JP2006245727A - Image processing apparatus, network scanner apparatus, and color digital copying machine - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an image processing apparatus capable of accurately extracting black letters from image data with a simple processing. <P>SOLUTION: The image processing apparatus includes: a black letter discrimination means for discriminating a black letter region of read RGB image data; a black letter processing means for providing an output of the black letter region in substantially Bk units when converting the RGB image data into YMCBk; an image storage means for storing the YMCBk image data after being subjected to the black letter processing means; and a black letter extract means for extracting black letters from the YMCBk data stored in the image storage means. <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

  The present invention relates to an image processing apparatus, a network scanner apparatus, and a color digital copying machine, and more particularly to an image processing apparatus, a network scanner apparatus, and a color digital copying machine that perform appropriate image processing without reducing the resolution of characters.

  Compression that performs lossy compression such as a Jpg file has a very high compression rate, and can produce a small file. However, this method is effective for a picture, but for a binary image such as a character image, the edge of the character is blurred and the character is not easily read.

  Therefore, as in the techniques described in Patent Document 1 and Patent Document 2, one file has two high-compression image data and two binary data with high resolution for lossless compression. By selectively switching images with high binary data (character area), it is possible to create a highly compressed image file with high character resolution by outputting character edges with binary resolution. It is said.

However, when extracting character data, when separating a character area and a non-character area, if a rough dot (for example, a photographic part of a newspaper) is used as a character, the lossless compression rate is poor if discontinuous points occur. It is known to be.
Further, it is known that even in a natural image such as a normal person, when the binarization is performed with a high density, many discontinuous points are generated and the compression rate is deteriorated.

In addition, the technique described in Patent Document 3 is for identifying a binary image area composed of characters and lines and a halftone image area such as a photograph or halftone printing for input image data. After generating the image area separation data, the input image data and the image area separation data are compressed and stored. Next, the stored image data and image area separation data are read and decompressed, and then the image attribute of the decompressed image data is detected. Then, based on the detected image attribute and the decompressed image area separation data, the image processing to be performed on the decompressed image data is determined, and the determined image processing is performed on the decompressed image data. I applied.
As a result, although the capacity of the image memory is reduced by the compression process, even when a manuscript image in which characters / photographs are mixed is input, appropriate image processing can be performed on both, and the reproduced image can be reproduced. Image quality deterioration can be reduced as much as possible.
JP 2002-368986 A Japanese Patent No. 393086 Japanese Patent No. 3134756

  However, in the above-described prior art, character extraction performed after decompression must refer to a plurality of pixels or perform character determination using a plane different from that of image data, and thus requires complicated processing.

  The present invention has been made in consideration of the above circumstances, and provides an image processing apparatus, a network scanner apparatus, and a color digital copying machine that can accurately extract black characters from image data by simple processing. For the purpose.

In order to solve the above-mentioned problem, the invention of the image processing device according to claim 1 is characterized in that the black character area is substantially determined when converting from RGB to YMCBk, black character determination means for determining the black character area of the read RGB image data. Black character processing means for outputting in Bk single color, image storage means for storing YMCBk after execution of the black character processing means, and black character extraction means for extracting black characters from YMCBk data stored in the image storage means It is characterized by.
According to a second aspect of the present invention, in the image processing apparatus according to the first aspect of the present invention, the image processing apparatus further comprises correction means for correcting image data based on the result of the black character extraction means.

  An invention of the network scanner device according to claim 3 is an image input means for reading an image and converting it into RGB image data, and an image processing result obtained by processing the RGB image data with the image processing device according to claim 1 or 2. Transmitting means for transmitting to the external device via a network.

  According to a fourth aspect of the present invention, there is provided an image input means for reading an image and converting it into RGB image data, and image processing for processing the RGB image data by the image processing apparatus according to claim 1 or 2. Image output means for outputting the result to a sheet.

  According to the present invention, since the black character determination result is directly extracted from the image data, it is not necessary to have the black character determination result in another plane at the time of accumulation, and the black character can be extracted accurately.

Hereinafter, preferred embodiments of the present invention will be described with reference to the drawings.
FIG. 1 is a block diagram showing a schematic configuration of a digital color image processing apparatus according to the present embodiment.

