JP2008271131A - Method and device for image processing, and image forming apparatus - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a method and device for image processing, and an image forming apparatus, which have high image reproductivity. <P>SOLUTION: RGB data is converted to Lab data, and black color data K' before conversion is calculated from L that is brightness information of the converted Lab data. Chroma C is calculated from the Lab data, and black color data K after conversion is calculated from the black color data K' before conversion based on the calculated chroma C. Separately, a color space conversion is performed from the RGB data to CMY data using a three-dimensional table. Finally, under colors are removed to determine CMYK data. <P>COPYRIGHT: (C)2009,JPO&INPIT

Description

  The present invention relates to an image processing method, an image processing apparatus, and an image forming apparatus that perform color space conversion.

  There is an increasing demand for a digital multi-function peripheral that realizes a plurality of functions related to image formation such as a copying function, a print-out function, and a facsimile function with a single device. Since it is expected to reduce the installation area of the device and lower the operating cost, it is often used especially in offices, and additional functions for that purpose are also increasing.

One of the additional functions is a document filing function. This function stores once processed image data such as copied original image data, image data input from a PC (personal computer), image data received by facsimile or facsimile transmission in a predetermined storage device, and is necessary. This is a function that can be called up and printed again and sent by facsimile. In order to realize such a function, it is necessary to store as many image data as possible in the storage device. In addition to simply increasing the storage capacity of the storage device, the number of image data stored in the storage device can be increased by reducing the file size of each image data itself.

  For reducing the file size of image data, it is possible to use an existing file compression technique, and JPEG (Joint Photographic Experts Group) compression is often used because of its high compression ratio. Most of the image data handled by the digital multi-function peripheral is RGB (R: red, G: green, B: blue) data, but the color of the RGB data is a device for outputting an image (printing device, display device, etc.) Therefore, the reproducibility of the image is not ensured. Lab data is used as image data for improving the reproducibility of an output image.

  The image processing method described in Patent Document 1 converts read image data in the RGB color space into image data in the Lab color space independent of the device, and converts the converted image data in the Lab color space into image data in the CMYK color space. Convert.

  According to the color conversion method described in Patent Document 2, virtual CMY data is calculated based on input PGB data, the virtual CMY data is decomposed into K data and RGB data, and based on a predetermined mixing ratio of CMY data. Deliver to CMY data.

JP 2003-18419 A JP 2004-297380 A

  In the prior art as described above, black is generated without considering brightness, hue, saturation, etc., and there is a problem in image reproducibility.

  An object of the present invention is to provide an image processing method, an image processing apparatus, and an image forming apparatus with higher image reproducibility.

The present invention is an image processing method for converting RGB color space data into CMYK color space data,
An image processing method characterized in that black color data is added to RGB color space data to create RGBK ′ color space data, and conversion into CMYK color space data based on the RGBK ′ color space data.

The present invention also includes a first conversion step for converting RGB color space data into Lab color space data;
A black data creation step of creating the black data from luminance information based on Lab color space data;
A second conversion step of converting RGBK ′ color space data into CMYK color space data.

The present invention also includes a reading step of reading RGBK ′ color space data by a reading device;
A conversion step of converting RGBK ′ color space data into CMYK color space data.

  In addition, the present invention is characterized by having a black conversion step of converting black data based on saturation information.

  Further, according to the present invention, conversion from RGB color space data to CMY color space data is performed in advance in each region obtained by dividing the RGB color space into a plurality of block bodies, such as Y (yellow), M (magenta), and C (cyan). The conversion is performed based on a color conversion table in which predetermined gradation values are associated with each other.

  In addition, the present invention is an image processing apparatus that performs image processing using the above-described image processing method.

  According to another aspect of the present invention, there is provided an image forming apparatus that performs image formation based on CMYK color space data converted by using the image processing method described above.

  According to the present invention, there is an image processing method for converting RGB color space data into CMYK color space data. Black color data is added to the RGB color space data to create RGBK ′ color space data, and conversion into CMYK color space data is performed based on the RGBK ′ color space data.

