JP2006172291A - Image processing device - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an image processing device capable of calling data held in a storage device only by reading an outputted item by means of a reader for allowing simple setting change/correction on the spot. <P>SOLUTION: An MFP holds data in the storage device after outputting PDL data. In this process, the PDL data and index information associated with the PDL data are held simultaneously. In correction, the outputted item is read by a scanner, and then, the read data and the data held in the storage device are searched by means of some search means, recognized, and extracted. After extraction the data are displayed for urging the user to make a correction, and after correction, the data are outputted. <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

  The present invention relates to an image processing apparatus that collates and extracts data held in a temporary storage device with image data read by a reading device, and efficiently outputs the data held in the temporary storage device.

As a means for collating and extracting image data read by a reading device and data stored in a storage device in advance, a code indicating an ID is embedded in the image, the ID is detected at the time of reading, and matches the ID code. It is common to search for data to be performed (see, for example, Patent Document 1).
Japanese Patent Laid-Open No. 10-285378

  However, in the conventional technique described above, since it is necessary to embed an ID in an image in advance and print it at the time of output, only a specific document can be handled, and there is no versatility.

  The present invention has been made paying attention to the above-described problems, and an image processing apparatus that can read data held in a storage device by simply reading an output output in the past with a reading device. The purpose is to provide.

In order to solve the problems described above, the present invention provides:
Data holding means for holding external input data input from the outside;
First feature value generation means for generating a first feature value from the external input data;
Feature quantity holding means for holding the first feature quantity generated by the first feature quantity generation means;
Output means for outputting the external input data held by the data holding means;
An image reading unit that reads an output image output by the output unit,
Second feature quantity generation means for generating a second feature quantity from the image read by the reading means;
Feature quantity matching means for matching the second feature quantity generated by the second feature quantity generation means with the first feature quantity held in the feature quantity holding means;
Specific external input data is selected from the external input data held in the data holding means in accordance with the result of the feature amount matching means.

  According to the present invention, it is possible to easily collate and extract image data read by a reading device and data previously stored in a storage device. As a result, the data held in the storage device can be read simply by reading the output product output in the past with the reading device, and the convenience for the user is improved during reprinting.

  Hereinafter, the best mode for carrying out the present invention will be described in detail with reference to examples.

  Hereinafter, an embodiment of the present invention will be described with reference to the drawings.

  FIG. 1 is a block diagram showing an example of a configuration for carrying out the present invention.

[Reading section]
A document to be copied is placed on a document placing table glass (not shown) of the scanner unit 101 and read. As in FIG. 10, the scanner unit digitally reads an original image pixel by pixel with a color 3-line CCD and transfers a color image signal to the first input image processing unit 102. The input image processing unit 102 performs known image processing such as shading correction, CCD line correction, and color correction on the RGB color image signal sent from the scanner unit.

  Reference numeral 103 denotes a block that performs image area separation processing on the color image signal that has been processed by the input image output from 102, and detects image features such as a photo area, a character area, and a dot area for each pixel of the input image. Thus, the image area separation processing unit generates flag data representing an attribute for each image area.

[Image area separation processing]
Here, the image area separation processing unit will be described.

  The image area separation process is for extracting a feature of an original image and generating a signal indicating an image area attribute (hereinafter referred to as flag data) in order to perform optimum image processing according to the feature of the image included in the original image. To be done. For example, in a document, various image areas such as a continuous tone full-color photographic area, a black-colored character area, or a halftone dot printing area such as newspaper printing are usually mixed.

  If these are uniformly processed by the same image processing procedure and output, the output image generally does not often have a desirable image quality.

  Therefore, in the present invention, the attribute of the image data included in the document image is detected using the color image signal input from 102, and flag data for identifying the attribute is generated. A specific procedure is shown in FIG.

  FIG. 2 shows an example of an original image, and shows a state in which a silver halide photograph area 202, a black character area 203, a halftone dot print area 204, and a color graphic area 205 are mixed in one page 201. .

  Here, the scanner unit scans the original image with a color CCD sensor and reads it as a color digital signal (R, G, B) for each pixel. The read RGB signal has a characteristic determined by an attribute for each region of the image. FIG. 3 shows, for example, a plot of the G signal among the signal values (R, G, B) read by the CCD sensor in each region in the CCD arrangement direction.

