JPH1063833A - Processor and method for image processing - Google Patents

Abstract

PROBLEM TO BE SOLVED: To perform optimum conversion according to a color image to be converted by analyzing a color-value frequency distribution of pixels by color components and detecting a color value area, expanding the color value area and generating a conversion table consisting of color values before and after expansion, and converting a color image into a monochromatic image. SOLUTION: Multi-valued color image data of R, G, and B held in an auxiliary storage device 4 are read in a RAM 2, only R components of the color image data are extracted, and a histogram of the number of pixels to color values is generated and recorded in the RAM 2. The histogram is so shifted so that only an area having the number of pixels larger than a threshold value previously set for the histogram is regarded as an object. A new color value area is regarded as an object area of color/black-and-white conversion thereafter to obtain proper contrast to be converted. With the new histogram, a color value area having no distribution of pixels is detected and stored. Further, a conversion table having the same color value after conversion with input color values is generated and the R value process is completed.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

The present invention relates to an image processing apparatus and method, and more particularly, to an image processing apparatus and method for converting a color image into a black and white image.

[0002]

2. Description of the Related Art With the development of image input devices such as digital cameras and scanners in recent years, it has become easy to capture a full-color natural image into a computer.

However, for example, when printing a full-color natural image captured in a computer on a recording medium, it is necessary to perform image processing according to the performance of the printing apparatus. In particular, if the printing device is a monochrome printer, a full-color natural image must be converted to a monochrome image. In this case, in the image data after the black-and-white conversion, it is necessary to represent the image with a smaller amount of information than before the conversion. In many cases, a black-and-white conversion of a color image is performed according to a general formula using a coefficient that emphasizes a large number of colors. This coefficient was obtained empirically.

[0004]

However, when the conversion is performed using the general formula for color / black and white image conversion in the above-described conventional example, the converted black and white image has a larger data size than the color image before conversion. The amount is reduced. That is,
In the converted black and white image, the amount of information expressing the image is reduced, so that it is difficult to recognize subtle gradations.

Further, the above-mentioned general formula for color / black and white image conversion is an empirical formula obtained assuming a general natural image, and is not necessarily optimal for any image. I could not say it. For example, as described above, when it is desired to express a delicate gradation or to enhance contrast, an optimal conversion process cannot be performed according to an image to be processed.

SUMMARY OF THE INVENTION The present invention has been made to solve the above-mentioned problems, and an image processing apparatus and method for performing optimal conversion according to a color image to be converted when performing color / monochrome image conversion. The purpose is to provide.

For example, according to a color image to be converted,
An object of the present invention is to enable color / monochrome image conversion enabling natural gradation expression.

It is another object of the present invention to enable color / monochrome image conversion in which the contrast of the entire image is enhanced according to the color image to be converted.

[0009]

As one means for achieving the above object, the image processing apparatus of the present invention has the following arrangement.

That is, for each color component of a color image, analysis means for analyzing a frequency distribution of pixels with respect to color values, detection means for detecting a color value area in which the pixels are distributed based on the frequency distribution, Expansion means for expanding the color value area detected by the means, table creation means for creating a conversion table between the color values before expansion and color values after expansion, and monochrome conversion of the color image based on the conversion table. Conversion means for converting into an image.

Analysis means for analyzing a frequency distribution of pixels with respect to color values for each color component of the color image; detection means for detecting a distribution ratio of the pixels based on the frequency distribution; Converting means for converting the color image into a monochrome image based on the distribution ratio of each color component thus obtained.

Further, as a method for achieving the above object, the image processing method of the present invention includes the following steps.

That is, for each color component of a color image, an analyzing step of analyzing a frequency distribution of pixels with respect to color values, a detecting step of detecting a color value area in which the pixels are distributed based on the frequency distribution, An expansion step of expanding the color value area detected in the step, a table creation step of creating a conversion table between the color value before expansion and the color value after expansion, and monochrome conversion of the color image based on the conversion table. And converting the image into an image.

