JP2008141683A - Image processing apparatus and method, program, and storage medium - Google Patents

Abstract

A highly reliable original guarantee without misjudgment can be realized using accurate original information.
First image data of an image obtained by scanning a sheet with a scanner unit is acquired (S1501, S1502). Second image data of an image obtained by scanning the paper in another direction by the scanner unit is acquired (S1503, S1504). Mask data for masking noise generated by the scanner unit and included in the first and second image data is created based on the first and second image data (S1505). Mask data is registered and an image obtained by scanning is registered as an original (S1506).
[Selection] Figure 15

Description

  The present invention relates to an image processing apparatus and method, a program, and a storage medium. More specifically, the present invention relates to an image processing apparatus and an image processing method capable of handling paper fingerprint (hereinafter, paper fingerprint is also referred to as a paper print) information, a program for executing the method, and the program stored therein. The present invention relates to a storage medium.

In recent years, the color quality of copying machines and higher resolution have improved the quality of printed copies, making it difficult to distinguish between the original and the copy with the naked eye. A technique for guaranteeing safety has been devised. These conventional techniques can be seen in, for example, Patent Documents 1 to 3. In that case, a paper document to be managed as an original is scanned with a scanner, and a slight shadow pattern due to paper fibers is stored in the database as a characteristic characteristic of the paper. Register or write on the paper itself.

  In such an apparatus, generally, a blank area where nothing is printed is first detected, and a fiber pattern of the paper is read in the area.

JP 2004-102562 A JP 2004-112644 A JP 2006-245949 A

  As described above, in order to read a paper fiber pattern, it is necessary to use a high-sensitivity scanner or scan with a low light quantity of the scanner. In any case, slight stains, scratches, small dusts, etc. on the document table are read, and they become noise and are taken in as part of the paper pattern.

  The noise that has been captured as a paper print causes an erroneous determination at the time of matching the paper print.

  The present invention provides an image processing apparatus capable of realizing a highly reliable original guarantee by removing noise caused by slight dirt, scratches, dust, etc. of a scanner and collecting accurate original information when reading a paper pattern. It is an object to provide a method, a program, and a storage medium.

  In order to achieve the above object, an aspect of an image processing apparatus according to the present invention performs image processing for guaranteeing the originality of a sheet based on the characteristics of fibers constituting the sheet included in a scanned image of the sheet. In the image processing apparatus, means for acquiring first image data of an image obtained by scanning a sheet by an image scanning unit, and a second image obtained by scanning the sheet in another direction by the image scanning unit. The first and second image data are mask data for masking noise generated by the image scanning means and noise included in the first and second image data. And a registration means for registering the mask data and registering the image obtained by the scan as an original.

  In the apparatus according to the present invention, the first and second image data are data obtained from a scanned image of a paper fingerprint information acquisition region of the paper, and the mask data is the paper fingerprint information acquisition of the image scanning unit. It may mask noise generated at a part corresponding to the region.

  In order to achieve the above object, another aspect of the image processing apparatus according to the present invention performs image processing for examining the originality of the paper based on the characteristics of the fibers constituting the paper included in the scanned image of the paper. In the image processing apparatus to be performed, means for acquiring image data of an image obtained by scanning a sheet by the image scanning means, mask data and original image registered in the registration means provided in the image processing apparatus having the above-described aspect And the noise generated by the image scanning unit provided in the image processing apparatus configured as described above by using the acquired mask data is excluded from the target, and the scanned image of the sheet is the original Means for matching with images were provided.

  In order to achieve the above object, one aspect of an image processing method according to the present invention performs image processing for guaranteeing the originality of a sheet based on the characteristics of fibers constituting the sheet included in a scanned image of the sheet. In the image processing method, a step of acquiring first image data of an image obtained by scanning a sheet by an image scanning unit, and a step of obtaining an image obtained by scanning the sheet in another direction by the image scanning unit. Obtaining the second image data, mask data for masking the noise generated by the image scanning means and included in the first and second image data, as the first and second image data And a registration step of registering the mask data and registering an image obtained by the scan as an original.

  In the method of the present invention, the first and second image data are data obtained from a scanned image of a paper fingerprint information acquisition region of the paper, and the mask data is the paper fingerprint information acquisition of the image scanning unit. It may mask noise generated at a part corresponding to the region.

