the attribute of each block is decided, a selection section 17 selects a dot block and a photograph block and they are respectively stored in dot/photograph map memories 18, 19. Then an area decided by area rectangular processing sections 22, 23 is segmented and stored in position storage memories 24, 25.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention is used in a device for processing read image data such as a facsimile and a digital copying machine. More specifically, a character portion in one screen,
The present invention relates to an image processing device used for processing image data in which a photograph portion, a halftone portion, and the like are mixed.

[0002]

2. Description of the Related Art Conventionally, in a facsimile or the like, when a document is a text document, image processing suitable for a character is performed, and when it is a photo document, image processing suitable for a photograph is performed and the original document is transmitted. Even so, reproducibility close to that of the original document has been obtained. However, when characters and photographs are mixed in one original image, it is difficult to perform corresponding image processing on the characters and photograph areas.

As a solution to this problem, Japanese Unexamined Patent Publication No. Sho 6-96
There are conventional techniques such as 1-289764 and JP-A-3-126180. In order to perform image processing corresponding to each attribute such as characters and photos, these processes determine in advance which part of the document contains the character and which part contains the photo, that is, the process of cutting out image areas with the same attributes. The application is disclosed. Japanese Patent Laid-Open No. 61-2897
No. 64 is intended for a facsimile, and the image data to be processed is binary data. Then, the region is cut out using the run length of the binary data. Japanese Unexamined Patent Publication (Kokai) No. 3-126180 is to optimally binarize input image data, and cut out an information area from the binarized data by a circumscribed rectangle. Further, the attribute is determined based on the number of inversions from black pixels to white pixels in the area.

[0004]

However, in these conventional techniques, since the data to be processed at the time of cutting out an area or discriminating the attribute is pixel data of the entire original image, it takes a very long time to perform the processing. However, there is a drawback that a large amount of memory is required. In addition, the latter one has a defect that the amount of information is lost due to the optimum binarization and the discrimination rate is lowered. The present invention aims to eliminate the above drawbacks. That is, it is an object of the present invention to provide an image processing apparatus capable of accurately cutting out a region and discriminating an attribute of the region with a small amount of memory at high speed.

[0005]

To achieve the above object, the image processing apparatus of the present invention is an image processing apparatus for processing an image based on pixel data obtained by reading an original image for each pixel. The original image is divided into predetermined blocks, and the first discriminating means for discriminating the image attribute of each block based on the pixel data of a plurality of pixels included in each block, and a region larger than one block. A second discriminating means for discriminating the attribute of this area according to the attributes of the plurality of blocks included therein is provided. The first determining means may calculate predetermined information from pixel data of a plurality of pixels included in each block, and determine the image attribute for each block based on the calculation result.

The image processing apparatus of the present invention is an image processing apparatus that processes an image based on pixel data obtained by reading an original image for each pixel, and divides the original image into predetermined blocks. A determination unit that determines the attribute of the image for each block based on pixel data of a plurality of pixels included in each block, and a cutout unit that cuts out a region where blocks having the same attribute are collected are provided. Furthermore, after detecting a block having an attribute different from the attribute of the surrounding block and converting the attribute of the detected block based on the attribute of the surrounding block, a region in which blocks with the same attribute are collected is cut out. do it.

[0007]

With the above structure, the attribute of each block is determined based on the pixel data belonging to each block. Next, the attributes of the blocks that are larger than the blocks are determined using the determined attributes of each block. Further, after the attributes of each block are determined, an area in which blocks having the same attributes are collected is cut out. Furthermore, after the block attributes are determined, the determination result is confirmed again, and if the process is performed after the attributes of the blocks that are considered to be erroneous determinations are changed, an area in which blocks with the same attribute are gathered more accurately Is cut out.

[0008]

EXAMPLES Examples of the present invention will be described below. FIG. 1 is a block diagram showing the configuration of an image processing apparatus to which the present invention is applied. Although each processing unit is described in this block diagram, the processing in each processing unit is executed by a CPU (central processing unit) or the like (not shown).
First, in the image input unit 10, for example, CCDs (Charge Coupled Devic) arranged in a line in the main scanning direction are arranged.
The original image is read pixel by pixel by the image sensor such as e). The read pixel data is input to the line buffer 11 for each line in the main scanning direction and then stored in the matrix memory 12. Then, the sub-scanning of the document is sequentially advanced so that all pixel data of the document is stored in the matrix memory 12. The pixel data is usually represented by 256 gradations (8 bits). And
In subsequent processing blocks, the pixel data stored in the matrix memory 12 is processed, and the document image is classified into attributes such as a halftone dot area, a photograph area, a character area, and a background area. The halftone dot area is an image area represented by halftone dots like a photograph in a newspaper, and the photo area is
An image area smoothly expressed by halftone density, a character area is an area mainly composed of characters expressed in two gradations, and a background area is an area having the same color as the background color of the document. . Then, in the present embodiment, the halftone dot area and the photograph area are cut out from the original image and distinguished from the other areas. Further, in the subsequent processing, as shown in FIG. 2, the document is virtually divided into blocks each having a size of 8 × 8 pixels, and the processing proceeds in block units. It should be noted that the size of the block is not limited to 8 × 8 pixels, and may be any other suitable size (m × n pixels).