  Thereby, black generation in consideration of luminance, hue, saturation, and the like is performed, so that it can be converted into CMYK color space data with higher image reproducibility.

  According to the invention, the RGB color space data is converted into Lab color space data in the first conversion step, and the black data is created from the luminance information based on the Lab color space data in the black data creation step. In the second conversion step, RGBK ′ color space data is converted to CMYK color space data.

  Thereby, black generation in consideration of luminance information is performed, and conversion to CMYK color space data can be performed with higher image reproducibility.

  According to the invention, in the reading step, the RGBK ′ color space data is read by the reading device, and in the conversion step, the RGBK ′ color space data is converted into CMYK color space data.

  Since black data is read directly, it can be converted into CMYK color space data with higher image reproducibility.

  Moreover, according to this invention, it has a black conversion process which converts black data based on saturation information. Since the black data obtained from the luminance and the like is further converted based on the saturation information, the reproducibility of the black data is improved, and the black data can be converted into CMYK color space data with higher image reproducibility.

  According to the present invention, the conversion from the RGB color space data to the CMY color space data is performed by using Y (yellow), M (magenta), and C (cyan) in each area obtained by dividing the RGB color space into a plurality of block bodies. Are converted on the basis of a color conversion table corresponding to the predetermined gradation values.

  As a result, the amount of data in the table required for conversion from RGB color space data to CMY color space data can be reduced, and conversion with no color misregistration and higher reproducibility than when using a conversion formula is performed. be able to.

  According to the present invention, there is provided an image processing apparatus that performs image processing using the image processing method described above.

  Thereby, black generation in consideration of luminance, hue, saturation, and the like is performed, so that it can be converted into CMYK color space data with higher image reproducibility.

  According to the invention, there is provided an image forming apparatus characterized in that an image is formed based on CMYK color space data converted using the image processing method described above.

  As a result, high-quality image formation can be performed using CMYK color space data with high image reproducibility.

(First embodiment)
FIG. 1 is a block diagram showing a schematic configuration of a color image forming apparatus 50 according to the first embodiment of the present invention. The color image forming apparatus 50 includes a color image processing apparatus 10, a color image input apparatus 20, a color image output apparatus 30, and an operation panel 40, and is realized as a digital color copying machine, for example.

  As shown in FIG. 1, a color image processing apparatus 10 includes an A / D (analog / digital) conversion unit 11, a shading correction unit 12, an input tone correction unit 13, a region separation processing unit 14, a color conversion black generation lower color. A removal unit 15, a spatial filter processing unit 16, an output tone correction unit 17, and a tone reproduction processing unit 18 are provided.

  The color image input device 20 is composed of, for example, a scanner unit including a charge coupled device (hereinafter referred to as a CCD), and a reflected light image from a paper on which an original image is recorded is imaged by the CCD. Data is read as analog color signals of RGB (R: red, G: green, B: blue) and is input to the color image processing apparatus 10.

  An analog color signal read by the color image input device 20 is converted into an A / D conversion unit 11, a shading correction unit 12, an input tone correction unit 13, a region separation processing unit 14, a color conversion in the color image processing device 10. Black generation and under color removal unit 15, spatial filter processing unit 16, output gradation correction unit 17, and gradation reproduction processing unit 18 are sent in this order, CMYK (C: cyan, M: magenta, Y: yellow, K: As a digital color signal of black), it is output to the color image output device 30.

  The A / D converter 11 converts the input RGB analog color signal into a digital color signal which is image data. The shading correction unit 12 performs processing for removing various distortions generated in the illumination system, the imaging system, and the imaging system of the color image input device 20 from the RGB digital color signals sent from the A / D conversion unit 11. Apply.

  The input tone correction unit 13 adjusts the color balance of the RGB signal (RGB reflectance signal) from which various distortions have been removed by the shading correction unit 12, and at the same time, the color image processing apparatus 10 such as a density signal is easy to handle. Convert to signal.