  In order to achieve the above object, another aspect of the image processing method according to the present invention provides image processing for examining the originality of the paper based on the characteristics of the fibers constituting the paper included in the scanned image of the paper. In the image processing method to be performed, a step of acquiring image data of an image obtained by scanning a sheet by an image scanning unit, a mask data and an original image registered by the method of the present invention, and the acquired mask data The method includes the step of excluding noise generated by the image scanning means by executing the above-described method of the present invention from the target and collating the scanned image of the sheet with the original image.

  In order to achieve the above object, one aspect of a program according to the present invention is an image processing for performing image processing for guaranteeing the originality of a sheet based on the characteristics of the fibers constituting the sheet included in the scanned image of the sheet. A program of a method, wherein the processing device scans the paper in another direction by the image scanning means, the means for acquiring first image data of an image obtained by scanning the paper by the image scanning means. Means for acquiring second image data of the obtained image, and mask data for masking noise generated by the image scanning means and included in the first and second image data. A function for creating based on the second image data, and a registration means for registering the mask data and registering the image obtained by scanning as an original To.

  In order to achieve the above object, another aspect of the program according to the present invention provides an image for performing image processing for examining the originality of the paper based on the characteristics of the fibers constituting the paper included in the scanned image of the paper. A processing method program for acquiring image data of an image obtained by scanning a paper sheet by an image scanning unit, and mask data and original image registered by the program of the present invention; By using the acquired mask data, the noise generated by the image scanning unit is excluded from the target by executing the program of the present invention, and the scanned image of the sheet is made to function as a unit for collating with the original image.

  In order to achieve the above object, one aspect of the storage medium according to the present invention stores the above-described program of the present invention.

  In order to achieve the above object, another aspect of the image processing apparatus according to the present invention is an image processing apparatus that performs image processing for guaranteeing the originality of a sheet based on the characteristics of fibers constituting the sheet. Means for acquiring first image data obtained by scanning the paper on the platen by the image scanning unit, and second obtained by scanning the paper at a different position on the platen by the image scanning unit. Means for obtaining the image data, means for removing noise on the platen of the image scanning means based on the first and second image data, and the image data based on the image data removed by the removing means A registration means for registering fiber information was provided.

  According to the present invention, two pieces of image data having different directions are acquired for a predetermined area of the paper, and the mask data masks noise generated in a portion corresponding to the predetermined area of the image scanning unit. Therefore, even if dirt, scratches, dust, etc. on the image scanning means affect both image data as noise, the noise generated by the image scanning means is excluded from the target by using the mask data, and the scanned image of the paper is It can be compared with the original image. Therefore, it is possible to realize highly reliable originality assurance without erroneous determination using accurate original information.

  The best mode for carrying out the present invention will be described below with reference to the drawings.

<Image processing apparatus (FIG. 1)>
FIG. 1 is a block diagram showing a configuration of an embodiment of an image processing apparatus according to the present invention. In this apparatus, the host computer 40 and three image forming apparatuses (10, 20, 30) are connected to the LAN 50. However, in the image processing apparatus according to the present invention, the number of connections is not limited. In this embodiment, LAN is applied as a connection method, but the present invention is not limited to this. For example, an arbitrary network such as a WAN (public line), a serial transmission method such as USB, and a parallel transmission method such as Centronics and SCSI can be applied.

  A host computer (hereinafter referred to as a PC) 40 has a function of a personal computer. The PC 40 can send and receive files and send and receive e-mails using the FTP and SMB protocols via the LAN 50 and WAN. A print command can be issued from the PC 40 to the image forming apparatuses 10, 20, and 30 via a printer driver.

  The image forming apparatuses 10 and 20 are apparatuses having the same configuration. The image forming apparatus 30 is an image forming apparatus having only a print function, and does not have the scanner unit included in the image forming apparatuses 10 and 20. In the following, for the sake of simplicity of explanation, the configuration will be described in detail focusing on the image forming apparatus 10 of the image forming apparatuses 10 and 20.

  The image forming apparatus 10 includes a scanner unit 13 as an image input device, a printer unit 14 as an image output device, a controller (Controller Unit) 11 that controls operation of the entire apparatus 10, and an operation unit 12 as a user interface (UI). Composed.

  Paper database information (grayscale image data and noise mask image data) described later can be registered in the database 100.

