Patent Publication Number: US-8116513-B2

Title: Image processing method, image processing apparatus, document reading apparatus, image forming apparatus, and recording medium

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This Nonprovisional application claims priority under 35 U.S.C. §119(a) on Patent Application No. 2006-253143 and No. 2007-218864 filed in Japan on Sep. 19, 2006 and Aug. 24, 2007 respectively, the entire contents of which are hereby incorporated by reference. 
     BACKGROUND 
     1. Technical Field 
     The present application relates to: an image processing method and an image processing apparatus for performing determination processing whether an obtained document image is similar to a stored image stored; a document reading apparatus and an image forming apparatus employing the image processing apparatus; and a recording medium for storing a computer program for implementing the image processing. 
     2. Description of the Related Art 
     Proposed methods for processing of reading a document with a scanner and then determining whether the read document image is similar to a format stored include: a method in which keywords are extracted from an image read by an OCR and then pattern matching is performed on the basis of the extracted keywords; and a method in which documents of determination target are restricted to formatted documents with ruled lines and pattern matching is performed on the basis of information concerning the ruled lines extracted from the read document. 
     In storing a format to be used in similarity determination, recognition processing such as line segment extraction, character box extraction, character recognition, or frame extraction is performed on an input image inputted for registration. Then, from the recognition result, information (e.g., a feature point) such as the center coordinates of frame data, the center coordinates of a character string frame, and connecting frame information is extracted. After that, a features (e.g., a hash value) are calculated from the extracted information. Then, data (such as a features, a model name, and a parameter used for calculating the features) necessary for table management is generated and stored into a hash table, so that the format is stored. 
     In similarity determination for a document, recognition processing is performed on the inputted document image. Then, from the recognition result, information (e.g., a feature point) such as the center coordinates of frame data, the center coordinates of a character string frame, and connecting frame information is extracted. After that, a features (e.g., a hash value) corresponding to each information is calculated. Then, using the calculated features, an area of the hash table stored is searched, and vote is performed for each stored form name in the searched area. This processing is repeated for each feature point of the inputted document image, so that similarity is calculated by adopting as a recognition result a model which is the largest in a histogram. When the document image is recognized as being similar to a stored format, the document image is saved in a state that an identifier is imparted. Employing such processing, a filing apparatus for images (document images) is proposed that automatically performs matching between a document image and a stored format so as to reduce the user&#39;s work in the processing step (see Japanese Patent Publication No. 3469345). 
     Nevertheless, in the apparatus described in Japanese Patent Publication No. 3469345, stored formats used in similarity determination for a document image are documents in each of which a format (such as frames, ruled lines, and character strings that indicate entry items) is defined, that is, documents in which nothing is entered in the entry fields of each document. Thus, the features (e.g., a hash value) extracted from each stored format does not contain information (e.g., a feature point) concerning the items (e.g., character strings, figures, and marks) to be entered as the entry items. Accordingly, even a document image with omission in which necessary information is not written in the entry fields of the inputted document image can be determined as being similar to a stored format. This has caused a problem that in spite of the omission in the document image, the inputted document image is filed intact. Thus, it has been desired to determine omission in a document image with satisfactory accuracy. 
     SUMMARY 
     The present invention has been devised in view of this situation. An object of the present invention is to provide an image processing method and an image processing apparatus in which a part or a plurality of parts in a stored image are defined in advance, and in which when a document image is determined as being similar to the stored image, it is determined whether omission is present in a part in the document image corresponding to a part defined in the stored image, and then the determination result is outputted, so that in similarity determination for a document image, determination of omission in the document image is achieved with satisfactory accuracy. Also provided are: a document reading apparatus and an image forming apparatus employing the image processing apparatus; and a recording medium for storing a computer program for implementing the image processing. 
     Another object of the present invention is to provide: an image processing method and an image processing apparatus in which a part with omission in a document image determined as having omission is notified so that the part with omission can easily be determined; and a document reading apparatus and an image forming apparatus employing the image processing apparatus. 
     Another object of the present invention is to provide: an image processing apparatus in which presence or absence of omission is determined on the basis of a document image having undergone the page background removing so that omission can be determined with the still more satisfactory accuracy; and a document reading apparatus and an image forming apparatus employing the image processing apparatus. 
     Another object of the present invention is to provide an image processing apparatus in which: a pixel value of each pixel in a first pixel block containing a current pixel in the obtained document image is calculated on the basis of a pixel value of each pixel in a second pixel block containing the individual pixels in the first pixel block; whether the current pixel is an edge pixel is determined on the basis of distribution of the calculated pixel values of the individual pixels in said first pixel block; and whether the obtained document image has omission is determined on the basis of the number of determined edge pixels; so that determination of omission in the document image is achieved with satisfactory accuracy without the necessity of comparison between the pixel values of the document image and the stored image. Also provided are: a document reading apparatus and an image forming apparatus employing the image processing apparatus. 
     Another object of the present invention is to provide: an image processing apparatus in which calculation of the pixel value of each pixel in a first pixel block continuing a current pixel and determination whether the current pixel is an edge pixel are performed separately for each color component, so that determination accuracy in omission is improved; and a document reading apparatus and an image forming apparatus employing the image processing apparatus. 
     Another object of the present invention is to provide a document reading apparatus that has delivery means for delivering in a sorted manner a document with omission when an obtained document image is determined as having omission, and hence can sort out documents with omission from documents without omission. 
     Another object of the present invention is to provide a document reading apparatus having a configuration that delivery means displaces the delivery position for a document with omission, so that documents with omission can easily be sorted out from documents without omission. 
     An image processing method according to the present invention is characterized by an image processing method for determining presence or absence of omission in an obtained document image, comprising the steps of determining whether the obtained document image is similar to a stored image stored; when the document image is determined as being similar to the stored image, determining whether omission is present in a part or parts in the obtained document image corresponding to a part or a plurality of parts defined in said stored image; and outputting a determination result. 
     The image processing method according to the present invention is characterized by an image processing method comprising the step of notifying the part with omission in the document image determined as having omission. 
     An image processing apparatus according to the present invention is characterized by an image processing apparatus for determining presence or absence of omission in an obtained document image, comprising: a similarity determination processing section for determining whether the obtained document image is similar to a stored image stored; an entry item determination processing section that, when the document image is determined as being similar to the stored image, determines whether omission is present in a part or parts in the obtained document image corresponding to a part or a plurality of parts defined in said stored image; and a determination result output section for outputting a determination result. 
     The image processing apparatus according to the present invention is characterized by an image processing apparatus comprising a notification section for notifying the part with omission in a document image determined as having omission. 
     The image processing apparatus according to the present invention is characterized by an image processing apparatus comprising a page background removing section for removing the page background in the obtained document image, wherein said entry item determination processing section determines presence or absence of omission on the basis of the document image in which the page background has been removed by said page background removing section. 
     The image processing apparatus according to the present invention is characterized by an image processing apparatus comprising: a pixel value calculating section for calculating a pixel value of each pixel in a first pixel block containing a current pixel in the obtained document image, on the basis of a pixel value of each pixel in a second pixel block containing the current pixel; and an edge pixel determining section for determining whether said current pixel is an edge pixel on the basis of distribution of the calculated pixel values of the individual pixels in said first pixel block; wherein said entry item determination processing section determines whether the obtained document image has omission, on the basis of the number of current pixels determined as an edge pixel by said edge pixel determining section. 
     The image processing apparatus according to the present invention is characterized by an image processing apparatus wherein when the obtained document image is a color image, each of said pixel value calculating section and said edge pixel determining section performs processing separately for each color component. 
     A document reading apparatus according to the present invention is characterized by a document reading apparatus comprising: a document reading section for reading a plurality of documents; an image processing apparatus described above; and a document delivery section for delivering in a sorted manner a document with omission when the image processing apparatus determines that the document image read by said document reading section has omission. 
     The document reading apparatus according to the present invention is characterized by a document reading apparatus wherein said document delivery section displaces a delivery position for a document with omission relative to a delivery position for a document without omission. 
     An image forming apparatus according to the present invention is characterized by an image forming apparatus comprising: an image processing apparatus described above; and an image forming section for forming an output image on the basis of the image processed by the image processing apparatus. 
     A recording medium according to the present invention is characterized by a recording medium storing thereon a computer program executable to perform the steps of causing a computer to determine whether the obtained document image is similar to a stored image stored; and when the document image is determined as being similar to the stored image, causing a computer to determine whether omission is present in a part or parts in the obtained document image corresponding to a part or a plurality of parts defined in said stored image. 
     In the present invention, it is determined whether an obtained document image is similar to a stored image stored. Then, when the document image is determined as being similar to the stored image, it is determined whether omission is present in a part or parts in the obtained document image corresponding to a part or a plurality of parts defined in advance in the stored image similar to the document image. Then, the determination result (the presence or absence of omission) is outputted. The parts defined in advance are, for example, entry fields in a document (format) in which a format (such as frames, ruled lines, and character strings that indicate entry items) is defined, that is, parts where characters, figures, marks, and the like are to be written as entry items. Since parts where characters and the like are to be written are defined in advance in the stored image, omission can be determined only in the parts where characters and the like are to be written, out of the entirety of the obtained document image. This permits accurate determination whether the document image has omission (erroneous entry omission). Here, in the present invention, the obtained document image indicates: a document image obtained by reading a document image with a scanner; a document image in the form of electronic data generated by writing necessary information into data of a predetermined format with a computer; and electronized data generated by converting data read with a scanner into a predetermined file format such as JPEG. 
     Further, in the present invention, a part with omission in a document image determined as having omission is notified. For example, when the part with omission in the document image is displayed, this permits easy recognition of not only the presence of omission in the document but also the position of the part with omission in the document. In particular, for example, in a case that a large number of entry items are present in a single document sheet, or alternatively in a case that a large number of documents are to be read, omission can easily be recognized so that the user&#39;s convenience is improved. 
     Further, in the present invention, the page background removing is performed on the obtained document image, and then the presence or absence of omission is determined on the basis of the document image in which the page background has been removed. Thus, even in a case that the paper sheet material of the read document is different from that of the stored image like recycled paper and thinly colored paper, the presence or absence of omission can be determined with satisfactory accuracy. 
     Further, in the present invention, the pixel value of each pixel in a first pixel block containing a current pixel in the obtained document image is calculated on the basis of the pixel value of each pixel in a second pixel block containing the individual pixels in the first pixel block. Then, whether the current pixel is an edge pixel is determined on the basis of distribution of the calculated pixel values of the individual pixels in said first pixel block. Further, whether the obtained document image has omission is determined on the basis of the number of determined edge pixels. This permits determination of omission (erroneous entry omission) in the document image with satisfactory accuracy only on the basis of the obtained document image without the necessity of comparison of the pixel values of the document image and the stored image. Here, in the present invention, the obtained document image indicates: a document image obtained by reading a document image with a scanner; a document image in the form of electronic data generated by writing necessary information into data of a predetermined format with a computer; and electronized data generated by converting data read with a scanner into a predetermined file format such as JPEG. 
     Further, in the present invention, when the obtained document image is a color image, calculation of the pixel value of each pixel in a first pixel block continuing a current pixel and determination whether the current pixel is an edge pixel are performed separately for each color component. This suppresses the influence of isolated points in the document image and noise at the time of reading and the influence of dirt in the base sheet of the document or dust adhering to the base sheet. Accordingly, determination accuracy for omission is improved further. 
     Further, in the present invention, when the obtained document image is determined as having omission, delivery means delivers a document with omission in a sorted manner. Thus, for example, when a large number of documents are to be read, documents with omission and documents without omission are delivered in a sorted manner. This allows a user to easily sort out documents with omission from a large number of delivered documents. 
     Further, in the present invention, the delivery means displaces the delivery position for documents with omission. This allows documents with omission to easily be sorted from the delivered documents. 
     In the present invention, a part or a plurality of parts in the stored image is defined in advance. Then, when the document image is determined as being similar to the stored image, it is determined whether omission is present in a part in the document image corresponding to a part defined in the stored image, and then the determination result is outputted. By virtue of this, in similarity determination for the document image, omission in the document image can be determined with satisfactory accuracy. 
     Further, in the present invention, a part with omission in a document image determined as having omission is notified so that the part with omission can easily be determined. 
     Further, in the present invention, in a preceding stage to the determination whether the obtained document image has omission, the page background of the document image is removed. By virtue of this, even in a case that the paper sheet material of the read document is different from that of the stored image like recycled paper and thinly colored paper, the presence or absence of omission can be determined with satisfactory accuracy. 
     Further, in the present invention, the pixel value of each pixel in a first pixel block containing a current pixel in the obtained document image is calculated on the basis of the pixel value of each pixel in a second pixel block containing the individual pixels in the first pixel block. Then, whether the current pixel is an edge pixel is determined on the basis of distribution of the calculated pixel values of the individual pixels in said first pixel block. Further, whether the obtained document image has omission is determined on the basis of the number of determined edge pixels. This permits determination of omission in the document image with satisfactory accuracy only on the basis of the obtained document image without the necessity of comparison of the pixel values of the document image and the stored image. 
     Further, in the present invention, when the obtained document image is a color image, calculation of the pixel value of each pixel in a first pixel block continuing a current pixel and determination whether the current pixel is an edge pixel are performed separately for each color component. This suppresses the influence of isolated points in the document image and noise at the time of reading and the influence of dirt in the base sheet of the document or dust adhering to the base sheet. Accordingly, determination accuracy for omission is improved further. 
     Further, in the present invention, delivery means is provided that delivers in a sorted manner a document with omission when the obtained document image is determined as having omission. This permits sorting into documents with omission and documents without omission. In particular, in a case that a large number of documents are to be read, documents with omission are easily sorted from among a large number of delivered documents. This improves the user&#39;s convenience. 
     Further, in the present invention, the delivery means displaces the delivery position for documents with omission. This allows documents with omission to easily be sorted. 
     The above and further objects and features of the invention will more fully be apparent from the following detailed description with accompanying drawings. 
    
