JP2003338934A - Image processing equipment and method therefor - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide image processing equipment wherein image is compressed effectively while picture quality is maintained, and to provide its method. <P>SOLUTION: In image compression processing, region dividing is performed to a color document image, a binary MMR compression code is used for a latter region part, and a JPEG compression code is used for a substratum part extracting letters. Data are obtained wherein information regarding both of the latter region and the substratum, region position information and latter color information are synthesized, so that high compression ratio is obtained while picture quality is maintained to be high. In the processing, a quantization table in the case of producing the JPEG compression code is changed in accordance with areas of a letter region and a not-latter region of an original document image. <P>COPYRIGHT: (C)2004,JPO

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image processing apparatus and method.

[0002]

2. Description of the Related Art In recent years, the spread of scanners has promoted the digitization of documents. If you try to store a digitized document in full color bitmap format, for example: In the case of A4 size, 300 dpi requires about 24 Mbytes, which requires a huge amount of memory. Such a large amount of data cannot be said to have a size suitable for being attached to a mail and transmitted. Therefore, compression of a full-color image is usually performed, and JPEG is known as a compression method thereof. JPEG is very effective in compressing a natural image such as a photograph, and has good image quality. On the other hand, however, when a high frequency portion such as a character portion is JPEG-compressed, image deterioration called mosquito noise occurs and the compression rate is poor. Therefore, the JP of the background part is extracted by dividing the area and removing the character area.
There is a method in which EG compression and MMR compression of a character area portion with color information are created, and when decompressing, a white portion transmits a JPEG image and a black portion is represented by a representative character color.

Further, in order to realize a high compression rate without degrading the image quality as much as possible, there is a technique for changing the background resolution depending on the magnitude of the high frequency component remaining in the image background.

[0004]

However, in the above method, since the entire base image is uniformly reduced by the resolution conversion, there is a possibility that information may be excessively reduced even in a portion having a relatively high frequency component. .

In fact, in order to efficiently create / display an electronic image, it is preferable that the resolution conversion is performed at an integer magnification. Therefore, the size of the background image can be roughly changed, and it is difficult to flexibly deal with a case where a balance between image quality and compression rate is required.

The present invention has been made to solve the above-mentioned problems of the prior art, and an object of the present invention is to provide an image processing apparatus and method for efficiently compressing an image while maintaining the image quality.

[0007]

In order to achieve the above object, an apparatus according to the present invention comprises an extracting means for extracting a character area from multi-valued image data and generating position data of the character area, and the character area. Binarizing means for binarizing the multivalued image data to generate character area binary image data, color calculating means for calculating a representative color of the character area and generating character color data, Using the multi-valued image data of the area
Conversion means for converting the multi-valued image data of the character area to generate multi-valued image data without characters, and resolution conversion means for reducing the resolution of the multi-valued image data without characters to generate reduced multi-valued image data without characters. A first compression means for compressing the reduced character-less multi-valued image data and a second compression means for compressing the character area binary image data, wherein the first compression means It is characterized in that the quantization table for JPEG compression is changed according to the area of the region.

[0008]

BEST MODE FOR CARRYING OUT THE INVENTION Preferred embodiments of the present invention will be illustratively described in detail below with reference to the drawings. However, the constituent elements described in this embodiment are merely examples, and the scope of the present invention is not intended to be limited thereto.

FIG. 1 shows a block diagram of a first embodiment of the present invention.

Reference numeral 101 denotes a character area detection unit which detects a character area from an input original image and creates coordinates 109 of a plurality of character areas. Reference numeral 102 denotes a binarization unit that inputs the above-mentioned character area coordinates and creates a binary image 108 of the character area portion of the original image. Reference numeral 103 denotes a color calculation unit that calculates the representative color 110 of the black portion with reference to the black portion of the binary image and the original image. Reference numeral 104 denotes a character portion filling portion that extracts the area of the binary image (black) from the original image and creates a filled image A with the surrounding color. Reference numeral 105 denotes a reduction unit that inputs the image A and reduces it to create the image B. 106 is image B
Is input and JPEG compressed to create a compression code C (112). A plurality of compression codes D (1
12) is an MMR compressing unit for producing. Finally, the data from 109 to 112 surrounded by the broken line are combined to form the compressed data.