<Image Forming Apparatus 10 (FIG. 2)>
An appearance of the image forming apparatus 10 is shown in FIG. The scanner unit 13 has a plurality of CCDs. If the sensitivity of each CCD is different, it is recognized that each pixel has a different density even if the density of each pixel on the document is the same. Therefore, the scanner unit first performs exposure scanning on a white plate (uniformly white plate), converts the amount of reflected light obtained by exposure scanning into an electrical signal, and outputs the electrical signal to the controller 11. As will be described later, the shading correction unit 500 in the controller 11 recognizes the difference in sensitivity of each CCD based on the electrical signal obtained from each CCD. Then, using the recognized difference in sensitivity, the value of the electric signal obtained by scanning the image on the document is corrected. Further, when the shading correction unit 500 receives gain adjustment information from a CPU 301 in the controller 11 described later, the shading correction unit 500 performs gain adjustment according to the information. The gain adjustment is used to adjust how an electric signal value obtained by exposing and scanning a document is assigned to a luminance signal value of 0 to 255. By this gain adjustment, the value of the electrical signal obtained by exposing and scanning the document can be converted into a high luminance signal value or converted into a low luminance signal value. Next, a configuration for scanning the image on the document will be described.

  The scanner unit converts the image information into an electrical signal by inputting the reflected light obtained by exposing and scanning the image on the document to the CCD. Further, the electric signal is converted into a luminance signal composed of R, G, and B colors, and the luminance signal is output to the controller 11 as image data.

  The document is set on the tray 202 of the document feeder 201. When the user instructs to start reading from the operation unit 12, a document reading instruction is given from the controller 11 to the scanner unit 13. Upon receiving this instruction, the scanner unit 13 feeds the documents one by one from the tray 202 of the document feeder 201 and performs a document reading operation. Note that the document reading method is not an automatic feeding method by the document feeder 201, but a method of scanning the document by placing the document on a glass surface (not shown) and moving the exposure unit.

  The printer unit 14 is an image forming device that forms image data received from the controller 11 on a sheet. In this embodiment, the image forming method is an electrophotographic method using a photosensitive drum or a photosensitive belt, but an ink jet method in which ink is ejected from a minute nozzle array and printed on a sheet may be used. . The printer unit 14 is provided with a plurality of paper cassettes 203, 204, and 205 that allow selection of different paper sizes or different paper orientations. The paper after printing is discharged to the paper discharge tray 206.

<Detailed Description of Controller 11 (FIG. 3)>
FIG. 3 is a block diagram for explaining the configuration of the controller 11 of the image forming apparatus 10 in more detail.

  The controller 11 is electrically connected to the scanner unit 13 and the printer unit 14. On the other hand, the controller 11 is connected to the PC 40 or an external device via the LAN 50 or the WAN 331. As a result, input / output of image data and device information is possible.

  The CPU 301 comprehensively controls access to various connected devices based on a control program stored in the ROM 303, and also performs overall control of various processes performed in the controller. A RAM 302 is a system work memory for the CPU 301 to operate, and temporarily stores image data. The RAM 302 includes an SRAM that retains stored content even after the power is turned off, and a DRAM that erases the stored content after the power is turned off. The ROM 303 stores a boot program for the apparatus. An HDD 304 is a hard disk drive, and can store system software and image data.

  The operation unit I / F 305 is an interface unit for connecting the system bus 310 and the operation unit 12. The operation unit I / F 305 receives image data to be displayed on the operation unit 12 from the system bus 310 to the operation unit 12 and outputs information input from the operation unit 12 to the system bus 310.

  A network I / F 306 is connected to the LAN 50 and the system bus 310 to input / output information. The Modem 307 is connected to the WAN 331 and the system bus 310, and inputs and outputs information. A binary image rotation unit 308 converts the direction of image data before transmission. The binary image compression / decompression unit 309 converts the resolution of the image data before transmission into a resolution that matches a predetermined resolution or the partner's ability. For compression and decompression, methods such as JBIG, MMR, MR, and MH are used. The image bus 330 is a transmission path for exchanging image data, and is configured by a PCI bus or IEEE1394.