    
     
       BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS 
         FIG. 1  is a block diagram showing a configuration of an image forming apparatus employing an image processing apparatus according to the present invention; 
         FIG. 2  is a block diagram showing a configuration of a document matching process section; 
         FIG. 3  is a block diagram showing a configuration of a feature point calculating section; 
         FIG. 4  is an explanation diagram showing an example of a filter coefficient of a filtering section; 
         FIG. 5  is an explanation diagram showing an example of a feature point of a connected region; 
         FIG. 6  is an explanation diagram showing an example of a result of extraction of a feature point for a character string; 
         FIG. 7  is an explanation diagram showing the current feature point and the surrounding feature point; 
         FIGS. 8A to 8C  are explanation diagrams showing an example of calculation of an invariant with respect to a current feature point; 
         FIGS. 9A to 9C  are explanation diagrams showing an example of calculation of an invariant with respect to a current feature point; 
         FIGS. 10A to 10D  are explanation diagrams showing another example of calculation of an invariant with respect to a current feature point of; 
         FIGS. 11A to 11D  are explanation diagrams showing another example of calculation of an invariant with respect to a current feature point; 
         FIG. 12  is an explanation diagram showing a structure of a feature point coordinate table for a document image; 
         FIGS. 13A and 13B  are explanation diagrams showing a structure of a hash table for a stored format; 
         FIG. 14  is an explanation diagram showing a structure of a feature point coordinate table for a stored format; 
         FIG. 15  is an explanation diagram showing a structure of a feature point vote table; 
         FIG. 16  is an explanation diagram showing an example of similarity determination based on a voting result; 
         FIG. 17  is an explanation diagram showing position alignment between a document image and a stored format; 
         FIG. 18  is an explanation diagram showing an example of a stored format; 
         FIGS. 19A and 19B  are explanation diagrams showing an example of a determination area table indicating entry omission determination regions; 
         FIG. 20  is an explanation diagram showing another example of a stored format; 
         FIG. 21  is an explanation diagram showing another example of a determination area table indicating entry omission determination regions; 
         FIG. 22  is a flow chart showing a procedure of document matching process; 
         FIG. 23  is a flow chart showing a procedure of entry item determination processing; 
         FIG. 24  is a flow chart showing a procedure of entry item determination processing; 
         FIG. 25  is a block diagram showing a configuration of a document reading apparatus according to the present invention; 
         FIG. 26  is a schematic diagram showing a configuration of a document reading apparatus according to the present invention; 
         FIG. 27  is a transverse sectional view showing a configuration of a document shifter mechanism; 
         FIG. 28  is a transverse sectional view showing a configuration of a document shifter mechanism; 
         FIG. 29  is an explanation diagram showing a delivery position for a document; 
         FIGS. 30A to 30D  are explanation diagrams showing examples of screen display that notifies entry omission; 
         FIG. 31  is a flow chart showing a procedure of entry item determination processing according to Embodiment 2; 
         FIG. 32  is a flow chart showing a procedure of entry item determination processing according to Embodiment 2; 
         FIG. 33  is a flow chart showing a procedure of entry item determination processing according to Embodiment 3; 
         FIG. 34  is a flow chart showing a procedure of entry item determination processing according to Embodiment 3; 
         FIG. 35  is a schematic diagram showing a configuration of a document shifter mechanism in a case that a delivery tray is movable; 
         FIG. 36  is a transverse sectional view showing a configuration of a document shifter mechanism; 
         FIG. 37  is a schematic diagram showing a configuration of a document reading apparatus according to Embodiment 5; 
         FIG. 38  is a schematic diagram showing a configuration of a document reading apparatus according to Embodiment 6; 
         FIG. 39  is a block diagram showing a configuration of an entry item determination processing section according to Embodiment 7; and 
         FIG. 40  is a flow chart showing a processing procedure of an entry item determination processing section according to Embodiment 7. 
     
    
    