(A) When operating as a copying machine:
The scanner reads image data from a document, converts the image data (analog signal) into digital data (600 dpi), and outputs the digital data.
As will be described later, the scanner correction unit classifies the image area of the image data (digital data) read by the scanner into characters, line drawings, photographs, etc., removes the background image of the original image, Image processing such as conversion processing of RGB data into YMCBk is performed.
The compression processing unit compresses the YMCBk 8-bit image data after scanner correction, and sends the data to the general-purpose bus. The compressed image data is sent to the controller through the general-purpose bus. The controller has a semiconductor memory (not shown) and accumulates transmitted data.

Although the image data is compressed here, the data may be handled in an uncompressed state if the bandwidth of the general-purpose bus is sufficiently wide and the capacity of the HDD to be stored is large.
Next, the controller sends the image data of the HDD to the decompression processing unit via the general-purpose bus.
The decompression processing unit decompresses the compressed image data to the original YMCK 8-bit data and sends it to the printer correction unit. The printer correction unit performs γ correction processing, halftone processing, and the like, and performs correction processing of the light / dark characteristics of the plotter and gradation number conversion processing. In the tone number conversion process here, image data is converted from 8-bit to 2-bit for each color using error diffusion and dither processing. The plotter is a transfer paper printing unit that uses a laser beam writing process, draws 2-bit image data as a latent image on a photoconductor, and forms a copy image on the transfer paper after image formation / transfer processing with toner.

(B) When operating as a network scanner that distributes image data to a PC:
The image data read by the scanner, corrected by the scanner correction unit, and compressed by the compression processing unit is sent to the controller through the general-purpose bus. The controller performs gradation processing, formatting processing, and the like. In the gradation processing, gradation conversion processing is performed according to the mode during the distribution scanner operation. In the format process, general-purpose image format conversion to JPEG or TIFF format is performed. Thereafter, the image data is distributed to an external PC terminal via a NIC (Network Interface Controller).

(C) When operating as a network printer that prints out from a PC:
The image data sent in the same manner as the network scanner is received from the NIC, and the controller analyzes the image and a command for instructing the print from the received data, and develops a bitmap into a printable state as image data, The expanded data is compressed and stored. The accumulated data is written to a hard disk drive (HDD) which is a large capacity storage device as needed.

Next, the controller sends the image data of the HDD to the decompression processing unit via the general-purpose bus. The decompression processing unit decompresses the compressed image data to the original 8-bit data and sends it to the printer correction unit.
The printer correction unit performs γ correction processing, halftone processing, etc. independently for each YMCBk, and performs correction processing for the light / dark characteristics of the plotter and tone number conversion processing. In the tone number conversion process here, image data is converted from 8 bits to 2 bits using error diffusion or dither processing.
The plotter is a transfer paper printing unit that uses a laser beam writing process, draws 2-bit image data as a latent image on a photoconductor, and forms a copy image on the transfer paper after image formation / transfer processing with toner.

(D) When operating as a digital image processing apparatus:
In general, an original is read by a scanner, image data is converted into digital data, and an image area (image area) of the original is classified into areas having different characteristics (image area separation). Various image processing is performed on the image data according to the determination result as to which region the pixel of interest belongs to. This greatly improves the image quality of the output image.

Next, the scanner correction unit will be described in detail with reference to FIG.
The scanner correction unit performs image area separation based on image data img (reflectance linear) input from the scanner. The image area separation in this embodiment is assumed to be divided into three areas described in JP 2003-259115 A, a black character edge area, a color edge character area, and the other (photo area).
By performing the image area separation, an image area separation signal (a black edge character area, a color edge character area, and a photograph area) is added to the image data for each pixel.
The scanner γ unit converts the image data from reflectance linear to density linear data.

  The filter processing unit switches the filter processing according to the image area separation signal. In the character area (black edge character and color edge character), sharpening processing is performed with emphasis on legibility. In the photographic area, in order to make the characters in the picture easy to read, a sharp density change in the image data is used as an edge amount, and smoothing processing or sharpening processing is performed according to the edge amount.

The color correction processing unit converts R, G, and B data into C, M, and Y data by a primary density masking method or the like except for the black edge character region. In order to improve the color reproduction of the image data, the common portion of the C, M, and Y data is subjected to UCR (additional color removal) processing to generate Bk data, and the C, M, Y, and Bk data are output. Here, the black edge character area is equivalent to the luminance of the black character area because the black character of the original is colored due to the RGB reading position deviation of the scanner or the overlapping position deviation when the YMCK printer of the plotter is misaligned. Output as Bk single color data (data that does not print out C, M, and Y).
In the character γ portion, in order to improve the contrast of the character portion, γ is raised with respect to the color character and the black character.