  The scanner image processing unit 312 corrects, processes, and edits image data received from the scanner unit 13 via the scanner I / F 311. The scanner image processing unit 312 determines whether the received image data is a color document or a monochrome document, a character document, or a photographic document. Then, the determination result is attached to the image data. Such accompanying information is referred to as attribute data. Details of processing performed by the scanner image processing unit 312 will be described later.

  The compression unit 313 receives the image data and divides the image data into blocks of 32 pixels × 32 pixels. The 32 × 32 pixel image data is referred to as tile data. FIG. 4 conceptually shows this tile data. In a document (paper medium before reading), an area corresponding to the tile data is referred to as a tile image. The tile data is added with the average luminance information in the 32 × 32 pixel block and the coordinate position of the tile image on the document as header information. Further, the compression unit 313 compresses image data including a plurality of tile data. The decompression unit 316 decompresses image data composed of a plurality of tile data, raster-expands it, and sends it to the printer image processing unit 315.

  The printer image processing unit 315 receives the image data sent from the decompression unit 316 and performs image processing on the image data while referring to attribute data attached to the image data. The image data after the image processing is output to the printer unit 14 via the printer I / F 314. Details of processing performed by the printer image processing unit 315 will be described later.

  The image conversion unit 317 performs a predetermined conversion process on the image data. The image conversion unit 317 includes a processing unit as described below.

  A decompression unit 318 decompresses received image data. A compression unit 319 compresses the received image data. A rotation unit 320 rotates received image data. The scaling unit 321 performs resolution conversion processing (for example, 600 dpi to 200 dpi) on the received image data. The color space conversion unit 322 converts the color space of the received image data. The color space conversion unit 322 performs a known background removal process using a matrix or a table, performs a known LOG conversion process (RGB → CMY), or performs a known output color correction process (CMY → CMYK). can do. The binary multi-value conversion unit 323 converts the received two-gradation image data into 256-gradation image data. Conversely, the multi-level binary conversion unit 324 converts the received 256-gradation image data into 2-gradation image data using a technique such as error diffusion processing.

  The synthesizer 327 synthesizes the received two pieces of image data to generate one piece of image data. When combining two pieces of image data, a method of using an average value of luminance values of pixels to be combined as a combined luminance value, or a luminance value of a pixel having a brighter luminance level, A method for obtaining a luminance value is applied. In addition, it is possible to use a method in which the darker pixel is used as a synthesized pixel. Furthermore, a method of determining a luminance value after synthesis by a logical sum operation, a logical product operation, an exclusive logical sum operation, or the like between pixels to be synthesized is also applicable. These synthesis methods are all well-known methods. The thinning unit 326 performs resolution conversion by thinning out the pixels of the received image data, and generates image data such as 1/2, 1/4, and 1/8. The moving unit 325 adds a margin part to the received image data or deletes the margin part.

  The RIP 328 receives intermediate data generated based on PDL code data transmitted from the PC 40 or the like, and generates bitmap data (multi-value).

<Detailed Description of Scanner Image Processing Unit 312 (FIG. 5)>
FIG. 5 shows an internal configuration of the scanner image processing unit 312.

  The scanner image processing unit 312 receives image data composed of RGB 8-bit luminance signals.

  The shading correction unit 500 performs shading correction on the luminance signal. As described above, the shading correction is a process for preventing the brightness of the document from being erroneously recognized due to variations in CCD sensitivity. Further, as described above, the shading correction unit 500 performs gain adjustment according to an instruction from the CPU 301.

  Subsequently, the luminance signal is converted into a standard luminance signal that does not depend on the CCD filter color by the masking processing unit 501.

  The filter processing unit 502 arbitrarily corrects the spatial frequency of the received image data. The filter processing unit 502 performs arithmetic processing using, for example, a 7 × 7 matrix on the received image data. By the way, in a copier or a multi-function peripheral, a character mode, a photo mode, or a character / photo mode can be selected as a copy mode by pressing down a tab 1404 (shown in FIG. 14) described later. When the character mode is selected by the user, the filter processing unit 502 applies a character filter to the entire image data. When the photo mode is selected, a photo filter is applied to the entire image data. When the character / photo mode is selected, the filter is adaptively switched for each pixel in accordance with a character photo determination signal (part of attribute data) described later. That is, it is determined for each pixel whether to apply a photo filter or a character filter. Note that coefficients for smoothing only high-frequency components are set in the photographic filter. This is because the roughness of the image is not noticeable. In addition, a coefficient for performing strong edge enhancement is set in the character filter. This is to increase the sharpness of the characters.