  3, 302, 303, 304, and 305 are examples of characteristics that appear characteristically when the areas 202 to 205 in FIG. 2 are read. The horizontal axis represents the pixel position in the CCD arrangement direction, and the vertical axis represents the read. This indicates that the pixel value is closer to white (brighter) as it goes upward in the signal value.

  The characteristics of each region will be described. Since 202 is a photographic region, the change 302 depending on the position of the image signal to be read is relatively gentle, and the difference 312 between the pixel values in the short distance is a small value.

  Reference numeral 303 denotes a characteristic of the black character region 203. Since black characters are written on a white background, the signal value plot has such a characteristic that the read signal value changes rapidly from the white background portion 313 to the character portion 323.

  Reference numeral 304 denotes a characteristic of the halftone dot area 204. The halftone dot area is a repetition of the white background 314 and the halftone dot 324 printed thereon, so that the signal values plotted are white and black as shown in the figure. It becomes a characteristic that repeats frequently.

  305 is a plot diagram of the graph area. In the graphic edge portion 315, the signal value is abruptly decreased, and the internal colored portion 325 has a characteristic that a certain intermediate level continues.

  In order to determine these attributes, the characteristics for each region as described above may be detected and determined from the read signal value. For this purpose, the amount of change in the image data in the vicinity of the target pixel, or the integrated value of the amount of change within a certain interval, the luminance value of the surrounding pixels (whether white or colored background), the white of the image data within the certain interval A feature extraction method using a known method such as the number of changes to black can be used, and a known attribute discrimination method based on the feature extraction method can be used.

  FIG. 4 shows an example of the attribute flag generated for the document image shown in FIG. Here, three types of flags, a character flag, a graphic flag, and a halftone dot flag, are generated as attribute flags (flag data), but of course the invention is not limited thereto. FIG. 4A shows a character flag. Pixels represented by black in the drawing are pixels having character attributes, and character flag = 1 is generated. Otherwise, character flag = 0 (white portion in the figure). Yes. (B) is a graphic flag which is 1 in the graphic area and 0 otherwise. (C) is a halftone dot flag which represents an area which is 1 in the halftone area and 0 otherwise. Yes.

  Since the photographic area does not correspond to any of these, all the flags are 0, and they do not appear in FIG.

  Next, an example of a color flag generation method will be described.

  In order to determine whether a certain pixel of image data is a color, it is easily determined by mapping the chromaticity of the pixel on the color space. As an example, a Lab color space will be described as an example.

  The Lab color space is a color space proposed by the CIE (Commission Internationale de l'Eclairage) in 1976 as a uniform perceptual color space. L represents lightness (brightness), a represents chromaticity from red to green, and b represents chromaticity from blue to yellow. In the Lab color space, the amount of change in the three-dimensional color space is corrected so as to be proportional to the impression of the visual color change caused by the change, so that highly accurate color discrimination is possible.

An example of converting RGB signals into Lab signals is shown. Usually, XYZ tristimulus values are once calculated from RGB signals, and then Lab signal values are derived from the XZY tristimulus values. An example is shown. The coefficient of the conversion formula in the example is not limited because it depends on the device.
X = 0.412391 × R + 0.357584 × G + 0.180481 × B
Y = 0.1212639 * R + 0.715169 * G + 0.072192 * B
Z = 0.0193331 × R + 0.119195 × G + 0.950532 × B
L = 116 (Y / Y0) ^(1/3) −16
a = 500 ((X / X0) ^(1/3) -(Y / Y0) ^(1/3) )
b = 200 ((Y / Y0) ^(1/3) -(Z / Z0) ^(1/3) )
However, X0, Y0, and Z0 are tristimulus values in standard light. The ab value of each pixel calculated from the above equation is mapped to an orthogonal coordinate system to determine whether the pixel is chromatic or achromatic. An example is shown in FIG. The a-axis 901 and the b-axis 902 represent respective axes of the orthogonal coordinate system. In the determination of chromatic or achromatic color, for example, when saturation is used as a reference, in this coordinate system, the intersection of the a-axis 901 and the b-axis 902, that is, the origin is a point where the color component is zero. The saturation increases as the distance from the origin increases, that is, as the values of a and b increase. In the process of changing the saturation, it is determined whether the color is a chromatic color or an achromatic color with a certain size as a threshold value. For example, assuming that the hatched portion 903 is an achromatic region, if the ab value of a certain pixel is at 904 inside the hatched portion 903, this pixel is determined to be an achromatic color. When the ab value of a certain pixel is at 905 outside the shaded portion 903, this pixel is determined to be a chromatic color.