First, in order to discriminate the attribute (halftone dot, photograph, character, background) of each block, the feature amount peculiar to each block is the halftone dot detecting section 13, MAX-MIN detecting section 14, average density detection. It is calculated by each of the units 15. Halftone dot detector 13
3 counts the isolated points existing in each block. For all the pixels (64 pixels) in each block, FIG.
The process for applying the isolated point count filter is performed. That is, the isolated point count filter is operated 64 times for one block, and the number of pixels satisfying the following discriminant is output as the halftone dot value N. X> max (n1, n2, n3, n4) or X <min (n1, n2, n3, n4) Since the outermost block of the document can be operated by this isolated point count filter, The halftone dot value N of the block is set to 0. The MAX-MIN detection unit 14 looks at the distribution of pixel densities in each block, and the density difference D between the maximum density pixel and the minimum density pixel in each block is calculated. Then, the average density detector 15 calculates the average density A of 64 pixels in order to detect the density of each block.

As described above, three data (halftone dot value N, density difference D, average density A) are derived for all blocks in the document. The determination unit 16 determines the attribute of each block by using these data. As a determination procedure, first, a halftone dot block is determined. This is because the halftone dot image is the most characteristic image among the attributes and can be determined with high probability only by the halftone dot value N (in the determination based on the density difference D, the determination of the halftone dot and the character). Cannot be done). After the halftone dot block, the character block is determined. Since the character block is usually a black and white binary image, a block having a large density difference D is determined as a character block. Next, the photo block is determined. It is considered that the density difference D is not so large in the photo block,
If it is only this, it is indistinguishable from the background block, and therefore, a block in which the average density A is darker to some extent is also determined as a photographic block. After that, the remaining blocks are background blocks. However, the background block is
It is premised that the white or light color is usually present in the original document.

The above judgment can be summarized and expressed as the following judgment formula. However, T1 to T4 are predetermined threshold values. if N> T1 then halftone dot block else if D> T2 then character block else if D> T3 then photo block (T2> T
3) else if A> T4 then photo block else background block After the attributes of each block are determined as described above, the halftone dot block and the photo block are selected in the selection unit 17,
2 in each of the dot map memory 18 and the photo map memory 19
It is stored as a value map. That is, in the halftone dot map memory 18, “1” is assigned to the block determined as the halftone dot, and “0” is assigned to the other blocks. Further, in the photo map memory 19, “1” is assigned to a block determined to be a photo,
“0” is assigned to the other blocks.

Next, in the erroneously discriminant block correcting units 20 and 21, the block which is judged to be erroneous in the result judged by the judging unit 16, that is, a so-called noise block is corrected.
This correction is performed by checking the attributes of blocks around the block of interest, and if the attributes of the block of interest are far from the attributes of the blocks of interest, change the attributes of the block of interest to the surrounding attributes. In this embodiment, the smoothing process is performed using the filter shown in FIG. That is,
The filter of FIG. 4 is applied to the halftone dot map and the photographic map to which “0” and “1” are assigned, and when the central block value of interest is 5/9 or more, the block is set to “1” and 4 / If it is 9 or less, the block is corrected to be "0".

By the above processing, the halftone dot block and the photographic block are decided. After that, the block (block) of each block determined by the region rectangularization units 22 and 23 is cut out as a rectangle, and the position coordinates thereof are stored in the position storage memories 24 and 25. Less than,
A specific process in the halftone dot area rectangularization unit 22 will be described. Note that the processing regarding the photograph area is the same as the processing regarding the halftone dot area, and is therefore omitted.

FIG. 5A shows a halftone dot area (dots in the figure) in the halftone dot map. This halftone dot area is cut out in accordance with the processing of the flowchart of FIG. First, in step S1, a flag indicating that a halftone dot block is present in the scanning line is set to 0 (flag = 0 if not present, flag = 1 if present). Next, in step S2, scanning is performed line by line from the first line of the halftone dot map memory to check whether or not there is a halftone dot block in the line (step S2).
3). If a halftone dot block exists in the line and the flag is 0 (step S5), the flag is set to 1 in step S6.
And the current scanning line position is stored as the area start line.

Thereafter, line scanning proceeds, and step S3
Then, if a line in which a halftone dot block does not exist is detected and the flag is 1 (step S4), the position of the line one line before the current scanning line is stored as the region end line. As a result, the area surrounded by the area start line s1 and the area end line e1 is cut out as shown in FIG. After that, the scanning is advanced until the scanning line reaches the final line (step S11), and all the portions where the halftone dot areas are present are cut out. In addition, in FIG.
The second area (area start line s2 and area end line e
It is shown that it has been cut out up to the area surrounded by 2).