  The region separation processing unit 14 separates each pixel of the input image data as pixels belonging to a plurality of regions such as a character region, a halftone dot region, and a photo region based on the RGB signals.

  Then, the region separation processing unit 14 outputs a region identification signal indicating to which region the pixel belongs to the spatial filter processing unit 16 and the gradation reproduction processing unit 18 based on the separation result, and also receives the input signal. Is directly output to the subsequent color conversion black generation / under color removal unit 15.

  As the region separation processing, for example, a maximum density difference that is a difference between a minimum density value (minimum pixel value) and a maximum density value (maximum pixel value) in an n × m block (for example, 15 × 15) including the pixel of interest. By calculating the total density busyness, which is the sum of the absolute values of the density differences between adjacent pixels, and comparing it with a plurality of predetermined threshold values, the background area, photo area, text area, or halftone area It is possible to separate. In the present invention, after each pixel is separated into the above-described areas, it is determined that it belongs to a non-edge area if it is a background area or a photographic area, and it belongs to an edge area if it is a character area or a halftone dot area. . A specific example of the region separation process is described in, for example, Japanese Patent Application Laid-Open No. 2002-232708.

  Since the density distribution of the background region is usually small in density change, both the maximum density difference and the total density busyness are very small. The density distribution in the photographic area has a smooth density change, and the maximum density difference and the total density busyness are both small, but somewhat larger than the background area. In the density distribution of the halftone dot area, the maximum density difference varies depending on the halftone dot, but the total density busyness changes by the number of halftone dots, so the ratio of the total density busyness to the maximum density difference is large. Become.

  Therefore, when the total density busyness is larger than the product of the maximum density difference and the character / halftone dot determination threshold (one of the plurality of thresholds), it is determined that the area is a halftone area. In the density distribution of the character area, the maximum density difference is large and the total density busyness increases accordingly. However, since the density change is smaller than that of the halftone dot area, the total density busyness is smaller than that of the halftone dot area. Therefore, when the total density busyness is smaller than the product of the maximum density difference and the character / halftone dot determination threshold, the character area is determined.

  Therefore, a comparison between the calculated maximum density difference and the maximum density difference threshold, and a comparison between the calculated total density busyness and the total density busyness threshold, the maximum density difference is smaller than the maximum density difference threshold, If the total density busyness is smaller than the total density busyness threshold, it is determined that the pixel of interest is a background / photograph area, otherwise it is determined to be a character / halftone area.

  In addition, when it is determined that it is a background / photo area, the calculated maximum density difference is compared with the background / photo determination threshold, and if the maximum density difference is smaller, it is determined to be a background area, If the maximum density difference is larger, it is determined that the area is a photograph area. When it is determined that the area is a character / halftone area, the calculated total density busyness is compared with the value obtained by multiplying the maximum density difference by the character / halftone threshold, and the total density busyness is smaller Is determined to be a character region, and if the total density is larger, it is determined to be a halftone dot region.

  As will be described in detail later, the color conversion black generation / under color removal unit 15 adds RGB (K ′) data to RGB color space data to create RGBK ′ color space data, and generates CMYK colors based on the RGBK ′ color space data. Convert to spatial data.

  The spatial filter processing unit 16 performs spatial filter processing with a digital filter on the image data of the CMYK signal input from the color conversion black generation / under color removal unit 15 based on the region identification signal. By correcting the spatial frequency characteristics, it is possible to prevent blurring of the output image and deterioration of graininess.

  For example, a region separated as a character region by the region separation processing unit 14 emphasizes high-frequency components by sharp enhancement processing in the spatial filter processing of the spatial filter processing unit 16 in order to improve the reproducibility of black characters or color characters. . In addition, the region separated as the halftone dot region by the region separation processing unit 14 is reproduced by the spatial filter processing unit 16 as much as possible without performing the low-pass filter processing for removing the halftone dot component. As possible, high-frequency components are emphasized by passing through (prohibiting) spatial filtering or sharpening enhancement.