  By taking the above method, it is possible to determine whether a pixel is a chromatic color or an achromatic color.

  The conversion to chromaticity has been described using Lab, but is not limited thereto. In order to reduce the amount of calculation, a simple conversion formula may be used.

  When the image attributes are detected for each pixel by the above image area separation processing, the second input image processing unit 104 performs image processing according to the image attributes.

  Here, for example, the high frequency component of the image is emphasized for the character area to enhance the sharpness of the character, and the so-called low-pass filter processing is performed for the dot area to remove the moire component peculiar to the digital image. Can be performed. These processes can be switched in units of pixels according to the attribute flag data generated in 103.

[Storage of image data]
The image data read by the scanner and subjected to various input image processing and the attribute flag data generated by the above procedure are temporarily stored in the image memory 1 105 and the flag memory 1 106. At this time, the image data and the attribute flag data are stored as a partial image of the entire original page or a predetermined size of one page.

  The temporarily stored image data and attribute flag data are compressed by the data compression unit 109 and stored in the storage device 110. 110 is preferably a high-speed storage means such as a semiconductor memory device. The data compression unit performs different data compression processes on the image data and the flag data. In other words, image data is irreversible like JPEG compression, but it is subjected to highly efficient compression processing that makes image degradation inconspicuous in consideration of human visual characteristics. Therefore, it is desirable to use a reversible compression method such as JBIG compression because no attribute flag information is lost or changed.

  In this way, the image data and the flag data subjected to different compression processes are stored in the original 110 in units of one page. The stored data may also be written to 111 auxiliary storage devices. The auxiliary storage device is preferably a medium such as a hard disk that can store a large amount of data although the recording speed is slightly slow. By doing so, it is possible to efficiently store and accumulate a large number of pages of document images.

[Reading image data]
The image data and attribute flag data stored in 110 or 111 are read out for output from the print unit, and the compressed data is decompressed by 112 data decompression units, respectively. It is written to the flag memory 2.

  At this time, the pixel density conversion unit 113 may convert the pixel density of the stored image data. This is used, for example, when it is desired to print out the enlarged image data by enlarging or reducing the accumulated image data, or when it is desired to combine and output a plurality of accumulated pages on one print output sheet.

  For example, the composite output of a plurality of pages is as shown in FIG. That is, it is assumed that two document images 501 and 502 are stored in the storage device in advance. This is a case where a print output such as 503 is obtained by combining two sheets on output paper of the same size as the original.

  For this purpose, first, the stored image data 501 is read from the storage means, and the compressed data is decompressed, reduced at a predetermined magnification by the pixel density conversion unit 113, and rotated 90 degrees to the left by a rotation processing unit (not shown). It is written in a predetermined area of the image memory 2 (area corresponding to 504 in FIG. 5).

  Next, the image data 502 is read out, similarly decompressed, converted in resolution, and rotated, and written in an area corresponding to 505 in the image memory 2.

  At this time, the flag data corresponding to the originals A and B are similarly decompressed, resolution-converted and rotated, and written in the corresponding area of the flag memory 2.

  Here, it is desirable to apply different methods to the resolution conversion of image data and the resolution conversion of flag data. For example, a known method such as a linear interpolation method or a bicubic spline interpolation method can be applied to image data. For the resolution conversion of flag data, it is desirable to use a resolution conversion method suitable for binary data such as nearest neighbor processing.

[Output image data]
The image data and flag data temporarily stored in the image memory 2 and the flag memory 2 are transferred to the output image processing unit 116 when reaching a predetermined size.

