JP2002077633A - Apparatus and method of image processing - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an apparatus of image processing, a method of image processing capable of compressing images with efficiency along with keeping image quality, and its recording medium. SOLUTION: The apparatus comprises a character region detecting means 101 to produce character region coordinates 109 as positional data in the character region with extraction of the character region from multivalued image data, a binarizing part 102 to produce binary image data 108 by binarizing the multivalued image data in the character region, a color calculating part 103 to produce color data 110 of characters by calculating a typical color in the character region, a paint-out part 104 for character part to produce character-less multivalued image data A by converting the multivalued image data by using the multivalued image data in a region other than the character region, a reduction part 105 to produce a reduced character-less multivalued image data by reducing the resolution of the data A, a JPEG compression part 106 to perform JPEG compression for the reduced character-less multivalued image data and an MMR compression part to perform an MMR compression for binary image data in the character region.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

[0001] 1. Field of the Invention [0002] The present invention relates to an image processing apparatus and method, and a storage medium for implementing the method.

[0002]

2. Description of the Related Art In recent years, digitalization of documents has been advanced due to the spread of scanners. If you try to store a digitized document in full color bitmap format, for example. In the case of A4 size, it becomes about 24 Mbytes at 300 dpi, and the required memory becomes enormous. Such a large amount of data cannot be said to be a size suitable for being attached to a mail and transmitted. Therefore, full-color images are usually compressed, and JPEG is known as a compression method. JPEG is very effective for compressing natural images such as photographs, and has good image quality. On the other hand, when high-frequency portions such as character portions are JPEG-compressed, image degradation called mosquito noise occurs and the compression ratio is poor. Therefore, the area division is performed, and the JP of the background portion excluding the character area is performed.
There has been a method in which EG compression and MMR compression of a character area portion with color information are created, and at the time of decompression, a white portion is transmitted through a JPEG image and a black portion is represented with a representative character color.

[0003]

However, the compression ratio that can be realized while maintaining the image quality by the above method is not sufficient.

[0004] The present invention has been made to solve the above-mentioned problems of the prior art, and has as its object to provide an image processing apparatus, an image processing method, and a storage medium for efficiently compressing an image while maintaining image quality. And

[0005]

In order to achieve the above object, an apparatus according to the present invention extracts character regions from multi-valued image data and generates position data of the character regions; Binarizing means for binarizing the multi-valued image data to generate character area binary image data; color calculating means for calculating the representative color of the character area to generate 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 First compression means for compressing the multi-valued image data without reduced characters;
And second compression means for compressing the value image data.

[0006] Further, it is characterized in that it has a control means for controlling a resolution conversion parameter in the resolution conversion means.

When the non-character multi-valued image data is orthogonally transformed, the control means converts the non-character multi-valued image data having a small high frequency component into the character-less multi-valued image data having a large high frequency component. The resolution conversion parameter is controlled such that the resolution is converted to a lower resolution.

The control means applies a differentiation filter to the multi-valued image data without characters, and applies a high-frequency component having a large total number of absolute values to the multi-valued image data without characters having a small total number of absolute values. The resolution conversion parameter is controlled so that the resolution is converted to a lower resolution than the character-less multi-valued image data having a larger value.

[0009] The first compression means is based on JPEG compression.

[0010] The second compression means is based on MMR compression.

After the position data, the color data, and the outputs of the first and second compression means are combined, a third compression means for further compressing the data by a reversible compression method is further provided.

An image processing apparatus for expanding a compressed image by the image processing apparatus, wherein the first expansion means expands the multi-valued image data without reduced characters compressed by the first compression means; A second decompression means for decompressing the character area binary image data compressed by the second compression means, and a resolution for generating the character-less multivalued image data by increasing the resolution of the reduced character-less multivalued image data Conversion means, and image merging means for inputting the position data and the color data and generating the multi-valued image data from the character area binary image data and the character-less multi-valued image data, I do.