  Conventionally, the halftone dot region has been subjected to a smoothing process to prevent moire. However, when the smoothing process is performed, the halftone dot shape is lost, which is not preferable in reproducing the halftone dot. Therefore, in the present invention, the halftone dot form is preserved by performing no processing on the halftone dot region (through the spatial filter processing) or by performing weak enhancement processing. The spatial filter processing in the spatial filter processing unit 17 is a through process or a sharp enhancement process in the case of a halftone dot area, but a common filter process can be performed regardless of the area.

  The output tone correction unit 17 performs output tone correction processing for converting a signal such as a density signal into a halftone dot area ratio that is a characteristic value of the image output device 30. The gradation reproduction processing unit 18 performs pseudo gradation reproduction processing on the image data of the CMYK signal so that the image can finally reproduce the gradation in a pseudo manner based on the region identification signal.

  The image data subjected to the above-described processes is temporarily stored in a storage unit (not shown), read at a predetermined timing, and output to the color image output device 30. The color image output device 30 outputs an image on a recording medium (for example, paper), and examples thereof include, but are not particularly limited to, output methods such as an electrophotographic method and an ink jet method.

  The operation panel 40 is configured by, for example, a touch panel in which a display unit such as a liquid crystal display and an operation unit such as a setting button are integrated, and the color image processing device 10 based on information input from the operation panel by the user. The operations of the color image input device 20 and the color image output device 30 are controlled. Each of the above processes is controlled by a CPU (Central Processing Unit: control means) not shown.

Here, the color space conversion processing by the color conversion black generation and under color removal unit 15 will be described in detail.
FIG. 2 is a flowchart showing the procedure of color space conversion processing.

First, in step S1, RGB data as image data is converted into CIE 1976 L ^* a ^* b ^* (CIE: Commission Internationale de l'Eclairage, International Lighting Commission, L ^* : brightness, a ^* · b ^* : chromaticity) color space. Color space conversion is performed on data (hereinafter referred to as “Lab data”).

The conversion from RGB data to Lab data may be performed based on a conversion formula, but in this embodiment, it is performed by a LUT (Look Up Table). Based on the conversion formula shown below, a table indicating the correspondence between RGB data and Lab data is created in advance, and when executing the conversion process, the Lab data corresponding to the conversion source RGB data is stored in the table. Just search from.
In the conversion from RGB data to Lab data, RGB data is first converted into XYZ color space data (hereinafter referred to as “XYZ data”), and then converted from XYZ data to Lab data.

Conversion from RGB data to XYZ data is performed using the following conversion formula.
X = 0.412453 × R + 0.35758 × G + 0.180423 × B
Y = 0.212671 × R + 1.51616 × G + 0.072169 × B
Z = 0.019334 × R + 0.119193 × G + 0.950227 × B
Furthermore, conversion from XYZ data to Lab data is performed using the following conversion formula.

  In step S2, the pre-conversion black data K ′ is calculated from L which is the luminance information of the converted Lab data. Since L is a luminance value, the black data before conversion can be calculated by K ′ = 100−L.

In step S3, the saturation C is calculated from the Lab data.
Based on a and b which are chromaticity information of the converted Lab data, it can be calculated by C = √ (a ² + b ² ).

  In step S4, the converted black data K is calculated based on the saturation C calculated in step S3.

  As the black data, since the data calculated from L cannot be used as it is for the CMYK data, the conversion rate W is obtained based on the saturation C, and the converted black data K is calculated as K = K ′ × W.

  FIG. 3 is a graph showing the relationship between the saturation C and the conversion rate W. The vertical axis represents the conversion rate W (%), and the horizontal axis represents the saturation C. Such a graph is obtained in advance from experimental values and stored as a table in the storage unit.

  When the saturation C is calculated in step S3, the conversion rate W is obtained with reference to the table. The converted black data K is calculated from K = K ′ × W using the obtained conversion rate W.

  In step S5, color space conversion from RGB data to CMY data is performed using a three-dimensional table.

  The three-dimensional table here is a color in which predetermined gradation values of Y (yellow), M (magenta), and C (cyan) are associated with each region obtained by dividing the RGB color space into a plurality of block bodies. It is a conversion table (TBL).