  The histogram generation unit 503 samples the luminance data of each pixel constituting the received image data. More specifically, luminance data in a rectangular area surrounded by a start point and an end point specified in the main scanning direction and the sub scanning direction are sampled at a constant pitch in the main scanning direction and the sub scanning direction. Then, histogram data is generated based on the sampling result. The generated histogram data is used to estimate the background level when performing background removal processing. The input-side gamma correction unit 504 converts luminance data having nonlinear characteristics using a table or the like.

  A color / monochrome determination unit 505 determines whether each pixel constituting the received image data is a chromatic color or an achromatic color, and the determination result is converted into image data as a color / monochrome determination signal (part of attribute data). Accompany it.

  The character photograph determination unit 506 determines whether each pixel constituting the image data is a pixel constituting a character, a pixel constituting a halftone dot, a pixel constituting a character in a halftone dot, or a pixel constituting a solid image Is determined based on the pixel value of each pixel and the pixel values of peripheral pixels of each pixel. Note that pixels that do not correspond to any of these are pixels that form a white region. Then, the determination result is attached to the image data as a character / photo determination signal (part of the attribute data).

  The paper fingerprint information acquisition unit 507 acquires image data of a blank area of a predetermined size from the RGB image data input from the shading correction unit 500 based on the determination result by the character photo determination unit 506. Since the blank area is an area on which no recording material such as toner is placed, the fiber information of the paper can be extracted with high accuracy, and is suitable as an extraction area for paper fingerprint information. A low density portion of a gray scale image described later is also suitable as an extraction area for paper fingerprint information because the amount of recording material such as toner is small. Therefore, a low-density portion may be used as a paper fingerprint extraction region by preparing a threshold value for determining a low-density portion for a gray scale image to be described later and determining the density.

  FIG. 6 is a flowchart showing a paper fingerprint information acquisition process performed by the paper fingerprint information acquisition unit 507 for the blank area or the low density area (paper fingerprint information acquisition area).

  In step 601, the image data extracted by the paper fingerprint information acquisition unit 507 is converted into grayscale image data. In step 602, a message is displayed to change the orientation of the paper (original) and perform the second paper pattern collection, and prompt the user to rotate the paper by +180 (or +90, +270) degrees and set it again. FIG. 7 shows an example of a dialog 700 to be displayed.

  When the user presses the rescan execution button 701 in FIG. 7, the scan is executed again in step S603 to acquire image data corresponding to the same blank area on the paper, and in step 604, it is converted to grayscale image data. The generated image is rotated by 180 (or -90, -270) degrees by performing a known rotation process using a memory (not shown) in the scanner image processing unit 312, and matches the image generated in step 601. It is supposed to be oriented.

  In step 605, the grayscale image generated in steps 601 and 604 is compared for each pixel to generate a binary noise mask image. That is, each pixel of two grayscale images is compared. If the difference is less than or equal to a predetermined threshold value, the pixel is determined to be valid and “1” is set in the noise mask image. It is determined that noise is present, and “0” is set in the noise mask image.

  Next, in step 606, the grayscale image data generated in step 601 and the noise mask image data generated in step 605 are stored as paper pattern information.

  The paper fingerprint information acquisition unit 507 sends the above paper fingerprint information as original data to the RAM 302 through a data bus (not shown) and stores it. This original data can be sent and registered in the memory of the external device and / or the external database 100 through the Network I / F 306.

  When there is code image data in the image data output from the masking processing unit 501, the decoding unit 508 detects the presence thereof. Then, the detected code image data is decoded to extract information.

  In the processing described above, noise due to dirt, scratches, dust, etc. on the scanner manuscript table is placed on the paper pattern extracted in the first and second scans. Since the first and second scans have different paper orientations, the scanner platen area corresponding to the fingerprint collection target area is also different. Therefore, if there is noise due to dirt, scratches, dust, etc. on the platen, noise may or may not occur at the same position on the paper pattern extracted during the first and second scans. To do. Therefore, the noise mask image data is generated by comparing the two paper pattern patterns collected for the same area of the paper (original) to create the noise mask image data. It was made not to become.