To achieve the above object, a method according to the present invention comprises the steps of: extracting a character region from multi-valued image data and generating position data of the character region; A binarizing step of binarizing character area data to generate character area binary image data; a color calculating step of calculating a representative color of the character area to generate character color data; Of the image data, using the data of the area other than the character, the data of the character area is converted, only the characters are deleted from the multi-valued image data, a conversion step of generating multi-valued image data without characters, A resolution converting step of reducing the resolution of the multi-valued image data without characters to generate reduced multi-valued image data without characters; a first compression step of compressing the multi-valued image data without reduced characters;
A second compression step of compressing the value image data.

In order to achieve the above object, a storage medium according to the present invention is a computer-readable memory storing a compression program for compressing multi-valued image data, wherein the compression program stores a character area from the multi-valued image data. A code of an extracting step of extracting and generating position data of the character area;
Codes of a binarization step of binarizing the data of the character area from the multi-valued image data to generate character area binary image data, and calculating a representative color of the character area, The code of the color calculation step of generating the, of the multi-valued image data, using the data of the area other than the character, the data of the character area is converted, only the character is deleted from the multi-valued image data, A code of a conversion step of generating multi-valued image data without characters, a code of a resolution conversion step of generating reduced multi-valued image data without characters by reducing the resolution of the multi-valued image data of non-characters, A code of a first compression step of compressing image data, a code of a second compression step of compressing the character area binary image data,
It is characterized by including.

[0015]

Preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings. However, the relative arrangement of components described in this embodiment, formulas, numerical values, etc., unless otherwise specified,
It is not intended to limit the scope of the present invention only to them.

(First Embodiment) FIG. 1 shows a configuration diagram of the present embodiment.

Reference numeral 101 denotes a character area detecting unit which detects a character area from the input original image and creates coordinates 109 of a plurality of character areas. Reference numeral 102 denotes a binarizing unit which receives the 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 while referring to the black portion of the binary image and the original image. Reference numeral 104 denotes a character portion filling portion for extracting a region of the binary image (black) from the original image and creating a filling image A with a surrounding color. Reference numeral 105 denotes a reduction unit that receives the image A and reduces the size of the image A to create the image B. 106 is image B
Is a JPEG compression unit for inputting and inputting JPEG and creating a compression code C (112). 107 inputs the plurality of binary images, performs MMR compression, and generates a plurality of compression codes D (1).
12) is an MMR compression unit that creates Finally, data 109 to 112 surrounded by a broken line are combined to form compressed data.

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

In step S301, a color image is input, luminance conversion is performed while reducing the resolution by thinning out, and a luminance image J is created. For example, if the original image is RGB 24-bit 3
If the resolution is 00 dpi, the calculation of Y = 0.299R + 0.587G + 0.114B is performed every four pixels in both the vertical and horizontal directions, and when a new image J is created, the image J becomes Y8
An image of bits 75 dpi is obtained. In step S302, a histogram of the luminance data is obtained, and a binarization threshold T is calculated. Next, in step S303, the luminance image J is binarized by T to generate a binary image K. Further, step S304
Traces the contours of black pixels and labels all black areas. Next, in step S305, a character-like area in the black area is determined. In step S306, objects to be combined from shapes and positions are combined.

An example will be described. For example, when the color original shown in FIG. 4 is input, the histogram of the thinned-out luminance data is obtained as shown in FIG. From this histogram the average,
The threshold value T = 150 is calculated using data such as variance, and the binarized image is as shown in FIG. When the contour tracing of the black pixels in FIG. 6 is performed and all are labeled, for example, if only a group of black pixels whose width is equal to or less than the threshold or whose height is equal to or less than the threshold is allowed as a character, the group of black pixels illustrated in FIG. It becomes a character area (an image is not actually created, but an image).

When these groups of black pixels are grouped based on the closeness of position, width, and height, 17 character regions as shown in FIG. 8 can be detected. These coordinate data are stored in 109 in FIG.