  The output image processing unit 116 performs well-known image processing for printing out RGB image data, that is, luminance density conversion, RGB → CMYK conversion, gamma correction, binarization processing, and the like, and transfers them to the printer unit 117. To do.

  The printer unit 117 is laser-driven by the transferred CMYK image signal, and forms and outputs a visible image on the transfer paper in the same procedure as in FIG.

  Here, the flag data stored in the flag memory 2 is used for switching the processing of the output image processing unit 116. That is, the image quality of the output image can be improved by making the coefficient of RGB → CMYK conversion different between the photo area and the character area. For example, for a pixel having a character region, ie, a character flag = 1, a conversion coefficient such that a black character can be reproduced only with black toner (that is, a coefficient such that C, M, Y = 0 when the image data is achromatic) In other cases, C, M, and Y do not become 0 even if the color is achromatic, and a coefficient that can reproduce deep black can be used.

  In the binarization process, the C, M, Y, and K signals are converted into a binary signal of 0 or 1 using a known error diffusion process or dither process. At this time, an output image is output in the character area or the graph area. Since the sharpness of the image is given priority, the error diffusion process is applied, and the dithering process is applied because the gradation is emphasized in the photograph and the halftone area. The image quality of the output image can be improved by switching according to.

  An example of a block diagram of the configuration at this time is shown in FIG.

  The image memory 2 114, the flag memory 2 115, and the printer unit 117 are the same as those in FIG. The RGB color image data read from the image memory 2 is input to two RGB → CMYK conversion circuits 601 and 602 in parallel, and converted into CMYK image signals, respectively. One of the outputs 601 and 602 is selected by the selector 1 603 in accordance with the flag signal of the flag memory. When the conversion coefficient for the character area is set in 601 and the coefficient in other cases is set in 602, the output of 601 is selected when the character flag in the flag memory = 1, and the character flag = When 0, the output of 602 is selected.

  The output of the selector 1 is also separated into two systems in parallel, one of which passes through the gamma correction circuit 1 of 604 and the error diffusion binarization processing unit of 606 and is input to the selector 2 of 608 as a binary CMYK signal. .

  The other is passed through the gamma correction circuit 2 of 605 and the dither processing binarization circuit of 607 and is also inputted to the selector 2 of 608 as a binary CMYK signal.

  The selector 2 selects either the output 606 or 607 and transfers it to the printer unit. Here, since error diffusion processing is selected in the character area and the graph area, the selector when the character flag = 1 or the graphic flag = 1 is selected. 2 may select the output of 606, otherwise the output of 607 may be selected.

[Print image]
Typical image data input from the external communication path 119 through the communication interface 118 is image data described in a so-called PDL (Page Description Language).

  The PDL data input from the communication interface 118 is converted into an intermediate language format called a display list by the interpreter 108. This display list is sent to a RIP (Raster Image Processor) 107 and developed into bitmap data. The developed image data is stored in the image memory 1 105. At this time, the RIP 107 generates attribute information of the developed image data as flag data and stores it in the flag memory 1 106. The flag data refers to the attribute information (such as a photograph or text or graphic) held in each part of the PDL data input to the RIP, and the flag data of the corresponding pixel of the developed image is obtained. It may be generated. That is, when a PDL command for generating a character part is input to the RIP, the RIP generates a bitmap image of the character data, and at the same time, generates a character flag = 1 as flag data corresponding to the area where the character is generated. .

[Forgery determination processing]
There are several methods for forgery determination processing such as banknotes performed in the forgery determination processing 120, but a typical method is pattern matching. Features such as the shape and color of banknotes, or features that are intentionally embedded are extracted, and the degree of coincidence with those stored in advance is determined for determination. An example is shown in FIG.

  An image signal RGB for determination is input to the determination circuit 700. The RGB signal is binarized by the binarization unit 701. The threshold for binarization is variable and is stored in the memory 702. The binarized signal is input to the feature point extraction unit 703, and when it corresponds to the feature stored in the memory 704, the part is cut out. The features stored in the memory 704 are a shape, a color, a specific mark, and the like representing the features of the banknote. It also includes intentionally embedded features.