     DETAILED DESCRIPTION 
     Embodiments are described below in detail with reference to the drawings. 
     Embodiment 1 
     The present invention is described below with reference to the drawings illustrating an embodiment.  FIG. 1  is a block diagram showing the configuration of an image forming apparatus  100  employing an image processing apparatus according to the present invention. The image forming apparatus  100  (e.g., a digital color copying machine or a combined machine provided with a compound function such as a printer function, a filing function, and a facsimile and e-mail distribution function) includes a color image input apparatus  1 , a color image processing apparatus  2  (an image processing apparatus), a color image output apparatus  3  serving as image forming means, and an operation panel  4  for various kinds of operation. 
     Image data of analog signals of RGB (R: red, G: green, B: blue) obtained when the color image input apparatus  1  reads a document is outputted to the color image processing apparatus  2 , then processed by predetermined processing in the color image processing apparatus  2 , and then outputted to the color image output apparatus  3  as digital color signals of CMYK (C: cyan, M: magenta, Y: yellow, K: black). 
     The color image input apparatus  1  is, for example, a scanner provided with a CCD (Charged Coupled Device). The color image input apparatus  1  reads a reflected light image from the document image in the form of analog signals of RGB, and then outputs the read RGB signals to the color image processing apparatus  2 . Further, the color image output apparatus  3  is image forming means employing an electrophotography method or an inkjet method for outputting the image data of the document image onto a record paper sheet. Further, the color image output apparatus  3  may be a display unit such as a display. 
     The color image processing apparatus  2  is constructed from a CPU, an ASIC (Application Specific Integrated Circuit), and the like. 
     An A/D conversion section  20  converts the RGB signals inputted from the color image input apparatus  1  into, for example, 10-bit digital signals, and then outputs the converted RGB signals to a shading correction section  21 . 
     The shading correction section  21  performs correction processing in which various kinds of distortion generated in the illumination system, the image focusing system, and the image sensing system of the color image input apparatus  1  is removed from the inputted RGB signals. Further, the shading correction section  21  performs the processing of adjusting the color balance on the inputted RGB signals (RGB reflectivility signals) and performs the processing of converting the signals into those such as a density signal easily treated by the image processing system adopted in the color image processing apparatus  2 , and then outputs the converted RGB signals (image) to a document matching process section  22 . 
     The document matching process section  22  binarizes the inputted image (image data), then calculates feature points (e.g., the centroid) of a connected region specified on the basis of the binary image, then selects a plurality of feature points from among the calculated feature points, then obtains an invariant on the basis of the selected feature points, and then calculates a features (e.g., a hash value) on the basis of the invariant. Then, on the basis of the calculated features, the document matching process section  22  determines whether the inputted image (document image) is similar to a stored format (stored image) stored preliminary. When it is determined as being similar, the document matching process section  22  determines whether entry omission (erroneous omission) is present in the input image (document image), and then outputs a determination signal (a determination result indicating the presence or absence of entry omission). Further, the document matching process section  22  outputs the inputted RGB signals intact to an input tone correction section  23  of the subsequent stage. 
     The input tone correction section  23  performs image quality adjustment processing such as the page background density removing or contrast, and then outputs the processed RGB signals to a segmentation process section  24 . 
     On the basis of the inputted RGB signals, the segmentation process section  24  separates individual pixels of the inputted image into a character region (text region), a halftone region, and a photograph region. On the basis of the separation result, the segmentation process section  24  outputs a segmentation class signal indicating that each pixel belongs to which region, to a black generation and under color removal section  26 , a spatial filter process section  27  and a tone reproduction process section  29 . Further, the segmentation process section  24  outputs the inputted RGB signals intact to a color correction section  25  of the subsequent stage. 
     The color correction section  25  converts the inputted RGB signals into the color space of CMY, then performs color correction in accordance with the characteristics of the color image output apparatus  3 , and then outputs the corrected CMY signals to the black generation and under color removal section  26 . Specifically, for the purpose of high fidelity in color reproduction, the color correction section  25  performs the processing of removing color inaccuracy on the basis of the spectral characteristics of the CMY color materials containing unnecessary absorption components. 
     On the basis of the CMY signals inputted from the color correction section  25 , the black generation and under color removal section  26  generates a K (black) signal and, at the same time, subtracts the K signal from the inputted CMY signals so as to generate new CMY signals, and then outputs the generated CMYK signals to the spatial filter process section  27 . 
     An example of processing in the black generation and under color removal section  26  is described below. For example, in the case of processing of black generation by using skeleton black, the input-output characteristics of the skeleton curve is expressed by y=f(x), inputted data is denoted by C, M, and Y, outputted data is denoted by C′, M′, Y′, and K′, and the UCR (Under Color Removal) ratio is denoted by α (0&lt;α&lt;1). Then, data outputted in the black generation and the page background removing processing is expressed by K′=f{min(C,M,Y)}, C′=C-αK′, M′=M-αK′, and Y′=Y-αK′. 
     The spatial filter process section  27  performs spatial filtering by means of a digital filter based on the segmentation class signal, onto the CMYK signals inputted from the black generation and under color removal section  26 . By virtue of this, the spatial frequency characteristics of the image data is corrected so that blur occurrence or graininess degradation is avoided in the output image in the color image output apparatus  3 . For example, in order to improve the reproducibility of, especially, black characters or color characters, the spatial filter process section  27  performs edge enhancement processing so as to emphasize high frequency components for the region separated into a character region by the segmentation process section  24 . Further, the spatial filter process section  27  performs low pass filtering for removing the input dotted components, onto the region separated into a dotted region by the segmentation process section  24 . The spatial filter process section  27  outputs the processed CMYK signals to the output tone correction section  28 . 
     The output tone correction section  28  performs output tone correction processing of converting the CMYK signals inputted from the spatial filter process section  27  into a dotted area ratio which is a characteristic value of the color image output apparatus  3 . Then, the output tone correction section  28  outputs the CMYK signals having undergone the output gradation correction processing to the tone reproduction process section  29 . 
     On the basis of the segmentation class signal inputted from the segmentation process section  24 , the tone reproduction process section  29  performs predetermined processing on the CMYK signals inputted from the output tone correction section  28 . For example, in order to improve the reproducibility of, especially, black characters or color characters, the tone reproduction process section  29  performs binarization processing or multi-level-dithering processing on the region separated into a character region, such that the signals should become appropriate for the reproduction of high frequency components in the color image output apparatus  3 . 
     Further, the tone reproduction process section  29  performs gradation reproduction processing (halftone generation) on the region separated into a dotted region by the segmentation process section  24 , such that the image is finally separated into pixels so that each gradation can be reproduced. Further, the tone reproduction process section  29  performs binarization processing or multi-level-dithering processing on the region separated into a photograph region by the segmentation process section  24 , such that the signals should become appropriate for the gradation reproduction in the color image output apparatus  3 . 
     The color image processing apparatus  2  temporarily stores into a storage section (not shown) the image data (CMYK signals) processed by the tone reproduction process section  29 . Then, in a predetermined timing of performing image formation, the color image processing apparatus  2  reads the image data stored in the storage section, and then outputs the read image data to the color image output apparatus  3 . Control for these is performed, for example, by a CPU (not shown). Further, on the basis of the determination signal outputted from the document matching process section  22 , the CPU (not shown) in the color image processing apparatus  2  performs control such that predetermined processing (e.g., notification of entry omission and delivery of a document with omission) is performed on the document image. 
       FIG. 2  is a block diagram showing the configuration of the document matching process section  22 . The document matching process section  22  includes a feature point calculating section  221 , a features calculating section  222 , a vote processing section  223 , a similarity determination processing section  224 , an entry item determination processing section  225 , a memory  226 , and a control section  227  for controlling these sections. 
     The feature point calculating section  221  performs later-described predetermined processing on the inputted image data (document image) and, at the same time, extracts a connected region of character strings or ruled lines in the inputted image so as to calculate a feature point (e.g., the centroid) of the connected region. More specifically, the feature point calculating section  221  binarizes the inputted image extracts (calculates) a feature point (e.g., a value obtained by accumulating the coordinate values of the individual pixels constituting a connected region in the binary image and by dividing the accumulated coordinate values with the number of pixels contained in the connected region) of the connected region specified on the basis of the binary image, and then outputs the extracted feature point to the features calculating section  222 . 
       FIG. 3  is a block diagram showing the configuration of the feature point calculating section  221 . The feature point calculating section  221  includes a signal conversion section  2210 , a resolution converting section  2211 , a filtering section  2212 , a binarizing section  2213 , and a centroid calculating section  2214 . 
     When the inputted image (image data) is a color image, the signal conversion processing section  2210  achromatizes and converts the color image into a luminance signal or a lightness signal, and then outputs the converted image to the resolution converting section  2211 . For example, when the color components RGB of each pixel is denoted respectively by Rj, Gj, and Bj, the luminance signal Yj is expressed by Yj=0.30×Rj+0.59×Gj+0.11×Bj. Here, the present invention is not limited to this formula. That is, the RGB signals may be converted into CIE1976 L*a*b* signals. 
     Even when the inputted image is one having undergone optical magnification change in the color image input apparatus  1 , the resolution converting section  2211  performs magnification change on the inputted image again such as to realize a predetermined resolution, and then outputs to the filtering section  2212  the image having undergone the magnification change. By virtue of this, even when magnification change processing has been performed by the color image input apparatus  1  so that the resolution has varied, extraction of a feature point is achieved free from its influence. This permits accurate classification of the document. In particular, in the case of size-reduced characters, a possibility is avoided that when a connected region is to be specified by binarization processing, blotted characters cause intrinsically separated regions to be specified as if they are connected to each other so that the calculated centroid may deviate. Further, the resolution converting section  2211  converts the image into that of a resolution smaller than the resolution obtained when the image is read by the color image input apparatus  1  with unity magnification. For example, an image read at 600 dpi (dot per inch) by the color image input apparatus  1  is converted into that of 300 dpi. This reduces the amount of processing in the subsequent stage. 
     The filtering section  2212  corrects the spatial frequency characteristics of the inputted image (e.g., enhancement processing and smoothing of the image), and then outputs the corrected image to the binarizing section  2213 . Since the spatial frequency characteristics of the color image input apparatus  1  is different depending on each model, the filtering section  2212  corrects the different spatial frequency characteristics into required characteristics. In the image (e.g., image signal) outputted from the color image input apparatus  1 , degradation such as blurring in the image is caused by, for example: optical system components such as lenses and mirrors; the aperture ratio, the transfer efficiency, and the after-image of the light acceptance surface of CCD; and the storage effect and the scanning unevenness caused by the physical scan. The filtering section  2212  performs enhancement processing on the boundary or the edges so as to restores degradation such as blurring generated in the image. Further, the filtering section  2212  performs smoothing for suppressing high frequency components which are unnecessary in the feature point extracting processing performed in the subsequent stage. This permits accurate extraction of a feature point, and hence achieves accurate determination of the similarity of the image. Here, the filter coefficient used in the filtering section  2212  may be set up appropriately in accordance with the model, the characteristics, or the like of the employed color image input apparatus  1 . 
       FIG. 4  is an explanation diagram showing an example of the filter coefficient of the filtering section  2212 . As shown in the figure, the spatial filter is, for example, a mixing filter that has a size of 7×7 (seven rows by seven columns) and that performs enhancement processing and smoothing processing. The pixels of the inputted image are scanned so that arithmetic processing by the spatial filter is performed on all the pixels. Here, the size of the spatial filter is not limited to the size of 7×7. That is, the size may be 3×3, 5×5, or the like. Further, the numerical value of the filter coefficient is an example. That is, the actual value is not limited to this example, and may be set up appropriately in accordance with the model, the characteristics, or the like of the employed color image input apparatus  1 . 
     The binarizing section  2213  compares with a threshold value the luminance value (the luminance signal) or the lightness value (the lightness signal) of the inputted image so as to binarize the image, and then outputs to the centroid calculating section  2214  the binary image having undergone the binarization. 
     On the basis of the binarization information (e.g., expressed by “1” and “0”) of each pixel of the binary image inputted from the binarizing section  2213 , the centroid calculating section  2214  performs labeling (label attaching processing) on each pixel. Then, the centroid calculating section  2214  specifies a connected region where pixels having the same label are in succession, then extracts as a feature point the centroid of the specified connected region, and then outputs the extracted feature point to the features calculating section  222 . Here, the feature point is expressed by the coordinates (x′,y′) in the binary image (document image). 
       FIG. 5  is an explanation diagram showing an example of a feature point of a connected region. In the figure, the specified connected region is a character “A”, and is specified as a set of pixels to which the same label is imparted. A feature point (centroid) of this character “A” is located at a position (x′-coordinate,y′-coordinate) indicated by a black dot in the figure. 
       FIG. 6  is an explanation diagram showing an example of a result of extraction of a feature point for a character string. In the case of a character string composed of a plurality of characters, a plurality of feature points are extracted that have different coordinates depending on the kinds of characters. 
     Using the feature point inputted from the feature point calculating section  221 , the features calculating section  222  calculates an invariant with respect to the processing of rotation, expansion, size-reduction, or the like, and then calculates features (feature vector) on the basis of this invariant. More specifically, the features calculating section  222  adopts, as a current feature point, each feature point (that is, coordinate values of the centroid of the connected region) inputted from the feature point calculating section  221 , and then extracts, for example, surrounding four feature points having smaller distances from the current feature point. 
       FIG. 7  is an explanation diagram showing current feature points and surrounding feature points. As shown in the figure, as for a current feature point P 1 , for example, in ascending order of distance from the current feature point P 1 , four feature points surrounded by a closed curve S 1  are extracted (for the current feature point P 1 , a current feature point P 2  also is extracted as one feature point). Further, as for the current feature point P 2 , for example, similarly to the above-mentioned case, in ascending order of distance from the current feature point P 2 , four feature points surrounded by a closed curve S 2  are extracted (for the current feature point P 2 , the current feature point P 1  also is extracted as one feature point). 
     The features calculating section  222  selects three feature points from the four extracted feature points so as to calculate an invariant. Here, the number of selected feature points is not limited to three. That is, four, five, or the like feature points may be selected. The number of feature points to be selected differs according to the kind of desired invariant. For example, an invariant calculated from three points is a similarity invariant. 
       FIGS. 8A to 8C  are explanation diagrams showing examples of calculation of an invariant with respect to a current feature point P 1 .  FIGS. 9A to 9C  are explanation diagrams showing examples of calculation of an invariant with respect to a current feature point P 2 . As shown in  FIGS. 8A to 8C , three feature points are selected from the four feature points surrounding the current feature point P 1 . Then, three kinds of invariants are denoted respectively by H 1   j  (j=1, 2, 3). Each invariant H 1   j  is calculated by a formula expressed by H 1   j =A 1   j /B 1   j . Here, each of A 1   j  and B 1   j  indicates the distance between the feature points. The distance between feature points is calculated on the basis of the coordinate values of the individual surrounding feature points. Thus, for example, even when the document is rotated, moved, or inclined, the invariant H 1   j  does not vary. Accordingly, determination of the similarity of the image is achieved with satisfactory accuracy, and hence a similar document can be determined with satisfactory accuracy. 
     Similarly, as shown in  FIGS. 9A to 9C , three feature points are selected from the four feature points surrounding the current feature point P 2 . Then, three kinds of invariants are denoted respectively by H 2   j  (j=1, 2, 3). Each invariant H 2   j  is calculated by a formula expressed by H 2   j =A 2   j /B 2   j . Here, each of A 2   j  and B 2   j  indicates the distance between the feature points. Similarly to the above-mentioned case, the distance between feature points is calculated on the basis of the coordinate values of the individual surrounding feature points. In accordance with a similar procedure, invariants can be calculated for the other feature points. 
     On the basis of the invariants calculated for each current feature point, the features calculating section  222  calculates a hash value (a features) Hi. The hash value of a current feature point Pi is expressed by Hi=(Hi 1 ×10 2 +Hi 2 ×10 1 +Hi 3 ×10 0 )/E. Here, i is a natural number and denotes the identification number of a feature point. Further, E is a constant determined by how large remainder is expected. For example, when the value is set to be “10”, the remainder falls between “0” and “9”. This gives the range that can be taken by the calculated hash value. Further, i is a natural number and denotes the identification number of a feature point. 
       FIGS. 10A to 10D  are explanation diagrams showing other examples of calculation of an invariant with respect to a current feature point P 3 .  FIGS. 11A to 11D  are explanation diagrams showing other examples of calculation of an invariant with respect to a current feature point P 4 . As shown in  FIGS. 10A to 10D , four kinds of combinations may be selected from the four points consisting of the surrounding feature points P 1 , P 2 , P 4 , and P 5  of the current feature point P 3 . Then, similarly to the above-mentioned case, invariants H 3   j  (j=1, 2, 3, 4) may be calculated by H 3   j =A 3   j /B 3   j.    
     Further, as shown in  FIGS. 11A to 11D , four kinds of combinations may be selected from the four points consisting of the surrounding feature points P 2 , P 3 , P 5 , and P 6  of the current feature point P 4 . Then, similarly to the above-mentioned case, invariants H 4   j  (j=1, 2, 3, 4) may be calculated by H 4   j =A 4   j /B 4   j . In the examples of  FIGS. 10A to 10D  and  FIGS. 11A to 11D , the hash value Hi of a current feature point Pi is calculated by
 
 Hi =( Hi 1×10 3   +Hi 2×10 2   +Hi 3×10 1   +Hi 4×10 0 )/ E.  
 