An analyzing step of analyzing a frequency distribution of pixels with respect to a color value for each color component of the color image; a detecting step of detecting a distribution ratio of the pixels based on the frequency distribution; And converting the color image into a monochrome image based on the distribution ratio of each of the color components.

[0015]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment according to the present invention will be described below in detail with reference to the drawings.

<First Embodiment> In the present embodiment,
An example in which color / monochrome image conversion is performed in a host computer will be described. FIG. 1 is a block diagram of the inside of the host computer according to the present embodiment. In FIG. 1, reference numeral 1 denotes a CPU for controlling the color / monochrome image conversion processing in the present embodiment, reference numeral 2 denotes a RAM for providing a work area for the CPU 1, and reference numeral 3 denotes a data control unit for controlling the auxiliary storage device 4. Reference numeral 4 denotes an auxiliary storage device, which also stores a control program, a library, and the like in the present embodiment.
As the auxiliary storage device 4, a hard disk or a CD-RO
M, MO, FD, RAM and the like can be considered. 5 is a main bus, and the CPU 1 is a RAM via the main bus 5.
2, a data control unit 3 and an auxiliary storage device 4 are controlled. The control program in the present embodiment is loaded from the auxiliary storage device 4 into the RAM 2 under the control of the CPU 1 and executed.

The present embodiment is characterized in that a subtle gradation can be expressed in a monochrome image after color / monochrome image conversion.

Hereinafter, the color / monochrome image conversion processing in this embodiment will be described with reference to the flowchart of FIG.

First, the R held in the auxiliary storage device 4
The GB multi-valued color image data is read into the RAM 2 (S201). Next, only the R component of the color image data on the RAM 2 is extracted, a histogram of “color value” versus “number of pixels” is obtained, and is recorded in the RAM 2 (S202). FIG. 3 shows an example of this histogram. In FIG. 3, the horizontal axis indicates the image density value (color value), and the vertical axis indicates the number of data (pixel number) having the density value.

Next, with respect to the histogram obtained in step S202, the histogram is shifted so that only the region having the number of pixels equal to or greater than a preset threshold value is targeted (S203). That is, as shown in FIG. 4, a histogram shown in FIG. 5 is obtained by extracting a color value region having the number of pixels equal to or larger than the threshold value S. Hereinafter, the new color value area shown in FIG. 5 is set as the target area of the color / monochrome conversion. This makes it possible to remove noise included in the conversion target image and obtain an appropriate contrast to be converted. Note that this threshold S is a characteristic of a color image to be processed,
It is also possible to make the color components different depending on the converted black-and-white image characteristics and the like.

Next, in the new histogram obtained in step S203, a color value area having no pixel distribution (non-color distribution area), that is, a color value range in which the number of pixels is 0 is detected and stored in the RAM 2. (S204). Further, a color value area (color distribution area) where pixels are distributed is detected,
(S205). For example, taking the histogram of FIG. 5 as an example, the non-color distribution area is the area indicated by a in FIG. 6, and the other areas are the color distribution areas.

If no non-color distribution area is detected (S206), the process proceeds to step S210, where a dummy conversion table that does not actually perform conversion is created. That is, a conversion table is created so that the input color value and the converted color value are equal, and the conversion table is stored in the RAM 2. This gives R
The process for the value ends, and the process proceeds to step S211 to start the process for the next color component (for example, the G component).

When a non-color distribution area is detected in step S206, a median M in the obtained color distribution area is obtained as shown in FIG. 7 (S207). Then, the pixel distribution is extended to the non-color distribution area around the median M (S208). The expansion rate at this time is set so that the expanded color distribution areas do not overlap each other, but can be changed as appropriate according to the characteristics of the color image to be converted and the converted monochrome image. . FIG. 8 shows how the color distribution region is expanded. In FIG. 8, a dotted line indicates step S2.
03 is a histogram obtained by expanding the histogram in the direction of the arrow to obtain an expanded histogram indicated by a solid line.