  The cut out signal is input to the pattern matching unit 705, and when it matches the pattern corresponding to the memory 706, the determination result is transmitted to the control CPU 707. The control CPU 707 that has received the result of forgery prevents the forgery by painting an image to be output by the printer unit.

  The above is an example of the forgery determination process performed by the copying machine, but is not limited thereto.

  Such an image processing system is generally called an MFP (Multi Function Peripheral). By using this MFP, the user can easily print data created on a PC (Personal Computer).

  However, when the user sees the printed matter after output and notices that the printed matter is deficient, even if it is a simple setting change or slight modification, the user purposely returns to the place where the PC is located, and the setting change, contents I had to fix it and reprint it.

  In view of the above, an object of the present invention is to improve the convenience of the user by making a setting change or correction on the MFP and reprinting the user without returning to the PC. Specifically, the output printed matter is read by the MFP, the PDL data is searched and displayed, and the setting is changed and corrected on the MFP.

  Hereinafter, the present invention will be described in detail. FIG. 10 is a diagram showing the flow of the entire process.

  The user prints PDL data from the PC with the MFP (1002), and obtains a temporary print 1003. The user looks at the temporary printed material 1003 and determines whether correction is necessary (1004). If not, the temporary printed material 1003 becomes the final printed material, but if correction is necessary, the temporary printed material is read by the scanner of the MFP (1005). The MFP that has read the temporarily printed material analyzes the read data and searches the MFP for the original data (1006). If there is no data, “NO DATA” is displayed to the user on the UI (User Interface) (1014). If there is data, the search result is displayed on the UI (100). The user changes the print setting or modifies the PDL data on the UI (1009). Thereafter, the image is output again from the MFP (1010), and the output image is confirmed (1011). If there is a problem, change or correct it on the UI again. Repeat as long as there is a problem. If there is no problem, the user is notified of the corrected location and setting (1012).

  The data search unit 1006 will be specifically described. The PDL data to be searched will be described with reference to FIG.

  The PDL data 1101 output from the user's PC is once converted into an intermediate language DL (Display List) 1103 by an interpreter 1102. The DL 1103 is expanded into bitmap data by the RIP 1104 to obtain raster data 1105. Usually, the raster data 1105 is sent to the printer unit and printed.

  At this time, a thumbnail image is generated from the raster data 1105 (1107), and the thumbnail data 1108 is held in the storage device 1110. The storage device 1110 also holds PDL data 1101 or expanded raster data 1105 (1109). Although it is desirable to have both, since there is a limit to the capacity of the storage device, it is sufficient to hold either one. From the viewpoint of image quality, it is desirable to retain PDL data.

  Note that raster data generated from certain PDL data and thumbnail data generated from the raster data are held in association with each other.

  Next, a method for searching the stored PDL data or raster data from the read image will be described with reference to FIG.

  The output 1106 output from the MFP is read by the scanner of the MFP (1201). The read image data is corrected (1202), and further, resolution conversion (1203) is performed in order to match the thumbnail size, thereby obtaining raster data 1204. The image correction 1202 is performed in order to generate a signal equivalent to the original PDL data by correcting skew reading, distortion, etc., or correcting MTF that decreases during printing.

  When the raster data 1204 is obtained, matching is performed with the thumbnail data 1108 held in the storage device 1110 (1205), and a result 1206 is obtained. If the result 1206 identifies the thumbnail data, the PDL data or raster data associated with the thumbnail is displayed on the UI (1008).

  The matching 1206 between the raster data 1204 and the thumbnail data 1108 will be described with reference to FIG.

  Each of the raster data 1204 and the thumbnail data 1108 is converted into N values (1301/1302), and N−1 1-bit images are obtained. At this time, the threshold value for N-value can be set independently. Although the same signal level may be used as the threshold value, different threshold values may be used. Next, matching 1 (1309) of the result image 1 (1303) of the N-value conversion 1301 and the result image 1 (1306) of the N-value conversion 1302 is performed. Here, a well-known pattern matching is performed and the similarity is calculated. For example, the degree of similarity is represented by 100 when the two coincide completely, and the degree of similarity is represented by 0 when they do not coincide at all. .., N-1 (1305) and N-valued 1302 result image 2 (1307),..., N-1 (1308) are matched. To calculate each similarity. Whether the raster data 1205 and the thumbnail data 1108 match is determined based on the calculated N similarities (1312). The determination result is output as a result 1206.