     Here, the above-mentioned hash value serving as features is an example, and is not limited to this. Another hash function may be employed. The above-mentioned example has been described for the case that four points are extracted as other surrounding feature points. However, the number of points is not limited to four. For example, six points may be extracted. In this case, five points may be extracted from the six feature points. Then, for each of the six kinds of methods of extracting five points, invariants may be calculated by extracting three points from the five points, so that a hash value may be calculated. This permits that one hash value is calculated from one feature point, and also that a plurality of hash values are calculated from one feature point. 
     The features calculating section  222  stores: an index indicating a feature point of the document image; a hash value calculated with respect to the feature point; and the coordinates of the feature point on the document image; as a feature point coordinate table for the document image into the memory  226 . 
     When the document image is to be stored, for example, a document registration mode is selected in the operation panel  4  of the image forming apparatus  100 , so that registration is performed. Whether the document registration mode is selected is determined by the control section  227 . When the document registration mode is not selected, ordinary operation of copying, filing, e-mail transmission, or the like is performed. Here, in addition to being performed by a dedicated hardware circuit such as the document matching process section  22 , the document registration processing may be performed by a method in which a computer program that defines the procedure of document registration processing is loaded onto a personal computer having a CPU, a RAM, a ROM, and the like and then the computer program is executed by the CPU. 
       FIG. 12  is an explanation diagram showing the structure of a feature point coordinate table  2261  for a document image. The feature point coordinate table  2261  for a document image is composed of individual fields for: an index indicating a feature point of the document image; a hash value calculated with respect to the feature point; and the coordinates (x′-coordinate, y′-coordinate) of a feature point on the document image. 
     As shown in  FIG. 12 , for example, the hash value calculated with respect to the feature point in which the index indicating a feature point of the document image is p 1  is H 1 . The coordinates of the feature point are (x 11 ′,y 11 ′). Further, similarly, the hash value calculated with respect to the feature point in which the index indicating a feature point of the document image is p 2  is H 8 . The coordinates of the feature point are (x 32 ′,y 32 ′). 
       FIGS. 13A and 13B  are explanation diagrams showing the structure of a hash table  2262  for stored formats. As shown in  FIG. 13A , The structure of the hash table  2262  includes individual fields of a hash value and an index that indicates a document (a stored format). More specifically, in correspondence to an index that indicates a document, a point index that indicates a position in the document and an invariant (both are not shown) are stored. The hash table  2262  is stored in the memory  226 . Further, for the purpose of determination of the similarity of an image, stored formats (images to be collated and document images) are stored in the memory  226 . Here, as shown in  FIG. 13B , when hash values are equal to each other (H 1 =H 5 ), the two entries in the hash table  2262  may be unified. 
       FIG. 14  is an explanation diagram showing the structure of a feature point coordinate table  2263  for stored formats. The feature point coordinate table  2263  for stored formats is stored in the memory  226 , and composed of individual fields of: an index indicating a document for specifying each stored format; an index indicating a feature point for specifying the feature point calculated in each stored format; and the coordinates (x-coordinate, y-coordinate) of each feature point on the stored format. 
     As shown in  FIG. 14 , for example, the stored format having the index ID 1  indicating the document has feature points f 11 , f 12 , f 13 , f 14 , . . . . The coordinates of the individual feature points on the stored format are (x 11 ,y 11 ), (x 12 ,y 12 ), (x 13 ,y 13 ), (x 14 ,y 14 ) . . . . The situation is similar to the other stored formats ID 2 , . . . . 
     On the basis of the hash value (features) calculated by the features calculating section  222 , the vote processing section  223  searches the hash table  2262  for stored formats stored in the memory  226 . When the hash value agrees, the vote processing section  223  votes for the index indicating the document stored at the hash value (that is, the image in which the same hash value has been calculated). The result obtained by accumulating the votes is outputted as the number of obtained votes to the similarity determination processing section  224 . 
     Further, when the hash value of the document image and the hash value of the stored format agree with each other, the vote processing section  223  determines which feature point in which stored format has been voted by the feature point of the document image, and then stores the determination result as a feature point vote table  2264  in the memory  226 . 
       FIG. 15  is an explanation diagram showing the structure of the feature point vote table  2264 . In the feature point vote table  2264 , indices p 1 , p 2 , . . . each indicating a feature point of a document image are recorded in each element of a matrix composed of: indices f 11 , f 21 , . . . , fn 1  (denoted by “fn 1 ”, hereinafter) each indicating a feature point of a stored format corresponding to indices ID 1 , ID 2 , ID 3 , ID 4 , . . . , IDn each indicating the document of a stored format; f 12 , f 22 , . . . , fn 2  (denoted by “fn 2 ”, hereinafter); and similarly, fn 3 , fn 4 , fn 5 , fn 6 , fn 7 , . . . . 
     As shown in  FIG. 15 , for example, it is determined that the hash value calculated for the feature point of the document image expressed by the index p 1  agrees with the hash value of the feature point f 11  having the index ID 1  indicating the document of the stored format. Further, for example, it is determined that the hash value calculated for the feature point of the document image expressed by the index p 2  agrees with the hash value of the feature point f 32  having the index ID 3  indicating the document of the stored format. Furthermore, for example, it is determined that the hash value calculated for the feature point of the document image expressed by the index p 3  agrees with the hash value of the feature point f 13  having the index ID 1  indicating the document of the stored format. The situation is similar to the subsequent indices p 4 , p 5 , p 6 , p 7  . . . . 
     On the basis of the voting result inputted from the vote processing section  223 , the similarity determination processing section  224  determines whether the read document image is similar to any stored format, and then outputs the determination result to the entry item determination processing section  225 . More specifically, the similarity determination processing section  224  divides the number of obtained votes inputted from the vote processing section  223  by the greatest number of obtained votes of the document image (expressed by the number of feature points×the number of hash values calculated from one feature point), so as to calculates a normalized similarity. Then, the similarity determination processing section  224  compares the calculated similarity with a threshold value Th (e.g., 0.8) determined in advance. When the similarity is greater than or equal to the threshold value Th, the similarity determination processing section  224  determines that the document image is similar to the stored format in which the similarity has been calculated. When the similarity is smaller than the threshold value Th, the similarity determination processing section  224  concludes the absence of a stored format similar to the document image, and then outputs the determination result to the entry item determination processing section  225 . Here, the number of obtained votes inputted from the vote processing section  223  may be compared with a threshold value defined in advance. Then, when the number of obtained votes is greater than or equal to the threshold value, it may be determined that the document image is similar to a stored format stored in advance, and further it may be determined that a stored format having the greatest number of obtained votes among the stored formats determined as being similar is identical to the document image. 
       FIG. 16  is an explanation diagram showing an example of similarity determination based on a voting result. As shown in  FIG. 16 , the hash table  2262  is searched and vote is performed for each hash value calculated from the read document image. Then, it is assumed that as a result, vote has been performed for the stored formats in which the indices indicating the documents are ID 1 , ID 2 , and ID 3 . Then, each number of obtained votes obtained as a result of the voting is divided by the greatest number of obtained votes of the document image, so that normalized similarities N 1 , N 2 , and N 3  are calculated. The stored format having a calculated similarity greater than or equal to the threshold value Th is that has the index ID 1  indicating the document. Thus, the document image is determined as being similar to the stored format having the index ID 1  indicating the document. 
     When the determination result that the document image is similar to the stored format is outputted from the similarity determination processing section  224 , the entry item determination processing section  225  determines whether the document image has entry omission, and then outputs a determination signal that indicates the presence or absence of entry omission. More specifically, the entry item determination processing section  225  performs: position alignment processing for aligning the positions of the document image and the stored format; processing for specifying an entry omission determination region; difference processing for calculating the difference of the pixel values (e.g., luminance values) of each pixel between the document image and each stored format; determination processing for determining whether the document image has entry omission, on the basis of the calculated difference; and the like. 
     Next, the position alignment processing for transforming the coordinate system of the stored format into the coordinate system of the document image so as to align the positions between the images is described below. Here, in the following description, it is assumed that the document image has been determined as being similar to the stored format having the index ID 1  indicating the document. 
     The entry item determination processing section  225  accesses the memory  226  and extracts from the feature point vote table  2264  a feature point of the document image having voted for the index ID 1  indicating the document. In the example of  FIG. 15 , the indices indicating feature points of the document image are p 1 , p 3 , p 4 , and p 7 . 
     The entry item determination processing section  225  specifies indices f 11 , f 13 , f 14 , and f 17  indicating the feature points of the stored format corresponding to the indices p 1 , p 3 , p 4 , and p 7  indicating the feature points of the extracted document image (the hash values agree with each other). With reference to the feature point coordinate table  2263  for stored formats and the feature point coordinate table  2261  for the document image, the entry item determination processing section  225  calculates a matrix Jin concerning the coordinates of the feature points of the stored format expressed by Formula (1) and a matrix Jout concerning the coordinates of the feature points of the document image expressed by Formula (2). The transformation coefficients in a transformation matrix W are assumed to be Formula (3). 
     
       
         
           
             
               
                 
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     The entry item determination processing section  225  calculates the transformation matrix W in accordance with Formula (4). In this case, the transposed matrix Jin T  of Jin is multiplied to both sides of Formula (4), so that Formula (5) is obtained. Further, the inverse matrix of Jin T  Jin is multiplied to both sides of Formula (5), so that Formula (6) is obtained. As a result, the transformation coefficients are calculated. Using the transformation matrix W expressed by the calculated transformation coefficients, the entry item determination processing section  225  transforms arbitrary coordinates (x,y) on the stored format into coordinates (x′,y′) on the document image as shown by Formula (7).
 
 J out= J in× W   (4)
 
 J in T   J out= J in T   J in× W   (5)
 
( J in T   J in) −1   J in T   J out= W   (6)
 
( x′,y′, 1)=( x,y, 1)× A   (7)
 