Next, the printer correction unit will be described in detail with reference to FIG.
The γ correction processing unit performs γ correction processing on the image data that has passed through the compression processing unit and the expansion processing unit according to the frequency characteristics of the plotter.
The edge amount detection unit detects a steep density change in the image data as an edge amount.
The halftone processing unit performs gradation correction by performing quantization such as dither processing and error diffusion processing according to the gradation characteristics and edge amount of the plotter. It is also possible to enhance the contrast of black characters by performing black character signals (black character extraction processing described later) during quantization processing, thereby improving the legibility of the characters.

Next, the controller unit will be described in detail with reference to FIG.
When outputting image data to an external device, the image data is extracted from the page memory storing the image data img, and the compression / decompression processing unit decompresses the compressed image data into 8-bit data of each original color. Output to the output format converter. The output fort conversion unit performs color conversion of C, M, Y, and Bk data to RGB data, and simultaneously performs general-purpose image format conversion to JPEG or TIFF format. The data i / f unit outputs the data color-converted by the output format conversion unit to the NIC.

When image data received from an external device is output to a plotter, a command (not shown) is analyzed by a CPU (not shown) and written to the page memory. The data i / f unit develops the image data into bitmap data by the input format conversion unit, compresses it by the compression / decompression processing unit, and writes it to the page memory.
The image developed with the input format data is a natural image of jpg or tiff.

Next, the output format conversion unit will be described in detail with reference to FIG.
The color conversion unit converts the YMCBk data into RGB data. Data converted to RGB is subjected to pixel density conversion such as 300 dpi and 200 dpi in the resolution conversion unit. In the present embodiment, the pixel density when converted at 300 dpi will be described.
The resolution-converted image is converted into each format by each format generation unit (TIF format generation unit, Jpg format generation unit, compression format generation unit). The data i / f part outputs a format to be output to the NIC.

The compression format generation unit will be described.
A binarization unit outputs binary data of a character area and a non-character area based on the lightness and darkness of the image density.
The binary image generation unit performs MMR compression that is reversible conversion.
In the resolution conversion units 1 and 2, resolution is reduced by converting the resolution of the image data (150 dpi). Here, the character image and the background image need not have the same resolution as the background image, and may be about 75 dpi.
Further, in the background image generation unit, in order to improve the compression ratio, the image data of the region that has become the character region in the binarization unit is converted into image data having a constant value corresponding to white, and irreversible compression jpg Perform compression.
Further, the character image generation unit performs rewrite irreversible compression jpg compression using the image data of the region that has become the background region as a constant value of image data in order to improve the compression rate.

  In the image file composition unit, three images, that is, the output from the binary image generation unit (MMR), the output from the background image generation unit (jpg), and the output from the character image generation unit (jpg) are made into one file (see FIG. 6). ). The file format at this time may be a general-purpose format (for example, a PDF file).

  Next, the processing of the binarization unit that performs binarization by extracting a plurality of feature amounts will be described in detail with reference to FIG. The following processes 1 to 12 are sequential processes. When one process is completed, the adjacent pixel is processed. When one line is completed, the process is performed from the beginning of the next line and the process is continued until the end of the image. Become.

1. Black character extraction processing:
A black character edge signal is extracted from the YMCBk image. Since the color correction processing unit of the scanner correction unit outputs the Bk single color in the black character edge region, if reversible compression is used, Y = M = C = 0 (there are no Y, M, and C color components), and If the Bk data is greater than or equal to a certain value (darker than the certain value), it is a black character edge.
However, when irreversible compression is performed, the black character edge is not always Y = M = C = 0. Therefore, if all the values of YMC are equal to or smaller than a certain value (thinner than the certain value), the black character edge is present. I reckon. In this way, the same result as the black character edge processing at the time of copying can be obtained.

2. Resolution conversion:
Resolution conversion (300 dpi) is performed at the same resolution as that applied to the image so that the image data and the pixel density are the same. This output is black.

3.3 × 3 filter:
In order to extract character features, a 3 × 3 filter for enhancing the image is applied to each of RGB.