  This matching method is only an example. A well-known pattern matching technique may be used, or images may be matched in a multivalued state.

  By using the above-described method, it is possible to retrieve a document read by the MFP scanner and PDL data or raster data held in the MFP. If there is data as a result of the search, the data is displayed on the UI, the image is confirmed, the output method is changed, and the image is output. When raster data is used, the data is output without being rasterized, so that it can be processed at high speed. When PDL data is used, when scaling is performed, the original data is used for rasterization, so that a high-quality image can be provided.

  In this embodiment, a thumbnail image is used, but the resolution of the thumbnail image may be arbitrary. Further, since the capacity of the storage device is limited, it is only necessary to hold an arbitrary number of thumbnail images, raster data, and PDL data.

  As described above, once the output image is read by the scanner of the MFP, and the data stored in the storage device is automatically searched / displayed, the convenience of the user is improved during reprinting by simple setting change or correction. To do. In addition, it is possible to search at high speed by using thumbnail images.

  In the first embodiment, thumbnail images and scanned images are used to search and collate images by pattern matching of image data. However, since it is necessary to hold raster data, it depends on the capacity of the storage device. Therefore, instead of holding thumbnail images as they are, statistics such as average value, maximum value, minimum value, standard deviation, and histogram are calculated and the statistics are held. FIG. 14 shows a configuration diagram.

  As described above, once the output image is read by the scanner of the MFP, and the data stored in the storage device is automatically searched / displayed, the convenience of the user is improved during reprinting by simple setting change or correction. To do. Further, since the statistics are calculated and stored from the raster data generated at the time of printing, there is little restriction on the capacity of the storage device.

  In this embodiment, a method for searching for an image using attribute information representing the feature of the image will be described. FIG. 15 shows a configuration diagram thereof. The image area separation processing 1507 is the same as the image area separation processing 103 shown in FIG.

  As described in the first embodiment, the attribute information indicates the characteristics constituting the image. For example, in the case of the original image shown in FIG. 2, a silver salt photograph area 202, a black character area 203, a halftone print area 204, and a color graphic area 205 are mixed in one page 201. FIG. 4 shows an example of attribute flags generated by subjecting the original image of FIG. 2 to image area separation processing. Here, three types of flags, a character flag, a graphic flag, and a halftone dot flag, are generated as attribute flags (flag data), but of course the invention is not limited thereto.

  FIG. 4A shows a character flag. Pixels represented by black in the drawing are pixels having character attributes, and character flag = 1 is generated. Otherwise, character flag = 0 (white portion in the figure). Yes. (B) is a graphic flag which is 1 in the graphic area and 0 otherwise. (C) is a halftone dot flag which represents an area which is 1 in the halftone area and 0 otherwise. Yes. Since the photographic area does not correspond to any of these, all the flags are 0, and they do not appear in FIG. Further, the color flag described in FIG. 9 may be handled as attribute information.

  In order to generate the above-described attribute information, as shown in FIG. 15, when the PDL data is output by the MFP, the raster data 1105 is subjected to image area separation processing (1507), and the flag data 1508 is held in the storage device 1110. Keep it.

  The search method has the configuration shown in FIG. The output product 1106 and the MFP are scanned (1601), and the image data is corrected (1602). The image correction 1602 is performed in order to generate a signal equivalent to the original PDL data by correcting skew reading, distortion, etc., or correcting MTF that decreases during printing. An image area separation process 1603 is performed on the signal for which the image correction 1602 has been completed, and flag data 1604 is generated. When the flag data 1604 is obtained, matching is performed with the flag data 1508 held in the storage device 1110 (1605), and a result 1606 is obtained. If the flag data can be identified from the result 1606, the PDL data or raster data related to the flag data is displayed on the UI (1008). The user sees the displayed image and changes the output method or outputs the image.