       FIG. 17  is an explanation diagram showing position alignment between the document image and the stored format. As shown in  FIG. 17 , when correspondence is established respectively between the feature points f 11 , f 13 , f 14 , and f 17  of the stored format and the feature points p 1 , p 3 , p 4 , and p 7  of the document image, even in a case that the positions of the origin (the pixel at the upper left of the image) of the stored format and the pixel at the upper left of the document image deviate from each other, the origins of the two images can be made to agree with each other, so that position alignment is achieved between the stored format and the document image. Here, the number of feature points of each image is not limited to four. Further, depending on the format of a stored format, in a case that a large number of feature points are present, several feature points may be selected from among them. 
     Next, the specification of a determination region (a determination part) where the presence or absence of entry omission is to be determined.  FIG. 18  is an explanation diagram showing an example of a stored format. As shown in  FIG. 18 , in the stored format (that is, a document having a predetermined format) serving as an example, entry fields are provided that correspond to individual item names consisting of date, name, address, telephone number, and contents. Further, as for parts where entry omission is to be determined among the entry fields, entry fields (regions with marking in the figure) are defined in advance in correspondence to the individual item names consisting of date, name, address, and telephone number. 
       FIGS. 19A and 19B  are explanation diagrams showing an example of the determination area table  2265  indicating the entry omission determination regions. As shown in  FIG. 19A , the determination area table  2265  is composed of the index indicating the document of a stored format; the item name of a stored format; and the diagonal coordinates of the entry field corresponding to the item name. Further, as shown in  FIG. 19B , the position of the entry field corresponding to each item name on the stored format is specified by the coordinates of the four corners of the entry field. In  FIG. 19B , the coordinates (x 1 ,y 1 ), (x 2 ,y 1 ), (x 1 ,y 2 ), and (x 2 ,y 2 ) of the date field are shown as an example among the entry fields of the stored format having the index ID 1  indicating the document. 
     As shown in  FIG. 19A , for example, in the stored format having the index ID 1  indicating the document, the entry field of date is specified by the coordinates (x 1 ,y 1 ) and (x 2 ,y 2 ) which are the diagonal coordinates of the entry field. Similarly, the entry field of name is specified by the coordinates (x 3 ,y 3 ) and (x 4 ,y 4 ), while the entry field of address is specified by the coordinates (x 5 ,y 5 ) and (x 6 ,y 6 ). Further, the entry field of telephone number is specified by the coordinates (x 7 ,y 7 ) and (x 8 ,y 8 ). The situation is similar to the other stored formats (having the indices ID 2 , ID 3 , . . . indicating the documents). 
       FIG. 20  is an explanation diagram showing another example of a stored format.  FIG. 21  is an explanation diagram showing another example of the determination area table  2265  indicating the entry omission determination regions. As shown in  FIG. 20 , in the stored format, in addition to the item names of date, name, address, telephone number, and contents, an entry field corresponding to the item name of stamping is provided. Further, as for parts where entry omission is to be determined among the entry fields, entry fields (regions with marking in the figure) are defined in advance in correspondence to the individual item names consisting of date, name, address, telephone number, and stamping. 
     As shown in  FIG. 21 , for example, in the stored format having the index ID 1  indicating the document, the entry field of date is specified by the coordinates (x 1 ,y 1 ) and (x 2 ,y 2 ) which are the diagonal coordinates of the entry field. Similarly, the entry field of name is specified by the coordinates (x 3 ,y 3 ) and (x 4 ,y 4 ), while the entry field of stamping is specified by the coordinates (x 0 ,y 0 ) and (x 9 ,y 9 ). Further, the entry field of address is specified by the coordinates (x 5 ,y 5 ) and (x 6 ,y 6 ), while the entry field of telephone number is specified by the coordinates (x 7 ,y 7 ) and (x 8 ,y 8 ). 
     When the document image is determined as being similar to a stored format, on the basis of the index indicating the document of the stored format determined as being similar, the entry item determination processing section  225  searches the determination area table  2265 , and obtains the item names and the coordinate values of the stored format being similar. Then, on the basis of the obtained coordinate values, the entry item determination processing section  225  specifies an entry omission determination region for each item name, and then determines entry omission in the regions of the document image corresponding to the specified determination regions. 
     Next, the difference processing for calculating the difference of the pixel values of each pixel between the document image and the stored format is described below. The entry item determination processing section  225  scans the pixels in each determination region between the document image and the stored format having undergone position alignment, sequentially, for example, from the upper left to the lower right of the two images, and thereby calculates the difference of the luminance values of corresponding current pixels in the two images. In this case, with taking into consideration the reproducibility or the like of the pixel value at the time of reading the document, in a case that the image is expressed in 256 gradation levels, when the difference of the luminance values of corresponding pixels in the two images falls within a range of 5 to 10 (a difference threshold value Tg), the current pixels is determined as being the same. For example, when the luminance value of a particular current pixel in the document image is 210 while the luminance value of the corresponding current pixel in the stored format is 215, it is determined that the two current pixels are the same. Further, for example, when the luminance value of a particular current pixel in the document image is 210 while the luminance value of the corresponding current pixel in the stored format is 235, it is determined that the two current pixels are not the same. 
     The entry item determination processing section  225  determines whether the ratio obtained when the number of pixels (the number M of determined pixels) in which the pixel values (e.g., luminance values) have been determined as being approximately the same is divided by the number of pixels owned by the determination region in the stored format is greater than a ratio threshold value Ts (e.g., 0.99). When the calculated ratio is greater than the ratio threshold value Ts, the entry item determination processing section  225  determines that the document image has entry omission, and then outputs a determination signal. Further, when the calculated ratio is smaller than or equal to the ratio threshold value Ts, the entry item determination processing section  225  determines that entry omission is absent in the document image, and then outputs a determination signal. Here, it may be determined whether the ratio obtained when the number of pixels in which the pixel values have been determined as not being approximately the same is divided by the number of pixels owned by the stored format is smaller than a ratio threshold value Td (e.g., 0.01). Then, when the calculated ratio is smaller than the ratio threshold value Td, the document image may be determined as having entry omission. In contrast, when the calculated ratio is greater than or equal to the ratio threshold value Td, the document image may be determined as having no entry omission. 
     That is, in the entry item determination processing, in the determination regions (determination parts), the differences of the pixel values owned by the obtained document image and the stored format (stored image) are calculated. Then, the calculated difference values are compared with a predetermined threshold value (difference threshold value), so that the number of pixels (the number of determined pixels) having approximately the same pixel value is calculated. Then, a ratio is calculated that is obtained when the calculated number of determined pixels is divided by the total number of pixels owned by the determination region in the stored format. Then, the calculated ratio is compared with a predetermined threshold value (ratio threshold value) (larger or smaller comparison). Then, the presence or absence of entry omission is determined in accordance with the comparison result. 
     In the processing that the coordinate system of the stored format is transformed into the coordinate system of the document image so that position alignment is performed between the images, the entire stored format may be transformed as described above. Alternatively, a part where coordinate transformation is to be performed may be defined in advance for each entry field of the stored format. Then, coordinate transformation may be performed only on the part having been defined so. In this case, the part where coordinate transformation is to be performed may be set identical to the determination region where entry omission is to be determined. This allows the entry omission determination processing to be performed in a state that coordinate transformation has been performed only on the part where the presence or absence of entry omission is to be determined. Accordingly, in comparison with the case that the entire image is processed, processing work effort is reduced, and hence the entry item determination processing is performed at a high speed. 
     Next, the operation of the image forming apparatus  100  is described below.  FIG. 22  is a flow chart showing the procedure of document matching process. Here, in place of implementation by a dedicated hardware circuit, the document matching process may be performed by loading a computer program that defines the procedure of document matching process onto a personal computer provided with a CPU, a RAM, a ROM, and the like and then causing the CPU to execute the computer program. Further, in addition to the document matching process, the computer program may includes the control processing for controlling: notification of the determination result in accordance with a result determined in the document matching process; delivery of a document; and the like. 
     The control section  227  determines the presence or absence of operation from a user (document reading operation) (S 11 ). In the case of absence of operation (NO at S 11 ), the processing of step S 11  is continued, and hence operation from a user is awaited. In the case of presence of operation from a user (YES at S 11 ), the control section  227  obtains a document image obtained by document read in the color image input apparatus  1  (S 12 ). 
     The control section  227  calculates a feature point on the basis of the obtained document image (S 13 ), and then calculates a hash value (features) on the basis of the calculated feature point (S 14 ). The control section  227  searches the hash table  2262  for stored formats on the basis of the calculated hash value (features), and then votes for an index indicating a document in which the hash values agree with each other (S 15 ). In this case, the control section  227  determines which feature point in which stored format has been voted by the feature point of the document image, and then stores the determination result. 
     the control section  227  divides the number of obtained votes by the greatest number of obtained votes of the document image so as to calculate the similarity (S 16 ), and then determines whether the calculated similarity is greater than the threshold value Th (S 17 ). When the similarity is greater than the threshold value Th (YES at S 17 ), the control section  227  performs processing entry item determination (S 18 ). Here, details of the entry item determination processing are described later. The control section  227  outputs the determination result obtained in the entry item determination processing (S 19 ). Here, the CPU (not shown) in the color image processing apparatus  2  performs predetermined control processing described later in accordance with the determination result. 
     The control section  227  determines whether all the document images have been obtained (S 20 ). When not all the document images have been obtained (NO at S 20 ), the control section  227  continues the processing at and after step S 12 . On the other hand, when the similarity is not greater than the threshold value Th (NO at S 17 ), the control section  227  continues the processing at and after step S 20 . When all the document images have been obtained (YES at S 20 ), the control section  227  terminates the processing. 
       FIGS. 23 and 24  are flow charts showing a procedure of entry item determination processing. The control section  227  transforms the coordinate system (coordinate values) of a stored format determined as being similar to the document image into the coordinate system (coordinate values) of the document image (S 101 ). In this case, coordinate transformation may be performed on the entire stored format. Alternatively, coordinate transformation may be performed only on entry fields determined in advance in the stored format. 
     The control section  227  searches the determination area table  2265  and thereby obtains the item names and the coordinate values of the individual item names of the stored format determined as being similar to the document image (S 102 ). Then, on the basis of the obtained coordinate values, the control section  227  specifies, on the document image and the stored format, entry item determination regions where entry omission is to be specified (S 103 ). 
     The control section  227  sets into “0” the number M of determined pixels that indicates the number of pixels having the same pixel value (e.g., luminance value) among individual pixels between the document image and the stored format (S 104 ), and then scans the current pixels in the document image and the stored format in the entry item determination regions, so as to calculate the difference of the pixel values for each current pixel (S 105 ). 
     The control section  227  determines whether the calculated difference is smaller than the difference threshold value Tg (S 106 ). When the difference is smaller than the difference threshold value Tg (YES at S 106 ), the control section  227  adds “1” to the number M of determined pixels (S 107 ). The control section  227  determines whether the processing has been completed for all the pixels of the entry item determination regions in the document image and the stored format (S 108 ). When processing for all the pixels is not yet completed (NO at S 108 ), the control section  227  continues the processing at and after step S 105 . 
     When the difference is not smaller than the difference threshold value Tg (NO at S 106 ), the control section  227  continues the processing at and after step S 108 . When the processing has been completed for all the pixels (YES at S 108 ), the control section  227  determines whether the ratio expressed by (the number M of determined pixels/the number of pixels in the stored format) is greater than the ratio threshold value Ts (S 109 ). 
     When the ratio is greater than the ratio threshold value Ts (YES at S 109 ), the control section  227  concludes the presence of entry omission (S 110 ), then records item names of entry omission (S 111 ), and then determines whether processing for all the determination regions has been completed (S 112 ). On the other hand, when the ratio is not greater than the ratio threshold value Ts (NO at S 109 ), the control section  227  concludes the absence of entry omission (S 113 ), and then continues the processing at and after step S 112 . 
     When determining that processing for all the determination regions is not yet completed (NO at S 112 ), the control section  227  continues the processing at and after step S 104 . When determining that the processing has been completed for all the determination regions (YES at S 112 ), the control section  227  terminates the processing. 
     As described above, in the entry item determination processing, determination is performed on the basis of the ratio obtained when the number of pixels having the same pixel value between the document image and the stored format is divided by the number of pixels in the stored format. This provides an advantage that even when noise causes pixels in the document image to have pixel values different from their intrinsic pixel values, influence of the noise is reduced when divided by the number of pixels in the stored format. 
     In accordance with the determination result of entry item determination processing, in the case of presence of entry omission, the CPU (not shown) of the color image processing apparatus  2  displays on the operation panel  4  a message notifying the presence of entry omission and the item name under the entry omission among the item names of the document. Alternatively, such information may be displayed on a display or the like of a personal computer connected to the image forming apparatus  100 . Further, in a case that a plurality of document sheets are read successively, when any of the read documents has entry omission, a message indicating the page number of the document sheet having the entry omission may be displayed. 