4.2 Binarization:
Here, the data (bk) having a small RGB difference is a black character when the value is larger than thabk, and the data having a small RGB difference is divided into six hues of YMCBGR, and threshold values (thay, tham, thac, (bin, thag, tha) are divided and binarization processing is performed, and binarization processing is performed with a dark color as an active pixel (character).
Here, the threshold value is divided for each hue because the maximum density of the input image (original) of YMCBk is different. Further, the threshold value of bk is also divided for the same reason. Further, the method of dividing the hue may be simply performed based on the RGB size relationship, or may be determined by the ratio of the RGB colors. This is determined by the characteristics of the input image.

5). Character detection 1:
The output of the binarization unit performs pattern matching on the active pixel. For example, if the pattern is as shown in FIG.

6). Character detection 2:
The result of character detection 1 is slightly smaller than the image data due to the pattern matching. Therefore, 3 × 3 OR processing is performed on the presence of the black pattern to thicken the data, and this result is used as a character region.

7). N-value:
In the N-value conversion, the features of halftone dot detection and gray detection, which will be described later, are used in common as N-value values.
Data with a small RGB difference (bk) is a black character when the value is larger than thabk, and data with a large RGB difference is divided into six colors of YMCBGR, and threshold values (thay, tham, thac, thab, The binarization process is performed separately for the “thag” and the “thar”, and the binarization process is performed with a dark color as an active pixel (character). However, the output result is held for each hue and defined as follows (the values in parentheses are displayed in bits).

Dtah = 0 (000): Not applicable,
Dtah = 1 (001): yellow,
Dtah = 2 (010): Magenta,
Dtah = 3 (011): red,
Dtah = 4 (100): cyan,
Dtah = 5 (101): green,
Dtah = 6 (110): blue,
Dtah = 7 (111): Black.

  Further, the white level is also binarized in the same manner. Data with a small RGB difference (bk) is a white pixel when the value is smaller than thbbk, and data with a large RGB difference is divided into six hues of YMCBGR, and threshold values (thby, thbm, thbc, thbb, thbg) for each hue. , Thbr) is divided and binarization processing is performed, and binarization processing is performed with light-colored pixels as active pixels (white pixels).

8). Halftone detection 1:
In halftone dot detection 1 and 2, fine halftone dots in the scanner correction unit have been eliminated by smoothing processing, but rough halftone dots such as newspaper photographs cannot be smoothed sufficiently. In addition, the dot shape of the halftone dot remains, and the object is to detect this rough halftone dot.
Here, halftone dot pattern matching is performed. Here, a black pixel is set when Dtah ≠ 0, and an N-valued white pixel is set as a white pixel.

  Hereinafter, the processing procedure of halftone detection 1 will be described with reference to the flowchart of FIG. In FIG. 9, MS is the processing result of the previous pixel, i is the pixel position in the main scanning direction that is currently processed, and SS [i] is the processing result of the previous line.

By comparing MS and SS [i], the larger one of the processing result of the previous line and the processing result of the previous pixel is obtained (steps S1 and S2). This MS is a halftone dot count value (to be described later) as a result of processing one pixel before.
If the white pixel matches the white pattern (see FIG. 10) (YES in step S3), MS is set to 0 (step S4), a non-halftone pixel (step S8), and SS [i] = MS ( = 0), SS [i] is used in the next line (step S10).

  On the other hand, if it does not match the white pattern (NO in step S3) and matches the halftone dot pattern (YES in step S5), 1 is added to the MS (step S6). Here, the halftone dot pattern is the pattern shown in FIG. 11, where ● represents a black pixel and ○ represents a non-black pixel. Further, in order to improve halftone dot detection accuracy, in order to determine non-black pixels, the number of conditions including white pixels may be increased to increase accuracy.

Next, if MS> 5 (YES in step S7), a halftone dot pixel is set (step S9), SS [i] = MS is used, and SS [i] is used in the next line (step S10).
On the other hand, if MS> 5 is not satisfied (NO in step S7), a non-halftone pixel is set (step S8), SS [i] = MS is used, and SS [i] is used in the next line (step S10).
As described above, a halftone pixel can be determined.