<Detailed Description of Printer Image Processing Unit 315 (FIG. 8)>
FIG. 8 is a block diagram of the printer image processing unit 315, and processing performed in the image processing unit 315 will be described with reference to FIG.

  The background removal processing unit 801 uses the histogram generated by the scanner image processing unit 312 to remove (remove) the background color of the image data. The monochrome generation unit 802 converts color data into monochrome data. The Log conversion unit 803 performs luminance density conversion. For example, the log conversion unit 803 converts RGB input image data into CMY image data. The output color correction unit 804 performs output color correction. For example, image data input as CMY is converted into CMYK image data using a table or matrix. The output-side gamma correction unit 805 performs correction so that the signal value input to the output-side gamma correction unit 805 is proportional to the reflection density value after copy output. The code image synthesis unit 807 synthesizes the (original) image data corrected by the output-side gamma correction unit 805 and the code image data generated by <paper fingerprint information encoding processing> described later. A halftone correction unit 806 performs halftone processing according to the number of gradations of the printer unit to be output. For example, the received high gradation image data is binarized or binarized.

  Each processing unit in the scanner image processing unit 312 or the printer image processing unit 315 can output the received image data without performing each processing. In the following, passing data without processing in a certain processing unit is expressed as “through the processing unit”.

<Paper fingerprint information encoding process>
The CPU 301 reads paper fingerprint information (original data) in a predetermined area stored in the RAM 302 or receives it from an external device or the like through an interface, and controls the paper fingerprint information to be encoded to generate code image data. be able to.

  In the present specification, a code image indicates an image such as a two-dimensional code image or a barcode image.

  Further, the CPU 301 can control to transmit the generated code image data to the code image synthesis unit 807 in the printer image processing unit 315 via a data bus (not shown).

  The above control (code image generation control and transmission control) is performed by executing a program loaded in the RAM 302. This program can be read from an external storage medium and loaded into the RAM 302 or loaded from the network through the network I / F 306.

<Paper fingerprint information matching process>
The CPU 301 can read out the paper fingerprint information of a predetermined area obtained by scanning the paper from the RAM 302, and can control to collate the paper fingerprint information with other paper fingerprint information received through the Network I / F 306. . The other paper fingerprint information means paper fingerprint information included in the code image data or paper fingerprint information registered as an original in an external device, a database, or the like.

  FIG. 9 is a flowchart showing the paper fingerprint information matching process. Each step of this flowchart is centrally controlled by the CPU 301.

  In step 901, registered paper fingerprint information, which is the other paper fingerprint information, is obtained from the RAM 302, an external device, a database, or the like.

  In step 902, the paper fingerprint information of a predetermined area obtained by scanning the paper by the processing in steps 1601 and 1602 (FIG. 16) described later is collated with the already registered paper fingerprint information as an original image. That is, in order to collate the registered paper fingerprint information, which is other paper fingerprint information acquired in step 901, with the paper fingerprint information of the predetermined area, the degree of matching between the two paper fingerprint information is calculated using equation (1). To do. If two pieces of paper fingerprint information are on the same paper, it is assumed that one piece of paper fingerprint information is obtained by shifting the other piece of paper fingerprint information, and an error image of the two pieces of paper fingerprint information is obtained. That is, in the function shown in Expression (1), the position is shifted for each pixel, and the value obtained by the function of Expression (1) is minimized (where the difference between the two pieces of paper fingerprint information is minimized). An error image (E) of fingerprint information is obtained according to the following equation.

In equation (1), α ₁ is mask data in the registered paper fingerprint information extracted in step 901. f ₁ is grayscale image data in the already registered paper fingerprint information extracted in step 901. α ₂ is mask data in the paper fingerprint information (obtained this time) sent from the paper fingerprint information acquisition unit 507 in step 902. f ₂ is a gray-scale image data sent from the paper fingerprint information acquisition unit 507 in (obtained this time) paper fingerprint information in step 902.

  A specific method will be described with reference to FIGS. FIG. 10 shows an image diagram of the registered paper fingerprint information and the paper fingerprint information obtained this time. Assume that each pixel is composed of horizontal n pixels and vertical m pixels.

  In the function shown in Expression (1), i and j are shifted by 1 pixel in the range of −n + 1 to n−1 and −m + 1 to m−1, respectively, and the registered paper fingerprint information and the paper fingerprint obtained this time (2n−1) × (2m−1) error values E (i, j) of information are obtained. That is, E (−n + 1, −m + 1) to E (n−1, m−1) are obtained.