  As described above, once the output image is read by the scanner of the MFP, and the data stored in the storage device is automatically searched / displayed, the convenience of the user is improved during reprinting by simple setting change or correction. To do. Further, by using attribute information, it becomes easy to specify data and the accuracy is improved.

  In the third embodiment, image retrieval and collation are performed by pattern matching between the attribute information that has been retained and the attribute information that is generated from the newly read image. However, since it is necessary to retain raster data, the capacity of the storage device Depends on. Therefore, the attribute information is not held as it is, but a statistic such as an average value, a maximum value, a minimum value, a standard deviation, or a histogram is calculated and the statistic is held. When searching, matching is performed based on the statistics.

  As described above, once the output image is read by the scanner of the MFP, and the data stored in the storage device is automatically searched / displayed, the convenience of the user is improved during reprinting by simple setting change or correction. To do. In addition, since the statistics are calculated and stored from the attribute information generated at the time of printing, the capacity of the storage device is not limited.

In the present embodiment, a method for searching for an image using a specific component of image compression will be described.
FIG. 17 shows a configuration diagram thereof. The compression processing 1707 is preferably compression that decomposes into frequency components, such as JPEG (Joint Photographic Experts Group). In the case of JPEG, encoding is performed with 8 × 8 (= 64 pixels) as one unit. At this time, regarding the frequency component after DCT conversion, attention is paid to the DC component, and only the component is held. By doing so, the amount of data is simply 1/64. A further reduction in the amount of data is expected by compressing the data when it is held.

  In order to generate the compressed DC component described above, as shown in FIG. 17, when outputting the PDL data by the MFP, the raster data 1105 is compressed (1707), and the compressed DC data 1708 is held in the storage device 1110. Keep it.

  The search method has the configuration shown in FIG. The output product 1106 and the MFP are scanned (1801), and the image data is corrected (1802). The image correction 1802 is performed in order to generate a signal equivalent to the original PDL data by correcting skew reading, distortion, etc., or correcting MTF that decreases during printing. A compression process 1803 is performed on the signal for which the image correction 1802 has been completed, and compressed DC data 1804 is generated. When the compressed DC data 1804 is obtained, matching is performed with the compressed DC data 1708 held in the storage device 1110 (1805), and a result 1806 is obtained. If the result 1806 identifies the compressed DC data, the PDL data or raster data related to the compressed DC data is displayed on the UI (1008). The user sees the displayed image and changes the output method or outputs the image.

  As described above, once the output image is read by the scanner of the MFP, and the data stored in the storage device is automatically searched / displayed, the convenience of the user is improved during reprinting by simple setting change or correction. To do. In addition, the use of compressed information reduces the data storage capacity. Further, since the gradation component of the image signal is retained by using the DC component at the time of compression, the accuracy is improved at the time of pattern matching.

  In the fifth embodiment, an image search and collation is performed by pattern matching between the compressed DC data that has been held and the compressed DC data generated from the newly read image. However, since the raster data needs to be held, the storage device Depends on capacity. Therefore, the compressed DC data is not held as it is, but a statistic such as an average value, a maximum value, a minimum value, a standard deviation, or a histogram is calculated and the statistic is held. When searching, matching is performed based on the statistics.

  As described above, once the output image is read by the scanner of the MFP, and the data stored in the storage device is automatically searched / displayed, the convenience of the user is improved during reprinting by simple setting change or correction. To do. Further, since the statistics are calculated and stored from the compressed DC data generated at the time of printing, there is little restriction on the capacity of the storage device.

  A search method using a combination of two or more of the pattern matching by the thumbnail of the first embodiment, the pattern matching by the attribute information of the third embodiment, and the pattern matching by the compressed DC component of the fifth embodiment.

  As described above, by configuring with multiple search methods, once output images are read with the scanner of the MFP, and data stored in the storage device is automatically searched / displayed, making simple setting changes and corrections, etc. Improves user convenience when reprinting with. In particular, since the search is performed by a plurality of methods, the search accuracy is improved.