9. Halftone detection 2:
Hereinafter, the processing procedure of the halftone detection 2 will be described with reference to the flowchart of FIG. Here, halftone dot detection 1 is processed in the forward direction, but halftone dot detection 2 is processed in the reverse direction. In FIG. 12, MS represents the state of whether or not the pixel currently being processed is a halftone dot.

  If the white pixel matches the white pattern (see FIG. 10) (YES in step S11), MS = 0 (step S12) and a non-halftone pixel is set (step S13).

  On the other hand, if it does not coincide with the white pattern (NO in step S11), if it is a pixel that has become a halftone pixel in the halftone detection 1 (YES in step S14), MS = 1 is set (step S15).

If MS = 1 (YES in step S16), it is output as a halftone pixel (step S18).
On the other hand, unless MS = 1 (NO in step S16), the result of halftone dot detection 1 (halftone dot / non-halftone dot) is output as it is (step S17).
If the output result is a halftone dot, the halftone dot region is set.

By performing halftone dot detection 1 and halftone dot detection 2 as described above, if there is a certain halftone dot pattern between the white pattern and the white pattern, it is detected as a halftone dot. This is because characters are generally on the white ground, and characters on the white ground are rarely erroneously detected because the halftone dot pattern is only near the edge of the character.
The same processing (halftone detection 1, 2) is performed using color data having a Y component (yellow, green, red, black) as a black pixel. Further, color data having M component (red, magenta, blue, black) and color data having C component (cyan, blue, green, black) are similarly subjected to Y component. The reason for developing the Y, M, and C components is to accurately detect ink dot reproduction because the printing ink component is YMC.

10. Gray detection 1:
In the gray detections 1 and 2, the fact that the character area is dark and the area around the character is light is used, and gray determination is performed with the density that is lighter than the character area and darker than the area around the character as medium density.
The processing procedure of gray detection 1 will be described using the flowchart of FIG. In FIG. 13, MS is the processing result of the previous pixel, i is the pixel position in the main scanning direction currently being processed, and SS [i] is the processing result of the previous line.

  By comparing MS and SS [i], the processing result one line before and the value having the larger processing result one pixel before are obtained (steps S21 and S22). Here, MS is the number of white pixels after gray detection (described later).

  If the medium density matches the gray pattern (see FIG. 14) (YES in step S23), MS = 5 (step S24), a gray pixel (step S30), SS [i] = MS, SS [i ] Is used in the next line (step S31). Here, the medium density is the density of a pixel when Dtah = 0 and a non-white pixel when N-valued.

  On the other hand, if it does not coincide with the gray pattern (NO in step S23) and is a white pixel (YES in step S25), the process proceeds to step S26. Here, the white pixel is a white pixel when N-valued.

If MS> 0 (YES in step S26), 1 is subtracted from MS (step S27), and the process proceeds to step S29.
If MS> 0 is not satisfied (NO in step S26), non-gray pixels are set (step S28), SS [i] = MS is used, and SS [i] is used in the next line (step S31).

On the other hand, if it is not a white pixel (NO in step S25) and MS> 0 (YES in step S29), the pixel is a gray pixel (step S30), SS [i] = MS, and SS [i] is the next line. (Step S31).
If MS> 0 is not satisfied (NO in step S29), non-gray pixels are set (step S28), SS [i] = MS is used, and SS [i] is used in the next line (step S31).

11. Gray detection 2:
Hereinafter, the processing procedure of the gray detection 2 will be described with reference to the flowchart of FIG. Here, gray detection 1 is processed in the forward direction, but gray detection 2 is processed in the reverse direction. In FIG. 15, MS represents the processing result of the previous pixel, i represents the pixel position in the main scanning direction currently being processed, and SS [i] represents the processing result of the previous line.

  If the result of gray detection 1 is a gray pixel (YES in step S41), MS = 5 (step S42), gray pixel, SS [i] = MS, and SS [i] is used in the next line (step S48).

On the other hand, if the result of gray detection 1 is not a gray pixel (NO in step S41) and is a white pixel (YES in step S43), if MS> 0 (YES in step S44), one is subtracted from the MS. (Step S45), the process proceeds to step S47. Here, the white pixel is a white pixel when N-valued.
If MS> 0 is not satisfied (NO in step S44), the result of gray detection 1 is output as it is, and SS [i] = MS is used as SS [i] in the next line (step S46).