     Further, when entry omission has been found, processing such as copying, filing, e-mail transmission, and facsimile transmission are not performed. Further, in a case that the document is composed of a plurality of sheets, in the processing of filing, e-mail distribution, and facsimile transmission, when any one of the document sheets has entry omission, such processing may be not performed. 
       FIG. 25  is a block diagram showing the configuration of a document reading apparatus  500  according to the present invention. As shown in the figure, the document reading apparatus  500  includes a color image input apparatus  1 , an A/D conversion section  20 , a shading correction section  21 , a document matching process section  22 , and a document shifter mechanism  50 . The color image input apparatus  1 , the A/D conversion section  20 , the shading correction section  21 , and the document matching process section  22  are similar to those of the above-mentioned image forming apparatus  100 , and hence description is omitted. 
     The document shifter mechanism  50  obtains the determination signal outputted from the document matching process section  22 , and in accordance with the obtained determination signal, delivers documents with entry omission and documents without entry omission in a sorted manner. Details are described later. 
       FIG. 26  is a schematic diagram showing the configuration of the document reading apparatus  500  according to the present invention. The document reading apparatus  500  includes: a document conveying section constructed in an upper housing  510 ; and a scanner section constructed in a lower housing  560 . 
     The upper housing  510  includes: a pickup roller  512  for conveying a document one by one placed on a document tray  511 ; conveyance rollers  513   a  and  513   b  for conveying the document for the purpose of reading of an image in the document; a document shifter mechanism  50  for shifting the delivery position for a document in the conveyance direction (delivery direction) of the document on the basis of the determination signal inputted from the document matching process section  22  at the time of document delivery; and a document delivery sensor  567  for detecting the document under delivery. Here, the document shifter mechanism  50  is constructed to be separable into two parts of upper and lower. 
     The lower housing  560  includes: scanning units  562  and  563  for performing reciprocation in parallel to the lower surface of a placement base  561 ; an image formation lens  564 ; a CCD line sensor  565  which is a photoelectric converter; a document shifter mechanism  50 ; and a delivery tray  566 . The scanning unit  562  includes: a light source  562   a  (e.g., a halogen lamp) for irradiating a document conveyed from the document tray  511  or a document placed on the placement base  561 ; and a mirror  562   b  for guiding to a predetermined optical path the light reflected in the document. Further, the scanning unit  563  includes mirrors  563   a  and  563   b  for guiding to a predetermined optical path the light reflected in the document. 
     The image formation lens  564  causes the reflected light guided from the scanning unit  563  to form an image at a predetermined position on the CCD line sensor  565 . The CCD line sensor  565  performs photoelectric conversion on the formed optical image so as to output an electrical signal. That is, on the basis of a color image read from the document (e.g., the front surface of the document), data having been separated into color components of R (red), G (green), and B (blue) is outputted to the color image processing apparatus  2 . 
       FIGS. 27 and 28  are transverse sectional views showing the configuration of the document shifter mechanism  50 . The document shifter mechanism  50  includes bodies  51  and  52  that have a rectangular transverse cross section and that are separable into up and down. The body  51  is supported by the lower housing  560 , while the body  52  is supported by the upper housing  510 . The body  52  includes an offset member  60 , a revolution driving source  65 , a driving transmission member  70 , an offset driving source  75 , and an offset driving transmission member  80 . 
     The offset member  60  is movable in the horizontal direction (in the figure, Y-direction, that is, a direction perpendicular to the document delivery direction), and includes: a body  61  having a rectangular transverse cross section and arranged inside the body  52 ; and offset rollers  62 , . . . separated at appropriate intervals along the longitudinal direction of the body  61 . When moving horizontally, the offset member  60  achieves offset document delivery (a document is delivered in a state shifted horizontally depending on the category of each document). The body  61  supports the offset rollers  62 , . . . in a revolvable manner for the purpose of delivery of the document in the conveyance direction. At the time of the delivery of the document, the offset rollers  62 , . . . chucks the document so as to deliver it onto the delivery tray  566 . 
     The driving transmission member  70  includes: a driving gear  71  connected to the revolution driving source  65 ; a shaft  72  fitted into the center part of the driving gear  71 ; a linkage gear  73   a  arranged on the shaft  72 ; a sliding member  74 ; and a linkage gear  73   b  screwed to the linkage gear  73   a . In the center part of the linkage gear  73   b , a bar-shaped support member  63  is fitted in. On the support member  63 , offset rollers  62 , . . . are fixed in a state separated at appropriate intervals. Accordingly, a driving force from the revolution driving source  65  is transmitted to the offset rollers  62 . 
     The shaft  72  is supported in a horizontally revolvable manner, while the sliding member  74  can slide on the shaft  72 . Further, the shaft  72  can move the offset member  60  in a direction (horizontal direction) perpendicular to the delivery (conveyance) direction for the document, via the sliding member  74  and the linkage gears  73   a  and  73   b . Furthermore, in order to restrict the horizontal moving range of the linkage gears  73   a  and  73   b  and the offset member  60 , the shaft  72  has a restriction member  72   a  engaged with a hole  74   a  that is provided in the sliding member  74  and that is elongated in the axis direction. When moving along the inner side of the hole  74   a , the restriction member  72   a  abuts against the two ends of the hole  74   a , so that the horizontal moving range of the linkage gears  73   a  and  73   b  and the offset member  60  is restricted. 
     A driving force from the revolution driving source  65  is transmitted to the driving gear  71 . Thus, the driving gear  71  revolves, so that the shaft  72  revolves. In response to the revolution of the shaft  72 , the revolution is transmitted to the linkage gears  73   a  and  73   b . Then, the revolution of the linkage gear  73   b  causes the support member  63  to revolve, so that the offset rollers  62 , . . . revolve. Offset roller  64 , . . . that abut against the offset rollers  62 , . . . and that revolve and follow the revolution of the offset rollers  62 , . . . are arranged on a support member  68  arranged in parallel to the support member  63 . 
     To the offset driving sources  75  and  75  arranged respectively in the upper housing  510  and the lower housing  560 , offset driving transmission members  80  and  80  each composed of a pinion gear  81  and a rack gear  82  are connected respectively. The bodies  61  and  61  are fixed to the rack gears  82  and  82 . In response to revolution of pinion gear  81 , the rack gear  82  is moved horizontally (in the Y-direction in the figure). As a result, the rack gears  82  and  82  move the bodies  61  and  61  horizontally. The offset driving sources  75  and  75  are controlled synchronously in response to the determination signal outputted from the document matching process section  22 , and thereby move the bodies  61  and  61  to different positions in the horizontal direction. As a result, the offset rollers  62 , . . . and the offset rollers  64 , . . . are simultaneously offset (shifted) in the same direction, so that the delivery position for the document is controlled. 
     In comparison with the case of  FIG. 27 , in  FIG. 28 , the offset rollers  62 , . . . and the offset rollers  64 , . . . are offset. 
       FIG. 29  is an explanation diagram showing a delivery position for the document. This figure shows an exemplary case that read documents are sorted into three: documents similar to a stored format (category C 1 ); documents not similar to a stored format (category C 2 ); and documents similar to a stored format and having entry omission (category C 3 ). For example, in accordance with the categories C 1 , C 2 , and C 3 , the delivery position for each document is offset (shifted), for example, by 1 inch or the like as indicated by Y 1 , Y 2 , and Y 3  in a direction perpendicular to the delivery (conveyance) direction for the document (the Y-direction). By virtue of this, when a user desires to read a large number of documents, in addition to the advantage that documents similar to stored formats are classified easily in comparison with the conventional art, documents with entry omission can also be sorted and classified. This improves the user&#39;s convenience. Here, the offset amount (shift amount) for the documents is not limited to 1 inch. 
       FIGS. 30A to 30D  are explanation diagrams showing examples of screen display that notifies entry omission. As shown in  FIGS. 30A to 30D , screen messages displayed in the case of presence of entry omission include: “document (document name xxx) has entry omission” which indicates the presence of entry omission; “name field in document (document name xxx) is not filled in” which notifies also the part of entry omission; “page OO of document has entry omission” which specifies the page of the document with entry omission in a case that a large number of documents are read; and “document xxx has entry omission and hence was delivered in a manner separated from the other documents” which indicates that a document with entry omission has been separated and delivered. Here, the screen display is not limited to these examples. 
     Embodiment 2 
     The paper sheet material of a document to be read is not restrict to white paper, and can be recycled paper or thinly colored paper. Even in such cases, when the page background removing processing is performed on the document image, the presence or absence of entry omission can be determined with satisfactory accuracy. In this case, the page background removing processing may be performed in the document matching process section  22  (a page background removing processing section is provided in the document matching process section  22 ). Alternatively, the input tone correction section  23  may be provided in the subsequent stage of the shading correction section  21 , and then the document matching process section  22  may be provided in the subsequent stage of the input tone correction section  23 , so that the page background removing processing may be performed in the input tone correction section  23 . 
     In a case that the page background is to be removed from the document image, the stored format is stored in a state that the page background removing processing has been performed similarly. Alternatively, the page background removing is performed on the document image such that its page background should be at the same level as the page background of the stored format. This may be achieved by setting up appropriately a density correction table used in the page background removing. 
     The document matching process section  22  extracts a signal obtained by correction inversion of the G signal among the RGB signals inputted from the shading correction section  21 , and then generates a density histogram of the document image with a condition that, for example, 256 density steps are divided into 16 bins. 
     Further, the maximum of density values determined as being the page background is stored in advance as a first threshold value in the memory  226 . At the same time, the number of pixels in which the pixels are determined as being the page background when exceeding that number of pixels, that is, the minimum in the number of pixels determined as being the page background, is stored in advance as a second threshold value in the memory  226 . Further, a density correction table used for removing the page background in correspondence to the density segment determined as being the background is stored in the memory  226 . 
     The document matching process section  22  searches from the high density side of the generated density histogram, so as to extract as being the background a density segment that has a density value smaller than or equal to the first threshold value density segment which is determined as being the background and that has the number of pixels greater than or equal to the second threshold value density segment. The document matching process section  22  performs the background removing processing by using the density correction table corresponding to the density segment extracted as being the page background. Here, in place of the G signal, a luminance signal ( 255 -Yj) may be used. Here, when the color components RGB of each pixel is denoted respectively by Rj, Gj, and Bj, Yj is expressed by Yj=0.30×Rj+0.59×Gj+0.11×Bj. 
       FIGS. 31 and 32  are flow charts showing a procedure of entry item determination processing according to Embodiment 2. The control section  227  transforms the coordinate system (coordinate values) of a stored format determined as being similar to the document image into the coordinate system (coordinate values) of the document image (S 121 ). Here, in this case, similarly to Embodiment 1, coordinate transformation may be performed on the entire stored format. Alternatively, coordinate transformation may be performed only on entry fields having been set up in the stored format. 
     On the basis of the signal obtained by correction inversion of the G signal extracted from the document image, the control section  227  generates a density histogram of the document image (S 122 ), and then extracts the page background by searching from the high density side of the generated density histogram (S 123 ). The control section  227  removes the page background of the document image by using the density correction table corresponding to the density segment extracted as being the page background (S 124 ). 
     The control section  227  searches the determination area table  2265  and thereby obtains the item names and the coordinate values of the individual item names of the stored format determined as being similar to the document image (S 125 ). Then, on the basis of the obtained coordinate values, the control section  227  specifies, on the document image and the stored format, entry item determination regions where entry omission is to be determined (S 126 ). 
     The control section  227  sets into “0” the number M of determined pixels that indicates the number of pixels having the same pixel value (e.g., luminance value) among individual pixels between the document image and the stored format (S 127 ), and then scans the current pixels in the document image and the stored format in the entry item determination regions, so as to calculate the difference of the pixel values for each current pixel (S 128 ). 
     The control section  227  determines whether the calculated difference is smaller than the difference threshold value Tg (S 129 ). When the difference is smaller than the difference threshold value Tg (YES at S 129 ), the control section  227  adds “1” to the number M of determined pixels (S 130 ). The control section  227  determines whether the processing has been completed for all the pixels of the entry item determination regions in the document image and the stored format (S 131 ). When processing for all the pixels is not yet completed (NO at S 131 ), the control section  227  continues the processing at and after step S 128 . 
     When the difference is not smaller than the difference threshold value Tg (NO at S 129 ), the control section  227  continues the processing at and after step S 131 . When the processing has been completed for all the pixels (YES at S 131 ), the control section  227  determines whether the ratio expressed by (the number M of determined pixels/the number of pixels in the stored format) is greater than the ratio threshold value Ts (S 132 ). 
     When the ratio is greater than the ratio threshold value Ts (YES at S 132 ), the control section  227  concludes the presence of entry omission (S 133 ), then records item names with entry omission (S 134 ), and then determines whether processing for all the determination regions has been completed (S 135 ). On the other hand, when the ratio is not greater than the ratio threshold value Ts (NO at S 132 ), the control section  227  concludes the absence of entry omission (S 136 ), and then continues the processing at and after step S 135 . 
     When determining that processing for all the determination regions is not yet completed (NO at S 135 ), the control section  227  continues the processing at and after step S 127 . When determining that the processing has been completed for all the determination regions (YES at S 135 ), the control section  227  terminates the processing. 
     As a result, even when the paper sheet material of the read document is recycled paper or thinly colored paper, the presence or absence of entry omission can be determined with satisfactory accuracy. 