Rather than binarizing a color image, a binary filter obtained by applying a differential filter, calculating the edge amounts of all pixels with neighboring pixels, and binarizing the edge amounts is calculated. Similarly, contour lines may be traced on an image to detect a character area.

In the binarizing section 102, binary images of 17 character areas obtained by the above method are created. This binary image may be binarized using, for example, T calculated by the character area detection unit, or a histogram may be taken for each area to calculate an optimal binarization threshold value for the character area. . Compared to 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 form as shown in FIG. 9, so that the threshold can be easily determined. 90
1 is a set of background colors, and 902 is a set of character colors.

An example of the processing of the character part painting unit 104 using the above-described binarization result will be described with reference to FIGS.

An image as shown in FIG. 10A in which a gradation image is a background and a blue character of ABC is drawn near the center is as an original image. It is assumed that a binary image of one character area as shown in (b) is obtained from the original image. In the present embodiment, all images are stored in a 32 × 32 area (hereinafter, parts).
And perform processing for each part. FIG. 10 (c)
Fig. 3 shows the state of each part. This figure shows a state of being divided into 5 × 4 parts for simple explanation. The numbers at the upper left of each area indicate part numbers. When divided in this way, parts 00 to 04, 10, 14, 2
In steps 0, 24, and 30 to 35, since it is determined that there is no character area in step S1103, the processing is not performed, and
Proceed to the next part. Step S for part 11
Proceeding to 1104, referring to the corresponding binary image, the RGB values (or YU) of the color image corresponding to the white portion of the binary image
V, etc.) may be calculated. Next, in step S1105, the density data of the pixel corresponding to the black pixel is referred to as ave_color with reference to the corresponding binary image. The above processing is repeated for the parts 12, 13, 21, 22, 23 in which the character area exists.

In this way, it is possible to fill in the average value of the pixels around the portion where the character exists. This image is reduced by the reduction unit 105. In the present embodiment, simple thinning is performed. Incidentally, the order of the reduction and the character portion filling process may be reversed. In that case, it is necessary to pay attention to the displacement between the binary image and the color image.

On the other hand, FIG. 12 shows an example of a character color calculating section utilizing the above-mentioned binarized result. In the present embodiment, the result of the partial binarization result 108 is used. However, the present invention is not limited to this. May be performed. Since the process is performed for each of the extracted character areas, it is checked in step S1201 whether there is any unprocessed character coordinate. If there is, the process proceeds to step S1202, and if not, the process proceeds to end. Step S1202
Performs thinning processing of the binary image referred to by the character coordinates, and reduces black corresponding to a change from the background to the character portion when reading the scanner, thereby creating a new binary image newbi. Next, in step S1203, a histogram of the RGB values 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, a representative value of each of RGB is calculated. For example, the largest value may be used. Alternatively, a method may be used in which the number of steps in the histogram is reduced to obtain the largest value in a rough histogram, and then the largest value is obtained in a fine histogram existing in the histogram.

By taking the latter method, FIG.
A true representative value 1301 can be obtained from the histogram shown in FIG. To explain in detail using the figure, a 256-level histogram (shown in FIG. 13) can be obtained from 8-bit R data, for example, as a fine histogram.
Its maximum value is 1302, which is not a true representative value. Therefore, 64 overlapping histograms
, And recalculate the values of 8 levels from the histogram of 256 levels. It is shown from 0 to 8, where 0 and 8 are only 32 widths. By this recalculation, it is found that the representative value exists, and 1301 can be obtained by searching the maximum value. By repeating the above process for all character coordinates, a representative color is calculated for each character coordinate.

Finally, each of the partial binary images 108 is represented by M
MR compression to create a compression code D, and a reduced image B
The compression code C is created by performing JPEG compression using an appropriate quantization table. If necessary, a format in which the character area coordinates (109), the character part representative color (110), the compression code C (111), and the compression code D (112) are combined is created.

This format may be PDF or XML.

FIG. 2 shows a configuration diagram at the time of extension.