FIG. 3 is a flow chart for explaining the processing in the character area detecting section.

In step S301, a color image is input, luminance conversion is performed while thinning to reduce the resolution, and a luminance image J is created. For example, the original image is RGB 24-bit 3
If it is 00 dpi, Y = 0.299R + 0.587G + 0.114B is calculated for every four pixels in the vertical and horizontal directions, and when a new image J is created, the image J becomes an image of Y8 bits 75 dpi. In step S302, the histogram of the brightness data is taken and the binarization threshold value T is calculated. Next, in step S303, the luminance image J is binarized by T to create a binary image K. Further, in step S304, contour lines of black pixels are traced to label all black regions. Next, in step S305, a character-like area in the black area is determined. In step S306, shapes and positions to be combined are combined.

An example is shown. For example, the color original shown in FIG. 4 is input, and the histogram of the thinned and converted luminance is obtained as shown in FIG. Average from this histogram,
A threshold value T = 150 is calculated using data such as variance, and the binarized image is as shown in FIG. If the contour lines of the black pixels in FIG. 6 are traced and all are labeled and, for example, only the collection of black pixels whose width is less than or equal to the threshold value or height is less than the threshold value is allowed as characters, the collection of black pixels shown in FIG. It becomes a character area (it is an image, not such an image is actually created).

When these groups of black pixels are grouped according to the closeness of positions, the width and height, 17 character areas as shown in FIG. 8 can be detected. These coordinate data are stored in 109 of FIG.

In the above process, the color image is not binarized, but a differential filter is applied, edge amounts of all pixels with neighboring pixels are calculated, and the edge amounts are binarized. The obtained binary image may be similarly contour-tracked to detect the character region.

The binarization unit 102 creates a binary image of 17 character areas obtained by the above method. This binary image may be binarized by, for example, T calculated by the character area detection unit, or a histogram may be taken for each area to calculate an optimum binarization threshold for the character area. . As compared with the histogram of the entire surface shown in FIG. 5, the luminance histogram of a part of the character area can be expected to have a simple shape as shown in FIG. 9, so that the threshold value can be easily determined. 90
Reference numeral 1 is a set of base colors, and 902 is a set of character colors.

An example of the processing of the character portion filling portion 104 using the binarization result will be described with reference to FIGS. 10 and 11.

An image as shown in FIG. 10A in which a blue character ABC is drawn near the center with a gradation image as a background is an original image. It is assumed that a binary image of one character area as shown in (b) is obtained from this original image. In the present embodiment, the entire image is a 32 × 32 area (hereinafter, parts)
Divide into and process each part. Figure 10 (c)
Shows how the parts are divided. For the sake of simplicity, this figure shows a state of being divided into 5 × 4 parts. The number on the upper left of each area shows the part number. When divided in this way, parts 00-04,10,14,2
Nos. 0, 24, 30 to 35 are determined to have no character area in step S1103, and thus no processing is performed,
Go to the next part. Step S for parts 11
Proceeding to 1104, the corresponding binary image is referenced, and the RGB value (or YU) of the color image corresponding to the white part of the binary image (or YU
The average value ave_color of V) may be calculated. Next, in step S1105, the corresponding binary image is referred to, and the density data of the pixel corresponding to the black pixel is set as the ave_color.

The above processing is performed for a part 1 having a character area.
Repeat steps 2, 13, 21, 22, 23.

In this way, the pixel having the character can be filled with the average value of the pixels around the portion having the character, and the image A in which only the character is apparently removed naturally is generated. .