RGB-CMY conversion using a three-dimensional table will be described.
In TBL, if the gradation values of R, G, and B are between 0 and 255, and the predetermined gradation values of Y, M, and C are associated with each gradation, the amount of data becomes enormous. Therefore, a predetermined number N of grid points GP are determined for each of R, G, and B, and each region is represented by this grid point GP. In the present embodiment, the predetermined number N is selected to be 24. The gradation values of R, G, and B in the color space of the RGB color system correspond to any one of 24 × 24 × 24 grid points GP. The position of the grid point GP in the R direction is represented by GPr, the position of the grid point in the G direction is represented by GPg, and the position of the grid point in the B direction is represented by GPb. Accordingly, the position of the grid point GP in the RGB color system color space is represented by (GPr, GPg, GPb).

  Each grid point GP corresponds to a plurality of gradation values for each of R, G, and B. Corresponding to each grid point GP, representative gradation values of R, G, and B are associated with predetermined gradation values of Y, M, and C. The representative gradation values of R, G, and B represent a plurality of gradation values of R, G, and B included in the region corresponding to the grid point. Since the gradation values of R, G, and B input to the shading correction unit 12 often do not overlap with the gradation values corresponding to the grid points GP described above, they belong to which grid point GP by the three-dimensional interpolation process. Ask for. In this three-dimensional interpolation process, specifically, 8-point interpolation is performed. The input signal space corresponds to the color space of the RGB color system, and the X, Y, and Z axes that are orthogonal to each other correspond to the R, G, and B axes, respectively.

R, G, B for image data p in the input signal space in a lattice space surrounded by eight lattice points p _{0 to} p ₇ (p _{0 to} p ₇ are respectively grid points GP) adjacent to each other. Assuming that the relative point to the lattice width in the lattice is a, b, c with respect to the lattice point po where the grayscale value is the smallest, the interpolated value f (p) of 8-point interpolation is the point pi. Let f (pi) be the table value at
f (p) = (1-a) (1-b) (1-c) .f (p ₀ )
+ A (1-b) (1-c) .f (p ₁ )
+ Ab (1-c) · f (p ₂ )
+ (1-a) b (1-c) .f (p ₃ )
+ (1-a) (1-b) c · f (p ₄ )
+ A (1-b) c · f (p ₅ )
+ Abc · f (p ₆ )
+ (1-a) bc · f (p ₇ )
It is represented by

  The number of grid points GP is determined by the balance between the storage capacity of the memory storing the table and the production cost. If the gradation values of R, G, and B are 0 to 255, the number of R, G, and B If 24 or more grid points GP are determined for each, it is possible to prevent the gradation reproducibility from being lowered.

  The color conversion table TBL is created individually for each color image forming apparatus 50 so as to match the RGB color system and the YMC color system. That is, the original gradation value of each grid point GP and Y, M, and C is set so that the gradation reproducibility is good by reading the original with the color image input device 20 and printing with the color image output device 30. Are associated with each other.

  In this way, by performing RGB-CMY conversion using a three-dimensional table, the amount of data in the table required for color space conversion can be reduced, and there is no color misregistration, which is reproduced more than when using a conversion formula. Conversion can be performed.

  The CMY data obtained in this step is data before undercolor removal, and should be expressed as C′M′Y ′ data.

  In step S6, under color removal (UCR) is performed to determine CMYK data.

  FIG. 4 is a diagram illustrating a black generation curve and a UCR curve. The horizontal axis indicates the CMY minimum value, and the vertical axis indicates the black data K and the UCR value. Such a graph is obtained in advance from experimental values and stored as a table in the storage unit.

  In this step, first, the CMY minimum value is obtained from the black generation curve based on the converted black data K calculated in step S4, and the UCR value is obtained from the UCR curve based on the obtained CMY minimum value.

  C, M, and Y are calculated based on the C'M'Y 'data obtained in step S5 and the UCR value. C, M, and Y are calculated by C = C′−UCR, M = M′−UCR, and Y = Y′−UCR, respectively.