  FIG. 11A shows an image diagram in which the upper left pixel of the registered paper fingerprint information is overlapped by the lower right pixel of the paper fingerprint information obtained this time. In this state, the value obtained by the function of Expression (1) is E (−n + 1, −m + 1). FIG. 11B shows an image obtained by moving the paper fingerprint information obtained this time to the right by one pixel as compared with FIG. In this state, a value obtained by the function of Expression (1) is E (−n + 2, −m + 1). Similarly, calculation is performed while moving the paper fingerprint information obtained this time. In FIG. 11C, the paper fingerprint information obtained this time is moved to a position where it overlaps with the registered paper fingerprint information, and E (0,-(m-1)) is obtained. Further, in FIG. 11D, the paper fingerprint information obtained this time is moved to the right end to obtain E (n−1, −m + 1). Thus, when shifted in the horizontal direction, i of E (i, j) is added one by one.

  Similarly, in FIG. 12A, the paper fingerprint information obtained this time by one pixel is moved downward in the vertical direction as compared with FIG. 11A, and the value of E (−n + 1, −m + 2) is obtained. .

  Further, in FIG. 12B, the value of E (n−1, −m + 2) is obtained by moving the paper fingerprint information obtained this time to the right end with respect to FIG.

  FIG. 13A shows a case where the registered paper fingerprint information and the paper fingerprint information obtained this time are at the same position, and the value of E (i, j) at this time is E (0,0).

  Similarly, the calculation is performed while shifting the images so that each paper fingerprint information overlaps at least one pixel. Finally, E (n-1, m-1) is obtained as shown in FIG.

  In this way, a set of (2n−1) × (2m−1) error values E (i, j) is obtained.

Here, in order to consider the meaning of Equation (1), i = 0, j = 0, and α ₁ (x, y) = 1 (where x = 0 to n, y = 0 to m). And α ₂ (x−i, y−j) = 1 (where x = 0 to n and y = 0 to m). That is, α ₁ (x, y) = 1 (where x = 0 to n, y = 0 to m), and α ₂ (xi, y−j) = 1 (where x = 0). E (0,0) in the case of .about.n, y = 0 to m).

  Note that i = 0 and j = 0 indicate that the registered paper fingerprint information and the paper fingerprint information obtained this time are at the same position as shown in FIG.

Here, α ₁ (x, y) = 1 (where x = 0 to n, y = 0 to m) indicates that all pixels of the registered paper fingerprint information are bright. In other words, when the registered paper fingerprint information is acquired, it indicates that no color material such as toner or ink or dust is placed on the paper fingerprint acquisition area.

Further, α ₂ (x−i, y−j) = 1 (where x = 0 to n, y = 0 to m) indicates that all pixels of the paper fingerprint information obtained this time are bright. In other words, when the paper fingerprint information obtained this time is acquired, it indicates that no color material such as toner or ink or dust was placed on the paper fingerprint acquisition area.

As described above, when α ₁ (x, y) = 1 and α ₂ (x−i, y−j) = 1 hold in all pixels, the equation (1) is expressed by the following equation.

{F ₁ (x, y) −f ₂ (x, y)} ² in Equation (1) ′ is the gray scale image data in the registered paper fingerprint information and the gray scale in the paper fingerprint information obtained this time. The square value of the difference from the image data is shown. Therefore, equation (1) ′ represents the sum of the squares of the differences in each pixel between the two pieces of paper fingerprint information. That is, E (0, 0) takes a smaller value as the number of pixels in which f ₁ (x, y) and f ₂ (x, y) are similar is larger.

What has been described above is how to obtain E (0,0), but other E (i, j) is obtained in the same manner. Incidentally, E (i, j) takes a smaller value as the number of pixels in which f ₁ (x, y) and f ₂ (x, y) are similar is larger. Therefore, when E (k, l) = min {E (i, j)}, the position when the registered paper fingerprint information is acquired and the position when the paper fingerprint information obtained this time are acquired are , It can be seen that they are shifted from each other by k and l.

<Significance of α>
The numerator of formula (1) means the result of multiplying {f ₁ (x, y) -f ₂ (xi, yj)} ² by α ₁ and α ₂ (exactly Is further calculated by sigma calculation). α ₁ and α ₂ indicate 0 for a dark pixel and 1 for a light pixel.