In the above cutting,
When the width of the cut out area (the length between the area start line and the area end line) is smaller than the predetermined length, the cut out area is regarded as a halftone dot block that has not been completely corrected (misclassified), Processing is performed so as not to cut out (steps S8 and S9). Next, the same processing as the processing of the flowchart of FIG. 7 is performed on each area cut out by the above processing, this time changing the scanning direction by 90 degrees. As a result, for example, the area start line s1 and the area end line e
As shown in FIG. 5B, an actual halftone dot area (area surrounded by lines s1, e1, s2, and e2) is cut out from the area surrounded by 1.

As a peculiar example, it is conceivable that the halftone dot areas in the document are arranged as shown in FIG. 6 (a). Even in such a case, the processing can be basically performed according to the flowchart of FIG. 7. That is, the same is applied to the regions (regions surrounded by the lines s1, e1, s'2, and e'2 in FIG. 6B) cut out as a result of performing the processing twice as described above. By further changing the scanning direction by 90 degrees (the same direction as the first time), the actual halftone dot area is cut out.

As described above, after the halftone dot area and the photograph area are cut out, they are combined and one bitmap is created by the composite bitmap forming unit 26. That is, each block has 2 bits, that is, the halftone dot block is "01",
Photo block is "10", other block is "00"
A bitmap is created as. Here, the other blocks correspond to the character block and the background block.
Treating the character block and the background block as the same can be seen as the background between the characters, and in the actual image processing that will be performed later, the background is not a problem regardless of what processing is performed. This is because it does not happen.

Using the bitmap of the finally created attribute block, that is, after grasping the attributes of each area in the original image, the actual pixel data stored in the matrix memory 12 is By performing processing suitable for each attribute, high image quality can be achieved and efficient image data compression can be performed.

In the above embodiment, the process of attribute discrimination and the like is performed after the pixel data for one screen is stored in the matrix memory 12, but the present invention is not limited to this. For example, without using a large-capacity matrix memory that can store pixel data for one screen,
A matrix memory that can store pixel data having a size (for example, 14 × 14 pixels) that can be applied to a 7 × 7 isolated point count filter may be used. In this case, the attribute of the corresponding block is determined in real time every time the pixel data of 14 lines × 14 columns is stored in the matrix memory, and the determination result is sequentially stored in the bitmap memory corresponding to each attribute.

However, in this case, the line buffer must have a capacity capable of storing at least 13 lines of pixel data. Further, when the attributes of the entire image are determined in this way, it is necessary to read the original image again at the stage of performing appropriate image processing on the actual pixel data using the result. As another method, it is possible to use a matrix memory capable of storing pixel data of about 1/4 of the original document for processing. In this case, if the image processing to be performed on the actual image data at the same time as the attribute determination and the region cutting processing is performed in the unit of 1/4 original, all the processing can be performed without rereading the original as described above. It will be possible.

[0022]

As is apparent from the above description, according to the present invention, image attribute determination is first performed in virtual block units, and thereafter, processing such as region extraction and attribute determination for that region is performed for each block. It uses attribute information. Therefore, the amount of data to be handled is very small, that is, the total number of blocks, so that the amount of memory used is very small and high-speed processing is possible. Further, since the attribute determination of each block is performed using each pixel data, the accuracy of the determination is sufficiently maintained. Further, the attribute of the block once discriminated is corrected again in consideration of the attributes of the surrounding blocks, so that the final attribute discrimination result becomes more accurate.

[Brief description of drawings]

FIG. 1 is a block diagram showing a configuration of an image processing apparatus of the present invention.

FIG. 2 is a diagram showing a document divided into blocks.

FIG. 3 is a diagram showing an isolated point count filter.

FIG. 4 is a diagram showing an erroneous discrimination extraction filter.

FIG. 5 is a schematic diagram showing a region to be cut out.

FIG. 6 is a schematic diagram showing a region to be cut out.

FIG. 7 is a flowchart showing a region cutting process.

Claims (4)

[Claims] 1. An image processing apparatus for processing an image based on pixel data obtained by reading an original image for each pixel, wherein the original image is divided into predetermined blocks, and pixels of a plurality of pixels included in each block are divided. First discriminating means for discriminating the attribute of the image for each block based on the data, and second discriminating means for discriminating the attribute of this area according to the attributes of a plurality of blocks included in an area larger than one block. An image processing apparatus comprising: 2. The first discriminating means calculates predetermined information from pixel data of a plurality of pixels included in each block, and discriminates an image attribute for each block based on the calculation result. 1. The image processing device according to 1. 3. An image processing apparatus for processing an image based on pixel data obtained by reading an original image for each pixel, wherein the original image is divided into predetermined blocks, and pixels of a plurality of pixels included in each block are divided. An image processing apparatus comprising: a discriminating unit that discriminates an image attribute for each block based on data; and a cutting unit that cuts out a region in which blocks having the same attribute are collected. 4. A detection means for detecting a block having an attribute different from an attribute of a surrounding block, and a conversion means for converting the attribute of the detected block based on the attribute of the surrounding block, The image processing apparatus according to claim 3, wherein the cutout unit cuts out an area in which blocks having the same attribute are collected after being converted by the conversion unit.