If MS> 0 (YES in step S47), the gray pixel, SS [i] = MS is set, and SS [i] is used in the next line (step S48).
If MS> 0 is not satisfied (NO in step S47), the result of gray detection 1 is output as it is, and SS [i] = MS is used as SS [i] in the next line (step S46).

  As described above, the character portion is generally composed of dark data and light (white) data, and a medium-density block, which is a feature of a photograph that does not exist in the character portion, is detected as gray. These peripheral pixels are gray pixels until the number of white pixels exceeds a certain value. As a result, the result of gray pixels is defined as a gray region.

12 Judgment:
Judgment is made as follows from the above result, and binarized data of YMCBk image data is obtained.
(1) If the output result of resolution conversion is a black character, the binarized data result is a character.
(2) If the output of the character detection 2 is a character region, the output of the halftone detection 2 is not a halftone region, and the output of the gray detection 2 is not a gray region, the result of the binarized data is taken as a character.

The reason why the character area is subjected to the logical operation with the halftone dot area and the gray area is that the character determination result is a photographic area that originally does not require resolution, and is corrected in the photographic area.
In particular, the photographic area contains a large number of isolated points. By performing this correction, the compression rate of the character image is improved, and the image is less mixed with characters and non-characters.
On the other hand, a black character is a signal having a black character edge at the time of copying, and has high determination accuracy. Therefore, there is no problem even if it is used as it is.

Next, the input format conversion unit will be described in detail with reference to FIG.
If the input image data is in the tif format, the TIF format development unit develops it into bitmap data. In the case of the Jpg format, the Jpg format development unit develops it into bitmap data. Furthermore, if it is a compression format, it expand | deploys in a compression format expansion | deployment part.
The output selection unit selects one of these three formats, and simultaneously converts the RGB data into YMCBk and outputs it.

Further, the compression format developing unit will be described.
The image file expansion unit converts three files among the files generated by the compression format generation unit in FIG. 5 into image data corresponding to the binary image expansion unit, the background image expansion unit, and the character image expansion unit, respectively. Output.

The binary image expansion unit expands the MMR and expands it into a bitmap, the background image expansion unit expands the background image Jpg into a bitmap, and the character image expansion unit expands the character image Jpg into a bitmap. If the output of the binary image development unit is a character region, the image data that is the output of the character image development unit is output. If the output of the binary image development unit is a non-character region, the output of the background image development unit Output some image data.
Then, the bitmap data expanded into three is synthesized into one piece of bitmap data by the image file synthesis unit to generate one image (see FIG. 6). Here, the resolution of characters and non-characters is the same as the resolution of the binary image.

1 is a block diagram illustrating a schematic configuration of a digital color image processing apparatus according to an embodiment. It is a block diagram which shows the structure of a scanner correction | amendment part. It is a block diagram which shows the structure of a printer correction | amendment part. It is a block diagram which shows the structure of a controller part. It is a block diagram which shows the structure of an output format conversion part. It is an image figure of an input image, a file image, and an output image. It is a block diagram which shows the structure of a binarization part. It is an example of a black pattern. It is a flowchart explaining the process sequence of the halftone detection 1. FIG. It is an example of a white pattern. It is an example of a halftone dot pattern. It is a flowchart explaining the process sequence of the halftone detection 2. FIG. It is a flowchart explaining the process sequence of the gray detection 1. FIG. It is an example of a gray pattern. It is a flowchart explaining the processing procedure of the gray detection 2. FIG. It is a block diagram which shows the structure of an input format conversion part.

Claims (4)

  Black character determining means for determining the black character area of the read RGB image data, black character processing means for outputting the black character area in a substantially Bk single color when converting from RGB to YMCBk, and storing YMCBk after execution of the black character processing means An image processing apparatus, comprising: an image storage unit configured to extract a black character from YMCBk data stored in the image storage unit.   The image processing apparatus according to claim 1, further comprising a correction unit that corrects image data based on a result of the black character extraction unit.   An image input unit that reads an image and converts it into RGB image data, and a transmission unit that transmits an image processing result obtained by processing the RGB image data by the image processing apparatus according to claim 1 to an external device via a network. A network scanner device comprising:   Image input means for reading an image and converting it into RGB image data; and image output means for outputting an image processing result obtained by processing the RGB image data with the image processing apparatus according to claim 1 to paper. Color digital copier characterized by