     Embodiment 3 
     Embodiments 1 and 2 have been described for the configuration that the presence or absence of entry omission is determined on the basis of the ratio expressed by (the number M of determined pixels/the number of pixels in the stored format). However, the entry omission determination processing is not limited to this configuration. That is, entry omission determination processing may be achieved by the document matching process section  22  calculating the number of pixels. 
       FIGS. 33 and 34  are flow charts showing a procedure of entry item determination processing according to Embodiment 3. The control section  227  transforms the coordinate system (coordinate values) of a stored format determined as being similar to the document image into the coordinate system (coordinate values) of the document image (S 141 ). In this case, coordinate transformation may be performed on the entire stored format. Alternatively, coordinate transformation may be performed only on entry fields determined in advance in the stored format. 
     The control section  227  searches the determination area table  2265  and thereby obtains the item names and the coordinate values of the individual item names of the stored format determined as being similar to the document image (S 142 ). Then, on the basis of the obtained coordinate values, the control section  227  specifies, on the document image and the stored format, entry item determination regions where entry omission is to be determined (S 143 ). 
     The control section  227  sets into “0” the number M of determined pixels that indicates the number of pixels having the same pixel value (e.g., luminance value) among individual pixels between the document image and the stored format (S 144 ), and then scans the current pixels in the document image and the stored format in the entry item determination regions, so as to calculate the difference of the pixel values for each current pixel (S 145 ). 
     The control section  227  determines whether the calculated difference is smaller than the difference threshold value Tg (S 146 ). When the difference is smaller than the difference threshold value Tg (YES at S 146 ), the control section  227  adds “1” to the number M of determined pixels (S 147 ). The control section  227  determines whether the processing has been completed for all the pixels of the entry item determination regions in the document image and the stored format (S 148 ). When processing for all the pixels is not yet completed (NO at S 148 ), the control section  227  continues the processing at and after step S 145 . 
     When the difference is not smaller than the difference threshold value Tg (NO at S 146 ), the control section  227  continues the processing at and after step S 148 . When the processing has been completed for all the pixels (YES at S 148 ), the control section  227  determines whether the number M of determined pixels is greater than the number-of-pixels threshold value (S 149 ). 
     When the number M of determined pixels is greater than the number-of-pixels threshold value (YES at S 149 ), the control section  227  concludes the presence of entry omission (S 150 ), then records item names with entry omission (S 151 ), and then determines whether processing for all the determination regions has been completed (S 152 ). On the other hand, when the number M of determined pixels is not greater than the number-of-pixels threshold value (NO at S 149 ), the control section  227  concludes the absence of entry omission (S 153 ), and then continues the processing at and after step S 152 . 
     When determining that processing for all the determination regions is not yet completed (NO at S 152 ), the control section  227  continues the processing at and after step S 144 . When determining that the processing has been completed for all the determination regions (YES at S 152 ), the control section  227  terminates the processing. 
     When the configuration that the number of pixels is calculated is adopted, the presence or absence of entry omission can be determined with satisfactory accuracy even in the case of tiny entry omission regardless of the size of the area of the entry field in the document. 
     In this case, in the entry item determination processing, in the determination regions (determination parts), the differences of the pixel values owned by the obtained document image and the stored format (stored image) are calculated. Then the calculated difference values are compared with a predetermined threshold value (difference threshold value), so that the number of pixels (the number of determined pixels) having approximately the same pixel value is calculated. Then, the calculated number of determined pixels is compared with a predetermined threshold value (large and small comparison). Then, the presence or absence of entry omission is determined in accordance with the comparison result. 
     Embodiment 3 described above has the configuration that the presence or absence of entry omission is determined on the basis of the number of the pixels having approximately the same pixel value with respect to the current pixel between the document image and the stored format. However, the present invention is not limited to this. For example, the number of pixels having different pixel values with each other with respect to the current pixel between the document image and the stored format may be calculated in the entry omission determination regions. Then, the calculated number of pixels may be compared with a predetermined threshold value, so that the presence or absence of entry omission may be determined. In this case, it is determined whether the number of pixels having different pixel values with each other is smaller than a predetermined threshold value. Then, when the number of pixels having different pixel values is smaller than the predetermined threshold value, the presence of entry omission is concluded. In contrast, when the number of pixels having different pixel values is not smaller than the predetermined threshold value, the absence of entry omission is concluded. 
     Further, the document image and the stored format within the entry omission determination regions may be binarized with a predetermined binarization threshold value. Then, the numbers of pixels after the binarization may be calculated. Then, entry omission may be determined on the basis of the difference in the calculated numbers of pixels. In this case, for example, when the difference between the number of pixels in the document image and the number of pixels in the stored format is smaller than a predetermined number-of-pixels threshold value, the presence of entry omission is concluded. In contrast, when the difference is not smaller than the predetermined number-of-pixels threshold value, the absence of entry omission is concluded. Further, in place of the configuration that the number of pixels after binarization is calculated, the number of black pixels in the document image may be calculated. 
     Further, the processing of determining the presence or absence of entry omission on the basis of the ratio shown in  FIGS. 23  and  24  (or  FIGS. 31 and 32 ) and the processing of determining the presence or absence of entry omission by calculating the number of pixels shown in  FIGS. 33 and 34  may be employed simultaneously. In this case, when the ratio expressed by (the number M of determined pixels/the number of pixels in the stored format) is greater than the ratio threshold value Ts and the number M of determined pixels is greater than the number-of-pixels threshold value, the control section  227  concludes the presence of entry omission. In contrast, when the ratio expressed by (the number M of determined pixels/the number of pixels in the stored format) is not greater than the ratio threshold value Ts and the number M of determined pixels is not greater than the number-of-pixels threshold value, the control section  227  concludes the absence of entry omission. Here, when any one of the criteria is not satisfied, priority may be imparted to any one of the determination results depending on the kind of the document or the like. 
     When the entry omission determination based on the ratio and the entry omission determination based on the number of pixels are employed simultaneously, determination accuracy for the presence or absence of entry omission is improved further. 
     Embodiment 4 
     Embodiments 1 to 3 have been described for the configuration that the document shifter mechanism  50  is provided. However, the configuration of the document shifter mechanism is not limited to that the document is offset when delivered. That is, the delivery tray may be moved in a direction perpendicular to the delivery (conveyance) direction for the document. In this case, the document need not be shifted by the document shifter mechanism. That is, mere a mechanism for document delivery (conveyance) is sufficient. 
       FIG. 35  is a schematic diagram showing the configuration of a document shifter mechanism  300  in a case that a delivery tray is movable.  FIG. 36  is a transverse sectional view showing the configuration of the document shifter mechanism  300 . The document shifter mechanism  300  includes: a supporting tray member  301  fixed to the main body of the document reading apparatus; and a movable tray member  302  arranged on the supporting tray member  301 . Here, the configuration of the document reading apparatus  500  is similar to that of Embodiment 1. Thus, like parts are denoted by like numerals, and description is omitted. 
     In the supporting tray member  301 , a recess  303  is provided that has a rectangular shape in a plane view and is slightly smaller than the outer dimension. Two metal bar-shaped guide shafts  304  and  305  separated at an appropriate interval approximately in parallel to each other are attached in a manner of being accommodated in the recess  303 . Specifically, the guide shafts  304  and  305  are inserted through respectively through holes  310 ,  311 ,  312 , and  313  formed in the side walls of the supporting tray member  301  and bearings  306 ,  307 ,  308 , and  309  provided vertically on the bottom surface of the recess  303  at appropriate intervals, and then are supported by the bearings  306 ,  307 ,  308 , and  309  in a movable manner. 
     In the center part of the recess  303 , a driving unit (not shown) is provided that includes; a motor; a reduction gearbox (not shown) incorporating a gear train is built; and a pinion  314 . The revolution of the motor is slowed down by the gear train and then transmitted to the pinion  314 . In the inside of the upper face of the movable tray member  302 , a rack  315  is attached that is arranged in parallel to the guide shafts  304  and  305  and engages with the pinion  314 . When the pinion  314  revolves, the rack  315  moves in the direction of the axes of the guide shafts  304  and  305 . 
     Further, in the side edge parts of the movable tray member  302 , protruding rim sections  316  and  317  are formed along the side edges (in the conveyance direction for the document). In the protruding rim sections  316  and  317 , bearings  320 ,  321 ,  322 , and  323  are provided into which the individual ends of the guide shafts  304  and  305  are inserted respectively and which support the guide shafts  304  and  305  in a movable manner. By virtue of the configuration described here, when the motor is driven so that the pinion  314  revolves, the revolution of the pinion  314  is transmitted to the rack  315 . Thus, the movable tray member  302  is guided by the guide shafts  304  and  305  so as to move in a direction (the direction indicated by an arrow in the figure) perpendicular to the conveyance direction for the sheet relative to the supporting tray member  301 . Here, the means for moving the movable tray member  302  is not limited to a rack and pinion mechanism, and may be another mechanism such as an endless belt mechanism and a linear motor. 
     In a case that the movable tray member  302  is to be moved in a direction perpendicular to the delivery (conveyance) direction for the document, for example, similarly to Embodiment 1, the amount of movement may be 1 inch or the like. By virtue of this, when a user desires to read a large number of documents, in addition to the advantage that documents similar to stored formats are classified easily in comparison with the conventional art, documents with entry omission can also be sorted and classified. This improves the user&#39;s convenience. Here, the offset amount (shift amount) for the documents is not limited to 1 inch. 
     Embodiment 5 
     Embodiments 1 to 4 have been described for the configuration that the document is offset at the time of delivery. However, the method of delivering documents in a sorted manner is not limited to this. That is, a plurality of delivery trays may be provided. Then, in response to the determination signal, the delivery tray into which the document is to be delivered may be switched. 
       FIG. 37  is a schematic diagram showing the configuration of a document reading apparatus  501  according to Embodiment 5. A document conveying section  520  includes: a document tray  521 ; a pickup roller  522   a  a shuffling roller  522   b  that are revolvable and that convey one by one the document sheets placed and stacked in the document tray  521 ; a conveyance path  525  for conveying the conveyed document to delivery trays  527   a ,  527   b , and  527   c ; and a resist roller  524   a , a conveyance roller  524   b , and a delivery roller  524   c  appropriately provided in the middle of the conveyance path  525 . 
     In the downstream of the delivery roller  524   c , gates  523   b ,  523   d  (located downward by means of flexibility or self-weight), and  523   c  are provided that switch the delivery tray into which the document is to be delivered. A conveyance roller  524   d  is arranged between the gate  523   d  and the gate  523   c . When the document is delivered, on the basis of the determination signal, the gates  523   b ,  523   d , and  523   c  are driven such that read documents (category C 1 ) being similar to the stored format are delivered into the delivery tray  527   a , documents (category C 2 ) not being similar to the stored format are delivered to the delivery tray  527   b , and documents (category C 3 ) being similar to the stored format and having entry omission are delivered into the delivery tray  527   c.    
     That is, when a document of category C 1  is to be delivered, the gate  523   b  is driven upward, so that the document is delivered into the delivery tray  527   a . Further, when a document of category C 2  is to be delivered, the gate  523   b  is driven downward while the gate  523   c  is driven upward, so that the document is delivered to the delivery tray  527   b . Furthermore, when a document of category C 3  is to be delivered, the gate  523   b  is driven downward while the gate  523   c  is driven downward, so that the document is delivered to the delivery tray  527   c.    
     In the document placing surface of the document tray  521 , a document sensor  521   a  is provided that detects the presence or absence of a document. When all the documents placed in the document tray  521  have been conveyed out, the document sensor  521   a  outputs a signal that indicates that no document is present. This permits determination whether the conveyance-out of all the document has been completed. 
     In the downstream of the shuffling roller  522   b , a document conveyance path  526  is provided that is separated from the conveyance path  525  and curved by approximately 180 degrees. In the middle of the document conveyance path  526 , a revolvable document roller  524   e  is provided, while the delivery tray  527   c  is attached in a manner connecting to the document conveyance path  526 . The pickup roller  522   a , the shuffling roller  522   b , and the document roller  524   e  revolve in forward and backward directions by means of a roller driving section (not shown). 
     At the branch point between the conveyance path  525  and the document conveyance path  526 , a gate  523   a  is arranged that can swing by means of a gate driving section (not shown). When the gate  523   a  is driven downward, a document placed in the document tray  521  is conveyed toward the conveyance path  525 . On the other hand, when the gate  523   a  is driven upward, a document once delivered into the delivery tray  527   c  is conveyed to the document tray  521 . That is, in the present embodiment, when a document with entry omission need be read again, re-reading can be performed automatically. 
     The scanner section constructed in the lower housing  560  is similar to that of Embodiments 1 to 4. Thus, like parts are denoted by like numerals, and description is omitted. 
     Embodiment 6 
     Embodiment 5 has been described for the configuration that a plurality of delivery trays are built in the document reading apparatus  501 . However, the method of delivering documents in a sorted manner is not limited to this, and another configuration may be adopted. For example, a configuration may be employed in which in place of the delivery trays, an option mechanism is provided that has a plurality of steps of delivery trays. 
       FIG. 38  is a schematic diagram showing the configuration of a document reading apparatus  502  according to Embodiment 6. As shown in the figure, an option mechanism  530  is provided that delivers documents in a sorted manner. The option mechanism  530  includes: delivery trays  534   a ,  534   b ,  534   c , and  534   d ; gates  533 , . . . for switching the conveyance path for the document in order to deliver the document into each delivery tray in a sorted manner; and delivery rollers  532 , . . . . 