On the basis of the extended histogram thus obtained, the conversion table between the original color value and the expanded color value for the R component of the original image, that is, the solid line from the dotted histogram in FIG. A conversion table of the color values to the histogram is created and stored in the RAM 2 (S2
09).

Thus, the processing for the R component is completed.
Then, it is determined whether or not the processing for all the color components of the original image has been completed (S211). If not completed, for example, in order to perform processing on the G component next, step S20
Return to 2. Thus, steps S202 to S21
By performing the process of 0 for all the R, G, and B color components, a conversion table for each of the R, G, and B color components is created.

Next, color image data is converted into black-and-white multi-value image data based on the R, G, B conversion tables created by the above steps (S212).
Hereinafter, a specific example of this conversion will be described.

By substituting the color values for each color component of the original image into the following color image data / black and white image data conversion formula (1), black and white multivalued image data is obtained.
Record in 2. That is, assuming that the R, G, and B color components of a pixel i in a color image are Ri, Gi, and Bi, the converted black-and-white multivalued data Valuei of the pixel is obtained by the following equation (1).

Valuei = (3 × TableR (Ri) + 6 × TableG (Gi) + TableB (Bi)) / 10 (1) where TableR: R conversion table TableG: G conversion table TableB: B conversion table Conversion Table As described above, in the present embodiment, color / black and white image conversion is performed according to the above equation (1).

As described above, according to the present embodiment, when performing color / monochrome image conversion, the color distribution area is expanded and the image information is sorted for each color component of the color image to be converted. The image information amount can be ensured even in the converted black and white image. Therefore, subtle gradation expression in the converted black and white image is also possible.

In this embodiment, an example in which the conversion table for each color component is applied to the equation (1) has been described. However, the coefficients and the like are not limited to the equation (1). . The present embodiment is characterized in that the density value of an input image is converted and applied to a conversion formula by a conversion table obtained by expanding the color distribution of a color image to be converted into an area having no distribution. The coefficients and the like in the expression 1) can be changed as appropriate.

<Second Embodiment> Hereinafter, a second embodiment according to the present invention will be described.
An embodiment will be described.

Since the configuration of the host computer for realizing the second embodiment is the same as that of the above-described first embodiment,
Description is omitted.

In the second embodiment, an example will be described in which color / black and white conversion in which contrast is enhanced is performed.

Hereinafter, the color / monochrome image conversion processing in the second embodiment will be described in detail with reference to the flowchart of FIG.

First, the R stored in the auxiliary storage device 4
The GB multi-valued color image data is read into the RAM 2 (S901). Next, for each of the R, G, and B components of the color image data on the RAM 2, a histogram of “color value” versus “number of pixels” is obtained and recorded in the RAM 2 (S9).
02). FIG. 10 shows an example of this histogram. FIG.
(A), (b), and (c) are histograms for each of the R, G, and B color components. The horizontal axis represents the image density value (color value), and the vertical axis represents the number of data having the density value. (Number of pixels).

Next, the area (distribution area) of the pixel distribution area is determined for each color component histogram (S903). For example, in (a) to (c) of FIG. 10, hatched portions respectively correspond to distribution areas.

Next, the ratio of the distribution area for each color component obtained in step S903 is determined (S904), and a coefficient of a conversion formula for converting a color image into black-and-white multivalued image data is set (S905). . Hereinafter, the setting method will be described.

First, assuming that the intensity ratio of each color component and the sum thereof are Kr: Kg: Kb K = Kr + Kg + Kb, the intensity coefficients of the R, G, and B color components are Kr / K, Kg / K, and Kb / K, respectively. It is represented by The intensity coefficient is a value preset based on a general image. For example, if Kr = 3, Kg = 6, and Kb = 1, the intensity coefficients Kr / K, Kg / K, and Kb / K Are 3/10,
6/10 and 1/10.

In this case, the color image data / monochrome image data conversion formula is as follows: for a pixel i in a color image, its R, G, B color components are Ri, Gi, Bi, Is the value, the following equation (2) is obtained.