Reference numeral 201 denotes the input of a compression code C,
A JPEG decompression unit that performs a decompression process to create 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 a multi-valued image E,
This is an enlargement unit that creates an image G by enlarging. An image 204 for inputting the coordinates of the character area and the representative color, selecting the image G for the white part and selecting the representative color for the black part with reference to the binary image F, and creating the final image H207 It is a united part.

FIG. 14 shows an example of the result of the merging process 204.
First, FIG. 14A shows the result of JPEG expansion of the compression code C. When the quantization irreversible method of JPEG compression is used, the pixel value is slightly different from that of FIG. 10C. However, compared to the case where the original image before the character portion is extracted is compressed by the JPEG lossy compression method, the change in the pixel value is small when the same quantization table is used. Referring to the binary image (b), the representative color (20, 30, 255) data is placed on the image (a) corresponding to the black pixels, and finally an image as shown in (c) is completed. This is the expanded image 207.

As described above, according to the present embodiment, the low-frequency portion (mainly a natural image region) does not require much resolution but needs gradation, and the high-frequency portion (mainly a character region)
Utilizing the characteristics of the human eye that requires a high resolution but does not require much gradation, the compression ratio can be increased by lowering the resolution of the background image other than the character portion. For example, a compression ratio of 1/200 can be realized, attachment of e-mail does not hinder the network, image manipulation is light, and a high-quality image can be provided.

In this embodiment, only a partial character area is binarized by the binarization 102. However, the present invention is not limited to this. For example, the binary image used in the 101 character area detection may be used as it is. Is also good. In that case, the configuration is as shown in FIG.

The binary image used in the character part filling unit 104 and the color calculating unit 103 is based on the result of 108. However, the present invention is not limited to this. You may. In that case, the configuration is as shown in FIG.

Further, in the present embodiment, in the character area detecting section, those having similar shapes and positions are finally combined as shown at 306 in FIG. 3, but the present invention is not limited to this and may not be combined. In that case, the result of the image in FIG.
Since more than one character is extracted, the subsequent color calculation process can be performed in detail, so that, for example, when most of the 20 characters in one line are black and some are red, it is possible to cope with a change in color in detail.

Further, in the present embodiment, it is impossible to process a high-luminance character (inverted character) on a low-luminance base. However, for example, the configuration shown in FIG. 17 makes it possible. 1
Reference numeral 701 denotes a differentiation processing unit which applies a differentiation filter as shown in FIG. 18 to the center of the pixel of interest, and binarizes the image into black if the absolute value exceeds a threshold, and white if not. FIG. 18A shows a first-order differential filter. The upper part can detect a horizontal line, and the lower part can detect a vertical line. An oblique line can be detected by using the sum of the absolute values of the two filters. Further, an oblique line filter may be used. FIG. 18B shows a secondary differential filter corresponding to all directions. The second derivative filter can also be created in the horizontal direction and the vertical direction. Such a filter is applied to all pixels to create a differential binary image 1702.
At this time, it is also possible to reduce the resolution at the same time by applying a filter while thinning out the pixel instead of the previous pixel. If the processing from step 304 in FIG. 3 is performed on the binary image created as described above, the character area coordinates including the inverted character can be detected.

If inverted characters are also targeted, the binarizing unit 1703 must be compatible. In the case where the inverted character area is also extracted as a character area, in the present embodiment, it is assumed that only the pattern of FIG. 9 is included.
The multi-value data of three patterns as shown in FIG. (B) is a reversed character, and (c) is a case where two colors of a black character and a white character exist on the same gray base. Considering these three patterns, the binarization unit 1703
Now, point A and point B are detected, the area between A and B is white,
In other cases, it is preferable to perform black binarization processing. Or (c)
Without considering the case, it is only necessary to detect one threshold value that separates the background and the character portion, and perform the inversion process if the pattern is an inversion pattern.