On the other hand, FIG. 12 shows an example of a character color calculation unit utilizing the above binarization result. Although the result of the partial binarization result 108 is used in the present embodiment, the present invention is not limited to this. For example, only the coordinates of the character region and the color image are input, and the color calculation process is performed using the result of binarizing the color image again. You may go. Since processing is performed for all the extracted character areas, it is checked in step S1201 whether or not there is an unprocessed character coordinate, and if there is, it proceeds to step S1202, and if there is none, it proceeds to end. Step S1202
The thinning process of the binary image referred to by the character coordinates is performed to reduce the black corresponding to the changing portion from the background to the character portion at the time of reading by the scanner, and a new binary image newbi is created. Next, in step S1203, a histogram of each value of RGB of the original image corresponding to the black pixel of newbi is obtained (of course, another color space such as YUV may be used). In step S1204, representative values of RGB are calculated. For example, it may be the largest value. Alternatively, the number of steps of the histogram may be reduced to obtain the largest value in the rough histogram, and then the largest value in the fine histogram existing in this histogram may be obtained. By repeating the above process for all the character coordinates, one representative color is calculated for all the character coordinates.

At 107, each of the partial binary images 108 is MMR compressed to create a compressed code D.

In the case of 105, an image A in which characters are filled
Then, the resolution is converted to generate image B. This is based on the general principle that the various information such as images, photographs, backgrounds, and decorations that remain without the characters require a higher resolution than the characters. Here, the size is uniformly reduced by 1/2, but depending on the required image quality and the size of the final generated image, it may be reduced to 1/4 or may be left as 1/1 without being reduced. .

Next, at 106, J is applied to the reduced image B.
PEG compression is performed to create a compression code C.

A general JPEG compression process is used. Briefly, divide the image into each component of YUV,
A DCT transform is performed for each small area (for example, 8 × 8 pixels), and the obtained transform coefficient is quantized and encoded to obtain a compressed code.

In the above quantization, each coefficient of DCT transformation is converted into
It is performed by dividing each corresponding term of the quantization table as shown in 3 and truncating the remainder below the decimal point. That is, the larger the value of each element of the quantization table, the coarser the quantization becomes, and the amount of information is reduced, but a high compression rate is obtained.

In the present embodiment, the content of the image, specifically, the ratio of the total area m of the black pixel set which is considered to be the character and the total area p of the other black pixel set in S305 of FIG. The quantization table is changed according to the value of p / (m + p).

As an example, when p / (m + p) is 0.1 or more, the compression rate is increased by using a quantization table having a large value. When it is less than 0.1, the compression rate is reduced by using a quantization table having a small value.

In the latter case, m >> p, most of the image area is a character area, and the area on image B is flattened by character filling. High compression ratio can be obtained. On the other hand, in the area other than the remaining characters, perhaps in the area of a picture or a picture, the loss of information amount is reduced and the image quality is improved due to the quantization table having a small value. On the other hand, although the compression rate also decreases, the total area of the corresponding portion is small, so that the compression code size of the entire image can be prevented from significantly increasing.

Needless to say, the relationship between the character and non-character areas and the quantization table setting is not limited to the above example, p / (m + p) is divided into n stages (n> 2), and each is quantized. The conversion table may be set. The quantization table may be determined from the value of p / m instead of p / (m + p) or the area of p alone.

Further, the magnitude of the compression rate may be determined in consideration of the final target value of the total compression code amount. For example,
For the relationship between the area of the non-character area and the size of the code after compression, we determined in advance the experiment for multiple quantization tables, and during the actual processing, the binary image compression code of the character part obtained earlier The optimum quantization table may be selected based on the difference between the size of D and the target total size.

Finally, if necessary, a format in which the four character region coordinates (109), the character part representative color (110), the compression code C (111), and the compression code D (112) are put together is created.

The format may be PDF or XML.

FIG. 2 shows a block diagram at the time of expansion.

A compressed code C is input to 201, and JPEG is input.
This is a JPEG decompression unit that performs decompression processing and creates a multi-valued image E. Reference numeral 202 denotes an MMR decompression unit that inputs a compression code and creates a binary image F. 203 inputs the multi-valued image E,
An enlargement unit that enlarges and creates an image G. Reference numeral 204 is an image for inputting coordinates of a character area and a representative color, selecting the image G for the white portion and the representative color for the black portion while referring to the binary image F, and creating an image H207 as a final image. It is a united part.