Valuei = (Kr × Ri + Kg × Gi + Kb × Bi) / K (2) Here, the area ratio for each of the R, G, and B color components obtained in step S 903 and the sum thereof are represented by Sr: Sg: Assuming that Sb S = Sr + Sg + Sb, the above conversion equation (2) is modified as follows in consideration of these area ratios.

Valuei = (Kr × Sr × Ri + Kg × Sg × Gi + Kb × Sb × Bi) × m / (K × S) (3) m = (K × S) / (Kr × Sr + Kg × Sg + Kb × Sb) (4) In the second embodiment, a new intensity coefficient is set by multiplying the intensity coefficient in the color / monochrome image conversion equation (2) by the area ratio of the pixel distribution area for each color component. (3) and (4) are obtained.

Then, according to the conversion formulas (3) and (4), color / monochrome image conversion is performed in consideration of the area ratio of the pixel distribution area for each color component (S906).

As described above, according to the second embodiment,
The area of the pixel distribution area for each color component of the color image
By multiplying the intensity coefficient of the black-and-white image conversion formula, it is possible to perform conversion that emphasizes colors that have a large proportion in the entire image.
Therefore, the contrast of the entire image can be enhanced.

In the first and second embodiments described above, the processing for converting an RGB color image into a monochrome image has been described. However, the processing for converting a color image composed of a plurality of color components into a monochrome image is described. If so, the present invention is of course applicable.

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

Another object of the present invention is to provide a storage medium storing a program code of software for realizing the functions of the above-described embodiments to a system or apparatus, and to provide a computer (or CPU) of the system or apparatus.
And MPU) read and execute the program code stored in the storage medium.

In this case, the program code itself read from the storage medium realizes the functions of the above-described embodiment, and the storage medium storing the program code constitutes the present invention.

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

When the computer executes the readout program code, not only the functions of the above-described embodiment are realized, but also the OS (Operating System) running on the computer based on the instruction of the program code. ) May perform some or all of the actual processing, and the processing may realize the functions of the above-described embodiments.

Further, after the program code read from the storage medium is written into a memory provided in a function expansion board inserted into the computer or a function expansion unit connected to the computer, based on the instruction of the program code, It goes without saying that the CPU included in the function expansion board or the function expansion unit performs part or all of the actual processing, and the processing realizes the functions of the above-described embodiments.

When the present invention is applied to the storage medium, the storage medium stores program codes corresponding to the above-described flowcharts. Each module shown in the memory map example is stored in the storage medium. That is,
At least the program code of each module of the “histogram creation module”, “histogram extension module”, “color conversion table creation module” and “color / monochrome conversion module” may be stored in the storage medium. Alternatively, each module shown in the example of the memory map in FIG. 11B is stored in a storage medium. That is, the program codes of at least the respective modules of the “histogram creation module”, the “area ratio calculation module”, and the “color / monochrome conversion module” may be stored in the storage medium.

[0052]

As described above, according to the present invention, when performing a color / monochrome image conversion, it is possible to perform an optimum conversion according to a color image to be converted.

For example, according to the color image to be converted,
Color / monochrome image conversion enabling natural gradation expression becomes possible.

Further, according to the color image to be converted, color / monochrome image conversion in which the contrast of the entire image is enhanced can be performed.

[0055]

[Brief description of the drawings]

FIG. 1 is a block diagram illustrating a configuration of a host computer according to an embodiment of the present invention.

FIG. 2 is a flowchart illustrating a color / monochrome image conversion process according to the embodiment.

FIG. 3 is a diagram showing an example of a histogram obtained in the embodiment.

FIG. 4 is a diagram illustrating an example of a shift of a histogram according to the present embodiment.

FIG. 5 is a diagram illustrating an example of a shift of a histogram according to the present embodiment.

FIG. 6 is a diagram illustrating an example of a non-color distribution area according to the present embodiment.

FIG. 7 is a diagram illustrating a median value of a color distribution area according to the embodiment.

FIG. 8 is a diagram illustrating a state in which a color distribution area is expanded in the embodiment.