As described above, if the reversed character area is also supported, JP
The inverted character area remaining in the EG-compressed image in the first embodiment is also smoothed by filling the character portion, so that the compression efficiency is good, and the inverted character portion is also improved without deteriorating the resolution or mosquito noise. It becomes possible to compress.

(Second Embodiment) In the first embodiment, the degree of reduction in the reduction unit 105 is fixed for all images. In this embodiment, however, the resolution conversion is performed as shown in FIG. A reduction parameter control unit 2001 for determining a reduction parameter (for example, a half, a quarter, etc.) is provided.

The reduction parameter control unit 2001 performs, for example, an orthogonal transformation on the entire surface of the image A every 8 × 8. 1, if it is less than the threshold, the reduction is 4
Adjust by a factor of one.

The reduction parameter is not limited to two levels, but may be, for example, three levels (half, quarter, not reduced). This has the effect of avoiding extreme reduction of the high frequency part and preventing image quality degradation.

In order to determine the reduction parameters, a method of applying a differential filter to the image and switching from the sum of the absolute values may be considered. In the case of this method, if the sum of the differences between adjacent pixel values is equal to or greater than the threshold value m, no reduction is performed, if n is equal to or more than n, 分 の, if less than n, ４.

According to the present embodiment, finer control of the resolution conversion can be performed, and the image quality can be further improved.

(Other Embodiments) The present invention relates to a system including a plurality of devices (for example, a host computer, an interface device, a reader, and a printer).
The present invention may be applied as a unit, or may be applied to a part of an apparatus including one device (for example, a copying machine or a facsimile machine).

Further, the present invention is not limited to only the apparatus and method for realizing the above-described embodiment, but includes a computer (CPU or M
PU) is supplied with software program code for implementing the above-described embodiment, and the computer of the system or apparatus operates the various devices according to the program code to realize the above-described embodiment. Included in the scope of the invention.

In this case, the program code itself of the software realizes the functions of the above-described embodiment, and the program code itself and means for supplying the program code to the computer, specifically, A storage medium storing the program code is included in the scope of the present invention.

As a storage medium for storing such a program code, for example, a floppy (registered trademark) disk, hard disk, optical disk, magneto-optical disk, C
D-ROM, DVD, magnetic tape, nonvolatile memory card, ROM, and the like can be used.

In addition to the case where the computer controls various devices in accordance with only the supplied program code to realize the functions of the above-described embodiment, the program code operates on the computer. Such a program code is included in the scope of the present invention even when the above-described embodiment is realized in cooperation with an OS (Operating System) or other application software. Further, after the supplied program code is stored in the memory provided in the function expansion board of the computer or the ladder expansion unit connected to the computer, the function expansion board or the function storage unit is stored based on the instruction of the program code. The present invention includes a case where the CPU or the like provided in the first embodiment performs a part or all of the actual processing, and the processing realizes the above-described embodiment.

[0051]

As described above, according to the present invention,
An image processing apparatus, an image processing method, and a storage medium for efficiently compressing an image while maintaining image quality can be provided.

[Brief description of the drawings]

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

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

FIG. 3 is a flowchart illustrating a process performed by a character area detection unit according to the first embodiment of this invention.

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

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

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

FIG. 7 is a diagram illustrating an example of a character area image for describing a character area detection process according to the first embodiment of this invention.

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

FIG. 9 is a diagram illustrating 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 for explaining a character portion filling process according to the first embodiment of this invention.

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

FIG. 12 is a flowchart illustrating a process of a color calculation unit according to the first embodiment of the present invention.

FIG. 13 is a diagram illustrating an example of a representative value calculation process of the color calculation unit according to the first embodiment of the present invention.

FIG. 14 is a diagram for explaining a united portion 204 of the stretching device according to the first embodiment of the present invention.

FIG. 15 is a block diagram showing a modification of the first embodiment of the present invention.

FIG. 16 is a block diagram showing a modification of the first embodiment of the present invention.

FIG. 17 is a block diagram showing a modified example of the first embodiment, which also supports inverted characters.