  CMYK data is obtained from the calculated C, M, Y and the converted black data K calculated in step S4.

(Conversion example)
For example, Lab data converted from RGB data is L = 22, a = 11, and b = -15.

First, K ′ = 100−L = 100−22 = 78 is calculated.
Further, C = √ (a ² + b ² ) = √ (11 ² + (− 15) ² ) ≈19 is calculated.

From the relationship between the saturation C and the conversion rate W shown in FIG. 3, W = 70% is obtained when C = 19.
From the obtained W, K = K ′ × W = 78 × 70% ≈55 is calculated.

  From the black generation curve and UCR curve shown in FIG. 4, when K = 55, UCR value = 63 is obtained.

  Using the three-dimensional table, RGB data is converted as C ′ = 90, M ′ = 100, and Y ′ = 70.

Using the obtained UCR value 63, C = C′−UCR = 90−63 = 27, M = M′−UCR = 100−63 = 37, and Y = Y′−UCR = 70−63 = 7, respectively. Is done.
From the above, C = 27, M = 37, Y = 7 and K = 55 are determined.

(Second Embodiment)
FIG. 5 is a block diagram showing a schematic configuration of a color image forming apparatus 50 according to the second embodiment of the present invention.

  In the present embodiment, the color image input device 20a is greatly different from the first embodiment in that the RGBK ′ data can be read. As such a CCD sensor capable of reading RGBK 'data, for example, a CCD linear image sensor TCD2561D manufactured by Toshiba can be practically used.

  Since the pre-conversion black data K ′ is obtained directly as data, the color conversion black generation / under color removal unit 15a of the color image processing apparatus 10a does not require step S2 of the flow shown in FIG. 2 in the color space conversion processing. . Other steps are the same in this embodiment.

  Since the pre-conversion black data K ′ is obtained directly as data, conversion processing with higher reproducibility can be performed.

1 is a block diagram illustrating a schematic configuration of a color image forming apparatus 50 according to a first embodiment of the present invention. It is a flowchart which shows the procedure of a color space conversion process. It is a graph which shows the relationship between saturation C and conversion rate W. It is a figure which shows a black production | generation curve and a UCR curve. It is a block diagram which shows the schematic structure of the color image forming apparatus 50 which is 2nd Embodiment of this invention.

Explanation of symbols

DESCRIPTION OF SYMBOLS 10 Color image processing apparatus 11 A / D conversion part 12 Shading correction part 13 Input gradation correction part 14 Area separation process part 15 Color conversion black production | generation under color removal part 16 Spatial filter process part 17 Output gradation correction part 18 Gradation reproduction Processing unit 20 Color image input device 30 Color image output device 40 Operation panel 50 Color image forming device

Claims (7)

An image processing method for converting RGB color space data into CMYK color space data,
An image processing method comprising: adding black data to RGB color space data to create RGBK ′ color space data, and converting the data into CMYK color space data based on the RGBK ′ color space data. A first conversion step of converting RGB color space data into Lab color space data;
A black data creation step of creating the black data from luminance information based on Lab color space data;
The image processing method according to claim 1, further comprising a second conversion step of converting RGBK ′ color space data into CMYK color space data. A reading step of reading RGBK ′ color space data by a reading device;
The image processing method according to claim 1, further comprising a conversion step of converting RGBK ′ color space data into CMYK color space data.   4. The image processing method according to claim 2, further comprising a black conversion step of converting black data based on the saturation information.   Conversion from RGB color space data to CMY color space data is performed by applying predetermined gradation values of Y (yellow), M (magenta), and C (cyan) to each region obtained by dividing the RGB color space into a plurality of block bodies. 5. The image processing method according to claim 1, wherein the conversion is performed based on a corresponding color conversion table.   An image processing apparatus that performs image processing using the image processing method according to claim 1.   An image forming apparatus that forms an image based on CMYK color space data converted by using the image processing method according to claim 1.

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