The block diagram which shows an example of the structure which implements this invention The figure which shows an example of the original image applied to this invention The figure explaining the image area separation processing of this invention The figure explaining the flag data by this invention The figure explaining the layout synthetic output by this invention The block diagram which shows an example of the output image processing structure of this invention The figure which shows an example of the forgery determination process applied to this invention The figure explaining the color conversion process applied to this invention The figure explaining the image area separation processing of this invention A block diagram of a processing configuration according to the first embodiment. Diagram for explaining thumbnail generation according to the first embodiment. The figure explaining the search means concerning Example 1. The figure explaining the matching of the image concerning Example 1. The figure explaining the production | generation of a statistic according to Example 2. The figure explaining the production | generation of attribute information concerning Example 3. The figure explaining the search means concerning Example 3. The figure explaining the production | generation of compression information concerning Example 1. The figure explaining the search means concerning Example 1.

Explanation of symbols

101 Scanner 102 Input Image Processing 1
103 Image area separation processing 104 Input image processing 2
105 Image memory 1
106 Flag memory 1
107 RIP
108 Interpreter 109 Data compression 110 Storage device 111 Auxiliary storage device 112 Data expansion 113 Pixel density conversion 114 Image memory 2
115 Flag memory 2
116 Output Image Processing 117 Printer 118 Communication I / F
119 External communication channel 120 Forgery determination processing

Claims (11)

Data holding means for holding external input data input from the outside;
First feature value generation means for generating a first feature value from the external input data;
Feature quantity holding means for holding the first feature quantity generated by the first feature quantity generation means;
Output means for outputting the external input data held by the data holding means;
An image reading unit that reads an output image output by the output unit,
Second feature quantity generation means for generating a second feature quantity from the image read by the reading means;
Feature quantity matching means for matching the second feature quantity generated by the second feature quantity generation means with the first feature quantity held in the feature quantity holding means;
An image processing apparatus, wherein specific external input data is selected from external input data held in the data holding means in accordance with a result of the feature amount matching means.   The image processing apparatus according to claim 1, wherein the first feature amount and the second feature amount are bitmap data.   The image processing apparatus according to claim 1, wherein the resolution of the first feature amount and the second feature amount is the same as that of the external input data.   The image processing apparatus according to claim 1, wherein a resolution of the first feature quantity and the second feature quantity is smaller than the external input data.   2. The feature quantity matching means for matching the first feature quantity and the second feature quantity, the bitmap data is converted into N-values, and collation / determination is performed at each level. Image processing apparatus.   The image processing apparatus according to claim 1, wherein the first feature amount and the second feature amount are statistical data. Data holding means for holding external input data input from the outside;
Encoding means for encoding when the external input data is held by the data holding means;
First feature quantity generating means for generating a first feature quantity from an element of the code quantity generated by the encoding means;
Feature quantity holding means for holding the first feature quantity generated by the first feature quantity generation means;
Output means for outputting the external input data held by the data holding means;
An image reading unit that reads an output image output by the output unit,
A second feature quantity generating means for encoding the image read by the reading means with the encoding means and generating a second feature quantity from the generated code quantity elements;
Feature quantity matching means for matching the second feature quantity generated by the second feature quantity generation means with the first feature quantity held in the feature quantity holding means;
An image processing apparatus, wherein specific external input data is selected from external input data held in the data holding means in accordance with a result of the feature amount matching means.   The image processing apparatus according to claim 7, wherein the first feature amount and the second feature amount are DC components of the code amount.   The image processing apparatus according to claim 8, wherein the first feature amount and the second feature amount are statistical data. Data holding means for holding external input data input from the outside;
Attribute information generating means for generating attribute information from the external input data;
First feature value generation means for generating a first feature value from the attribute information;
Feature quantity holding means for holding the first feature quantity generated by the first feature quantity generation means;
Output means for outputting the external input data held by the data holding means;
An image reading unit that reads an output image output by the output unit,
Second feature quantity generation means for generating attribute information from the attribute information generation means from the image read by the reading means, and generating a second feature quantity from the generated attribute information;
Feature quantity matching means for matching the second feature quantity generated by the second feature quantity generation means with the first feature quantity held in the feature quantity holding means;
An image processing apparatus, wherein specific external input data is selected from external input data held in the data holding means in accordance with a result of the feature amount matching means.   The image processing apparatus according to claim 10, wherein the first feature amount and the second feature amount are statistical data.