FIG. 14 shows an example of the result of the merge processing 204.
First, FIG. 14A shows a JPEG decompression result of the compressed code C. When the quantized lossy method of JPEG compression is used, the pixel values are slightly different from those in FIG. 10C. However, compared to the case where the original image before the character part is removed is compressed by the JPEG lossy compression method, the pixel value changes less when the same quantization table is used. By referring to the binary image (b), representative color (20, 30, 255) data is placed on the image (a) corresponding to the black pixel, and finally an image as shown in (c) is completed. This becomes the expanded image 207.

As described above, according to the present invention, it is possible to realize an image processing apparatus which efficiently compresses an image while maintaining the image quality.

[Other Embodiments] In the first embodiment, when the quantization table is selected, the focus is mainly on the area of the non-character region of the pre-compression image. The quantization table may be selected by paying attention to.

For example, in a document image including a table,
When a pixel group regarded as a table ruled line is extracted from non-character pixels, a quantization table having a small value is used for compression applied to the image B.

As a result, the noise generated around the line portion is reduced and the image quality is improved. On the other hand, although the compression rate decreases, the part where the ruled line exists is sparse compared to the area of the entire table, so the overall compressed code size does not increase significantly.

It is to be noted that a known area division algorithm is used for determining whether the pixel is a table ruled line pixel in the above description, and a description thereof will be omitted here.

Even in this case, it is possible to realize an image processing apparatus which efficiently compresses an image while maintaining the image quality.

(Other Embodiments) Although the embodiments of the present invention have been described in detail above, the present invention may be applied to a system including a plurality of devices, and an apparatus including one device. May be applied to.

The present invention supplies a software program for realizing the functions of the above-described embodiments to a system or apparatus directly or remotely, and a computer of the system or apparatus reads the supplied program code. Including cases that can be achieved by executing. In that case, the form need not be a program as long as it has the functions of the program.

Therefore, the program code itself installed in the computer to implement the functional processing of the present invention by the computer also implements the present invention. That is, the claims of the present invention include the computer program itself for realizing the functional processing of the present invention.

In this case, the program may take any form such as an object code, a program executed by an interpreter, or script data supplied to an OS as long as it has the function of the program.

As a recording medium for supplying the program, for example, a floppy (registered trademark) disk, hard disk, optical disk, magneto-optical disk, MO, CD
-ROM, CD-R, CD-RW, magnetic tape, non-volatile memory card, ROM, DVD (DVD-ROM,
DVD-R).

In addition, as a program supply method,
It can also be supplied by connecting to a homepage on the Internet using a browser of a client computer, and downloading the computer program itself of the present invention or a compressed file having an automatic installation function from the homepage to a recording medium such as a hard disk. It can also be realized by dividing the program code constituting the program of the present invention into a plurality of files and downloading each file from different homepages. That is, a WWW server that allows a plurality of users to download a program file for implementing the functional processing of the present invention on a computer is also included in the claims of the present invention.

The program of the present invention is encrypted to C
By storing the information in a storage medium such as a D-ROM and distributing it to the user, and having the user who satisfies the predetermined conditions download the key information for decrypting the encryption from the home page via the Internet, and by using the key information It is also possible to execute the encrypted program and install the program in a computer to realize it.

Further, the computer executes the read program to realize the functions of the above-described embodiments, and the OS and the like running on the computer execute the actual processing based on the instructions of the program. The function of the above-described embodiment can be realized also by performing a part or all of the above.

Furthermore, after the program read from the recording medium is written in the memory provided in the function expansion board inserted into the computer or the function expansion unit connected to the computer, based on the instructions of the program,
CPU provided on the function expansion board or function expansion unit
Performs a part or all of the actual processing, and the processing realizes the functions of the above-described embodiments.

[0052]

According to the present invention, a color document image is divided into areas, a character area portion is a binary MMR compression code, and a background portion without characters is a JPEG compression code. In the image compression processing that obtains a high compression rate while maintaining high image quality by combining the area position information and the character color information, the quantization table at the time of JPEG compression code generation is set to the character / non-character area of the original document image. More flexible image quality by changing according to the area of
It is possible to realize an image processing device that can achieve both compression rates.