FIG. 9 is a flowchart illustrating a color / monochrome image conversion process according to the second embodiment of the present invention.

FIG. 10 is a diagram showing an example of a histogram obtained in the second embodiment.

FIG. 11 is a diagram showing an example of a memory map when the present invention is applied to a storage medium.

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 1 CPU 2 RAM 3 Data control part 4 Auxiliary storage device 5 Main bus

Claims (16)

[Claims] An analyzing unit that analyzes a frequency distribution of pixels with respect to a color value for each color component of a color image; a detecting unit that detects a color value area in which the pixels are distributed based on the frequency distribution; Expansion means for expanding the color value area detected by the means; table creation means for creating a conversion table between the color values before expansion and the color values after expansion; and monochrome conversion of the color image based on the conversion table. An image processing apparatus comprising: a conversion unit configured to convert an image into an image. 2. An image processing apparatus according to claim 1, wherein said analysis means creates a histogram as a frequency distribution. 3. The image processing apparatus according to claim 2, wherein the analysis unit creates a histogram in which the frequency distribution of the pixels is equal to or more than a predetermined value. 4. The image processing apparatus according to claim 1, wherein the extension unit extends the color value area around a center value of the color value area. 5. The image processing apparatus according to claim 4, wherein the expansion unit expands the color value area to an area without a pixel distribution. 6. The expansion unit according to claim 5, wherein the expansion unit expands the plurality of color value areas after expansion so as not to overlap.
The image processing apparatus according to any one of the preceding claims. 7. The apparatus according to claim 1, wherein the conversion unit converts color values of each color component of the color image using the conversion table, and creates a monochrome image based on the converted color values. The image processing apparatus according to any one of the preceding claims. 8. The apparatus according to claim 1, wherein the table creation unit creates the conversion table so as not to convert the color value before expansion when the color value area is not detected by the detection unit. Image processing device. 9. An analyzing means for analyzing a frequency distribution of pixels with respect to a color value for each color component of a color image; a detecting means for detecting a distribution rate of the pixels based on the frequency distribution; Converting means for converting the color image into a monochrome image based on the obtained distribution ratio of each color component. 10. An image processing apparatus according to claim 9, wherein said analysis means creates a histogram as a frequency distribution. 11. The apparatus according to claim 10, wherein said detecting means obtains an area of a region where pixels are distributed on said histogram, and said converting means performs conversion based on an area ratio of each color component. Image processing device. 12. The image processing apparatus according to claim 11, wherein the conversion unit performs conversion based on a content rate of each color component in consideration of the area ratio. 13. An analyzing step of analyzing a frequency distribution of pixels with respect to a color value for each color component of a color image; a detecting step of detecting a color value area in which the pixels are distributed based on the frequency distribution; An expansion step of expanding a color value area detected in the step; a table creation step of creating a conversion table between the color values before expansion and the color values after expansion; and monochrome conversion of the color image based on the conversion table. Converting the image into an image. 14. An analysis step of analyzing a frequency distribution of pixels with respect to a color value for each color component of a color image; a detection step of detecting a distribution rate of the pixels based on the frequency distribution; A conversion step of converting the color image into a monochrome image based on the obtained distribution ratio of each color component. 15. A computer-readable memory storing a program code for image processing, comprising: a code of an analyzing step of analyzing a frequency distribution of pixels with respect to a color value for each color component of a color image; A code of a detection step of detecting a color value area in which the pixels are distributed, a code of an expansion step of expanding the color value area detected in the detection step, and a color value before expansion and a color value after expansion. A computer readable memory, comprising: a code for a table creation step for creating the conversion table described above; and a code for a conversion step for converting the color image into a monochrome image based on the conversion table. 16. A computer-readable memory storing a program code for image processing, comprising: a code of an analyzing step of analyzing a frequency distribution of pixels with respect to a color value for each color component of a color image; And a code for a conversion step of converting the color image into a monochrome image based on the distribution rate of each color component detected in the detection step. Computer readable memory featured.