     Embodiment 7 
     In each embodiment described above, in the determination of the presence or absence of entry omission, the pixel values have been compared between the document image and the stored format. However, the method of determination of the presence or absence of entry omission is not limited to this. That is, without the necessity of comparison with the pixel value of the stored format, the presence or absence of entry omission in the document image can be determined only on the basis of the document image. 
       FIG. 39  is a block diagram showing the configuration of an entry item determination processing section  228  according to Embodiment 7. The entry item determination processing section  228  includes a pixel value calculating section  2281 , a distribution calculating section  2282 , an edge pixel determining section  2283 , and a determining section  2284 . Processing in the individual sections described here is controlled by the control section  227 . Further, data obtained in the individual sections described here is stored in the memory  226 . Similarly to Embodiment 1, before the determination processing whether a document image has entry omission, the entry item determination processing section  228  performs: position alignment processing for aligning the positions between the document image and the stored format; and the processing of specifying entry omission determination regions. The contents of the processing is similar to that of Embodiment 1, and hence description is omitted. 
     For each pixel within a pixel block (e.g., a first pixel block composed of 7×7 pixels) composed of a plurality of pixels containing a current pixel in an inputted document image (image data), the pixel value calculating section  2281  calculates the average of the density values of the individual pixels within a pixel block (e.g., a second pixel block composed of 7×7 pixels) composed of a plurality of pixels containing the above-mentioned each pixel, and then adopts the calculated average as the pixel value of the above-mentioned each pixel. As a result, the average of each pixel (49 pixels, in this example) in the first pixel block containing the current pixel is obtained. Here, the pixel value to be calculated is not limited to the average. That is, another quantity may be calculated like the central value of the density values of the individual pixels in the second pixel block. 
     The distribution calculating section  2282  searches for the average of each pixel within the first pixel block composed of a plurality of pixels containing the current pixel, and then calculates the maximum density difference in the first pixel block. Here, the value to be calculated is not limited to the maximum density difference. That is, the variance or the like may be calculated as long as the distribution of the pixel values in the first pixel block can be recognized. 
     The edge pixel determining section  2283  compares the maximum density difference calculated by the distribution calculating section  2282  with an edge determination threshold value (e.g., 30) defined in advance. Then, when the maximum density difference is greater than the edge determination threshold value, the edge pixel determining section  2283  determines that the current pixel in the first pixel block is an edge pixel, and then adds 1 to the number of edge pixels so as to count the number of edge pixels. 
     Here, the above-mentioned processing of pixel value calculation, distribution calculation, and edge pixel determination is repeated for all the current pixels in the document image. 
     For each document image, the determining section  2284  compares the number of edge pixels counted by the edge pixel determining section  2283  with a predetermined first determination threshold value (e.g., 5000). Then, when the number of edge pixels is greater than the first determination threshold value, the determining section  2284  determines that the document image has no entry omission, that is, has an entry. In contrast, when the number of edge pixels is smaller than the first determination threshold value, the determining section  2284  determines that the document image has entry omission, that is, does not have an entry. 
     When the document image is a color document, the entry item determination processing section  228  may perform the above-mentioned processing for each plane (each color component) of RGB. Further, in a case that the current pixel is determined as being an edge pixel when the maximum density difference of any color component among a plurality of color components is greater than the edge determination threshold value, the page background removing need not be performed. Here, the above-mentioned processing may be performed only on a part of the color components. In this case, the processing ability is reduced. 
       FIG. 40  is a flow chart showing a processing procedure in an entry item determination processing section  228  according to Embodiment 7. Here, similarly to the above-mentioned embodiment, in addition to being performed by a dedicated hardware circuit, the document matching process may be performed by a method in which a computer program that defines the procedure of document matching process is loaded onto a personal computer having a CPU, a RAM, a ROM, and the like and then the computer program is executed by the CPU. 
     The control section  227  transforms the coordinate system (coordinate values) of a stored format determined as being similar to the document image into the coordinate system (coordinate values) of the document image (S 161 ). In this case, coordinate transformation may be performed on the entire stored format. Alternatively, coordinate transformation may be performed only on entry fields determined in advance in the stored format. 
     The control section  227  searches the determination area table  2265  and thereby obtains the item names and the coordinate values of the individual item names of the stored format determined as being similar to the document image (S 162 ). Then, on the basis of the obtained coordinate values, the control section  227  specifies, on the document image, entry item determination regions where entry omission is to be determined (S 163 ). 
     The control section  227  calculates the average of each pixel within the pixel block (the first pixel block) containing the current pixel (S 164 ), and then searches the calculated average so as to calculate the maximum density difference in the first pixel block (S 165 ). 
     The control section  227  determines whether the calculated maximum density difference is greater than an edge determination threshold value (e.g., 30) (S 166 ). When the maximum density difference is greater than the edge determination threshold value (YES at S 166 ), the control section  227  determines that the current pixel is an edge pixel, so as to count edge pixels (S 167 ). At this time, the edge pixel counting is performed by adding 1 to the number of edge pixels at each time of determination as being an edge pixel. When the maximum density difference is not greater than the edge determination threshold value (NO at S 166 ), the control section  227  performs the later-described processing of step S 168 , without counting the number of edge pixels. 
     The control section  227  determines whether processing for all the pixels in the document image have been completed (S 168 ). When processing for all the pixels is not yet completed (NO at S 168 ), the processing is changed to the next current pixel, and then the processing at and after step S 164  is continued. When processing for all the pixels has been completed (YES at S 168 ), that is, when the processing has been completed for all the pixels in the document image, the control section  227  determines whether the number of counted edge pixels is greater than a first determination threshold value (e.g., 5000) (S 169 ). 
     When the number of edge pixels is greater than the first determination threshold value (YES at S 169 ), the control section  227  concludes the absence of entry omission in the document image (S 170 ), and then terminates the processing. In contrast, when the number of edge pixels is not greater than the first determination threshold value (NO at S 169 ), the control section  227  concludes the presence of entry omission in the document image (S 171 ), and then terminates the processing. 
     According to Embodiment 7, the presence or absence of entry omission can be determined only on the basis of the image data of a document image without using the image data of a stored format. Further, the average of the density values within a pixel block (the first pixel block) composed of a plurality of pixels containing the current pixel is calculated for each color component. This suppresses the influence of isolated points and noise at the time of reading and the influence of dirt in the base sheet of the document or dust adhering to the base sheet of the document. Accordingly, determination accuracy for the presence or absence of entry omission is improved. 
     Embodiment 8 
     In each embodiment described above, the presence or absence of entry omission has been determined in a document image. However, the present invention is not limited to determination for a document image, and may be applied to electronic data (data generated by application software) or electronized data (data generated by converting data read by a scanner into a predetermined file format such as JPEG and PDF). 
     For example, data provided in the form of electronic data or electronized data may be stored in a server. Then, the present invention in the form of application software may be applied to such data. Preferably, the data described here is stored separately for each electronic data and file format. 
     As for electronic data, several kinds of software can be used. Thus, for example, using a RIP (raster image processor), PDL (Page Description Language) may be interpreted and converted into a raster image (RGB data). Then, the method of the present invention may be applied. 
     Further, as for electronized data, for example, in the case of an encoded image format such as JPEG and GIF, the method of the present invention may be applied, after decoding is once performed and then color conversion processing of converting YCC signals into RGB signals is performed when necessary. 
     As for a PDF format, when the image data is saved in an encoded image format such as JPEG, the method of the present invention may be applied after decoding and conversion into RGB signals are performed. As for a vector data part such as a font, the method of the present invention may be applied after conversion into image data of RGB is performed by a RIP or the like. In the case of a PDF format, information concerning each object (such as a text, a diagram, and a photograph) is stored as a tag. Thus, the data conversion can be performed with reference to this information. For example, in the case of a text, the information concerning an object includes the font, the point size, the color, and the display position. In the case of a photograph, the information includes the coding method, the size, and the display position. 
     As described above, according to the present invention, in similarity determination for a document image, entry omission (erroneous omission) in the document image can be determined with satisfactory accuracy. Further, in the case of presence of entry omission, the part with entry omission can easily be determined. 
     Further, in the preceding stage of the determination whether a document image has entry omission, the page background removing is performed on the document image. Accordingly, even in a case that the paper sheet material of the read document is different from that of the stored image like recycled paper and thinly colored paper, the presence or absence of entry omission can be determined with satisfactory accuracy. 
     Further, this permits determination of entry omission in the document image with satisfactory accuracy only on the basis of the obtained document image without the necessity of comparison of the pixel values of the document image and the stored image. Furthermore, this suppresses the influence of isolated points in the document image and noise at the time of reading and the influence of dirt in the base sheet of the document or dust adhering to the base sheet. Accordingly, determination accuracy for entry omission is improved further. 
     Further, at the time of document delivery, this permits sorting into documents with entry omission and documents without entry omission. In particular, in a case that a large number of documents are to be read, documents with entry omission are easily sorted from among a large number of delivered documents. This improves the user&#39;s convenience. Further, documents with entry omission can easily be separated. 
     In the above-mentioned embodiment, the stored formats and the hash table  2262  have been stored in the memory  226  in advance. However, the present invention is not limited to this. That is, the stored formats may be stored in a storage section of a server apparatus connected to the image forming apparatus  100  through a communication line (network), while the hash table  2262  may be stored in the memory  226  in a distributed manner. 
     In the above-mentioned embodiment, the color image input apparatus  1  may be implemented by, for example, a flat-bed scanner, a film scanner, a digital camera, or a portable telephone. Further, the color image output apparatus  3  may be implemented by, for example: an image display device such as a CRT display and a liquid crystal display; or a printer employing an electrophotography method or an inkjet method that outputs the processing result onto a recording paper sheet or the like. Furthermore, the image forming apparatus  100  may be provided with a modem serving as communication means for connecting with a server apparatus and the like via a network. Further, in place of acquiring color image data from the color image input apparatus  1 , the color image data may be obtained from an external storage device, a server apparatus, or the like via a network. 
     In the above-mentioned embodiment, the memory  226  and the control section  227  have been provided in the inside of the document matching process section  22 . However, the present invention is not limited to this. That is, the memory  226  and the control section  227  may be provided in the outside of the document matching process section  22 . 
     In the present invention, a program code for performing the document matching process, the entry omission notifying processing, the document delivery control processing, and the like may be recorded in a computer-readable recording medium used for carrying a program code (an executable form program, an intermediate code program, or a source program) to be executed by a computer. As a result, a recording medium that carries a program code for performing the above-mentioned processing is provided in a freely portable manner. In order that that processing can be performed by a microcomputer, the recording medium may be a program medium such as a memory (not shown) like a ROM. Alternatively, a program media of another type may be employed in which a program reading apparatus serving as an external storage device (not shown) is provided, and a recording medium is inserted into there so that the recording medium is read. 
     In these cases, the stored program code may be accessed and executed directly by a microprocessor. Alternatively, the program code may be read out, then the read-out program code may be downloaded into a program storage area (not shown) in a microcomputer, and then the program code may be executed. In this case, a computer program for download is stored in the main apparatus in advance. 
     Here, the above-mentioned program medium is a recording medium separable from the main body, and may be: a tape system such as a magnetic tape and a cassette tape; a disk system such as a magnetic disk (including a flexible disk and a hard disk) and an optical disk such as CD-ROM/MO/MD/DVD; a card system such as an IC card (including a memory card) and an optical card; and a medium that carry a program code in a fixed manner, including a semiconductor memory such as a mask ROM, an EPROM (Erasable Programmable Read Only Memory), an EEPROM (Electrically Erasable Programmable Read Only Memory), and a flash ROM. 
     Further, in this case, since the employed system configuration permits connection to a communication network including the Internet, the medium may carry the program code dynamically, for example, by means of downloading the program code from a communication network. Here, when the program code is to be downloaded from a communication network, a computer program for download may be stored in the main apparatus in advance, or alternatively may be installed from another recording medium. Here, the present invention may be implemented in the form of a computer data signal in which the above-mentioned program code is embedded in a carrier wave embodied by electronic transmission. 
     As this invention may be embodied in several forms without departing from the spirit of essential characteristics thereof, the present embodiment is therefore illustrative and not restrictive, since the scope of the invention is defined by the appended claims rather than by the description preceding them, and all changes that fall within metes and bounds of the claims, or equivalence of such metes and bounds thereof are therefore intended to be embraced by the claims.