FIG. 18 is a diagram illustrating an example of a filter of a differentiation process according to a modification of the first embodiment.

FIG. 19 is a diagram illustrating a histogram pattern of an area input to a binarizing unit 1703 according to a modification of the first embodiment.

FIG. 20 is a block diagram showing a reduction device according to a second embodiment of the present invention.

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Claims (10)

[Claims] An extracting means for extracting a character region from the multi-valued image data and generating position data of the character region; binarizing the multi-valued image data of the character region to convert the character region binary image data into A binarizing means for generating, a color calculating means for calculating a representative color of the character area and generating color data of the character, and a multi-valued image of the character area using multi-valued image data of an area other than the character Conversion means for converting data to generate multi-valued image data without characters; resolution conversion means for reducing the resolution of the multi-valued image data without characters to generate multi-valued image data without reduced characters; An image processing apparatus comprising: first compression means for compressing value image data; and second compression means for compressing the character area binary image data. 2. The image processing apparatus according to claim 1, further comprising control means for controlling a resolution conversion parameter in said resolution conversion means. 3. The non-character multi-valued image data having a large high-frequency component for the character-less multi-valued image data having a small high-frequency component when the multi-valued image data without a character is subjected to an orthogonal transformation. The image processing apparatus according to claim 2, wherein the resolution conversion parameter is controlled so as to convert the data into lower resolution than data. 4. The control means applies a differentiation filter to the multi-valued image data without characters, and increases the total number of absolute values for the multi-valued image data without characters having a small total number of absolute values. 3. The image processing apparatus according to claim 2, wherein the resolution conversion parameter is controlled so as to convert to a lower resolution than the multi-valued image data without characters having a large high-frequency component. 5. The image processing apparatus according to claim 1, wherein said first compression means conforms to JPEG compression. 6. An image processing apparatus according to claim 1, wherein said second compression means is based on MMR compression. 7. The image processing apparatus according to claim 1, further comprising a third compression unit that combines the position data, the color data, and the outputs of the first and second compression units, and further compresses the data by a reversible compression method. Item 2. The image processing device according to Item 1. 8. An image processing apparatus for decompressing a compressed image by the image processing apparatus according to claim 1, wherein said image is compressed by said first compression means. First decompression means for decompressing multivalued image data without reduced characters; second decompression means for decompressing the character area binary image data compressed by the second compression means; Resolution conversion means for increasing the resolution to generate the character-less multi-valued image data; and inputting the position data and the color data,
Image merging means for generating the multi-valued image data from the value image data and the character-less multi-valued image data. 9. An extraction step of extracting a character region from multi-valued image data and generating position data of the character region, and binarizing the character region data of the multi-valued image data to form a character region A binarizing step of generating binary image data; a color calculating step of calculating a representative color of the character area to generate character color data; and a data of an area other than the character in the multi-valued image data. Using, converting the data of the character area, only the characters are deleted from the multi-valued image data, a conversion step of generating multi-valued image data without characters, lowering the resolution of the multi-valued image data without characters A resolution conversion step of generating reduced character-less multivalued image data; a first compression step of compressing the reduced character-less multivalued image data; and a second compression step of compressing the character area binary image data. Features Image processing method. 10. A computer-readable memory storing a compression program for compressing multi-valued image data, wherein the compression program extracts a character area from the multi-valued image data and generates position data of the character area. A code of a process; a code of a binarization step of binarizing the data of the character area in the multi-valued image data to generate character area binary image data; and calculating a representative color of the character area. Using the code of the color calculation step of generating the color data of the character and the data of the area other than the character among the multi-valued image data, the data of the character area is converted, and only the character is converted from the multi-valued image data. A code for a conversion step of generating multi-valued image data without characters, and a resolution changer for reducing the resolution of the multi-valued image data without characters to generate reduced multi-valued image data without characters. And a code for a first compression step for compressing the multi-valued image data without reduced characters, and a code for a second compression step for compressing the character area binary image data. Readable memory.