[Brief description of drawings]

FIG. 1 is a block diagram of a compression device according to a first embodiment of the invention.

FIG. 2 is a block diagram of a decompression device according to the first embodiment of the invention.

FIG. 3 is a flowchart showing processing of a character area detection unit according to the first embodiment of the invention.

FIG. 4 is a diagram showing an example of an original image for explaining a character area detection process according to the first embodiment of the invention.

FIG. 5 is a diagram showing a histogram for explaining a character area detection process according to the first embodiment of the invention.

FIG. 6 is a diagram showing an example of a binary image for explaining a character area detection process according to the first embodiment of the invention.

FIG. 7 is a diagram showing an example of a character area image for explaining the character area detection processing according to the first embodiment of the invention.

FIG. 8 is a diagram illustrating an example of a character area portion for explaining a character area detection process according to the first embodiment of the invention.

FIG. 9 is a diagram showing an example of a histogram result of a character area input to the binarization unit 109 according to the first embodiment of this invention.

FIG. 10 is a diagram illustrating a character part filling process according to the first embodiment of this invention.

FIG. 11 is a flowchart illustrating a character part filling process according to the first embodiment of this invention.

FIG. 12 is a flowchart for explaining processing of a color calculation unit according to the first embodiment of the invention.

FIG. 13 is a diagram showing an example of a quantization table of a JPEG compression processing unit according to the first embodiment of the invention.

FIG. 14 is a diagram showing an example of a result of a combination process according to the first embodiment of the invention.

─────────────────────────────────────────────────── ─── Continued Front Page (51) Int.Cl. ⁷ Identification Code FI Theme Coat (Reference) H04N 1/40 H04N 1/40 FF Term (Reference) 5B057 CA01 CA08 CA16 CB01 CB08 CB16 CD05 CE12 CE16 CG01 CH07 DA08 DB06 DB09 DC23 DC25 5C076 AA21 AA22 BA06 5C077 MP08 PP27 PP28 PP32 PQ19 PQ23 RR02 RR21 5C078 BA27 BA57 CA02 CA21 CA27 DA02 5L096 AA02 FA06 FA37 FA44 GA34

Claims (8)

[Claims] 1. A character area is extracted from multi-valued image data,
Extraction means for generating position data of the character area, binarization means for binarizing the multi-valued image data of the character area to generate character area binary image data, and calculation of a representative color of the character area Then, the color calculating means for generating the color data of the character and the converting means for converting the multivalued image data of the character area by using the multivalued image data of the area other than the character to generate the multivalued image data without character. A resolution conversion means for reducing the resolution of the characterless multi-valued image data to generate reduced characterless multi-valued image data; a first compression means for compressing the reduced characterless multi-valued image data; An image processing apparatus comprising: a second compression unit that compresses the value image data. 2. The image processing apparatus according to claim 1, wherein the first compression unit complies with JPEG compression. 3. The image processing apparatus according to claim 1, wherein the second compression unit complies with MMR compression. 4. The image processing apparatus according to claim 1, wherein in the JPEG compression in the first compression means, a quantization table for performing quantization is variable. 5. The image processing apparatus according to claim 1, wherein the quantization table is selected according to the areas of the character area and the non-character area obtained by the character area extracting unit. 6. The quantization table is selected from the areas of the character area and the non-character area and the target compression size obtained by the character area extracting means.
The image processing device according to item 1. 7. The image processing apparatus according to claim 1, wherein the quantization table is selected according to the shape of the non-character area obtained by the character area extracting means. 8. An image processing apparatus for decompressing an image compressed by the image processing apparatus according to claim 1, wherein the image is compressed by the first compression unit. A first decompression unit for decompressing the reduced character-less multivalued image data, a second decompression unit for decompressing the character region binary image data compressed by the second compression unit, and a reduced characterless multivalued image data A resolution conversion unit for increasing the resolution to generate the characterless multi-valued image data, the position data and the color data are input, and the multi-valued image is obtained from the character area binary image data and the characterless multi-valued image data. An image processing device, comprising: an image merging unit that generates data.