Accordingly, when one (or both) of α ₁ and α ₂ is 0, α ₁ α ₂ {f ₁ (x, y) −f ₂ (xi, y−j)} ² Will be 0.

  That is, when one or both (or both) of the paper fingerprint information has a dark pixel, the density difference between the pixels is not considered. This is for ignoring pixels on which dust or color material has been placed.

Since the total number increases or decreases due to the sigma calculation by this processing, normalization is performed by dividing by the total number Σα ₁ (x, y) α ₂ (x−i, y−j). Note that an error value E (i, j) in which Σα ₁ (x, y) α ₂ (x−i, y−j) in the denominator of Expression (1) becomes 0 is a set of error values (E (-(N-1),-(m-1)) to E (n-1, m-1)) are not included.

<Determination method of matching degree>
As described above, when E (k, l) = min {E (i, j)}, the position when the registered paper fingerprint information is acquired and the paper fingerprint information obtained this time are acquired. It can be seen that the positions are shifted from each other by k and l.

  Subsequently, a value indicating how much the two pieces of paper fingerprint information are similar (this value is referred to as a matching degree) is obtained using the E (k, l) and other E (i, j). .

First, a set of error values (for example, E (0,0) = 10 *, E (0,1) = 50, E (1,0) = 50, E (1,1) = The average value (40) is obtained from 50). ... (A)
Note that * is not related to the value and is given because it needs attention. The reason why attention is required will be described later.

Next, each error value (10 *, 50, 50, 50) is subtracted from the average value (40) to obtain a new set (30 *, −10, −10, −10). .... (B)
Then, a standard deviation (30 × 30 + 10 × 10 + 10 × 10 + 10 × 10 = 1200, 1200/4 = 300, √300 = 10√3 = about 17) is obtained from this new set. Then, the new set is divided by 17 to obtain a quotient (1 *, -1, -1, -1). .... (C)
And let the maximum value of the calculated | required values be a matching degree (1 *). The value 1 * corresponds to the value E (0,0) = 10 *. In this case, E (0,0) is a value that satisfies E (0,0) = min {E (i, j)}.

<Conceptual explanation of how to determine the degree of matching>
The process of performing the matching degree determination method eventually calculates how far the smallest error value in the plurality of error value sets is from the average error value (A and B).

  Then, the degree of matching is obtained by dividing the degree of separation by the standard deviation (C).

  Finally, a matching result is obtained by comparing the matching degree with a threshold (D).

  The standard deviation means an average value of “difference between each error value and the average value”. In other words, the standard deviation value indicates how much variation is generally occurring in the set.

  By dividing the above degree of separation by such an overall variation value, how small is min {E (i, j)} in the set E (i, j) (projectingly small or slightly small) ) Will be understood.

  Then, it is determined to be valid when min {E (i, j)} is very prominent and small in the set E (i, j), and is invalid otherwise (D).

<Reason why min {E (i, j)} is determined to be effective only when it is very small in the set E (i, j)>
Here, it is assumed that the registered paper fingerprint information is obtained from the same paper as that obtained this time.

  Then, there should be a place (deviation position) where the registered paper fingerprint information and the paper fingerprint information obtained this time coincide very well. At this time, E (i, j) should be very small because the registered paper fingerprint information and the paper fingerprint information obtained this time agree very well at this misalignment position.

  On the other hand, if the position is slightly shifted from this position, there is no relationship between the registered paper fingerprint information and the paper fingerprint information obtained this time. Therefore, E (i, j) should be a normal large value.

  Therefore, the condition that “two pieces of paper fingerprint information are acquired from the same paper” matches the condition that “the smallest E (i, j) protrudes and is small in the set E (i, j)”.

Returning to <paper fingerprint information collating process> in FIG.
In step 903, the matching degree of the two pieces of paper fingerprint information obtained in step 902 is compared with a predetermined threshold value to determine “valid” or “invalid”. Note that the degree of matching may be referred to as similarity. A comparison result between the matching degree and a predetermined threshold value may be referred to as a matching result.
The description of the controller 11 has been described above.

<Explanation of operation screen>
FIG. 14 is an initial screen in the image forming apparatus 10.
An area 1401 indicates whether or not the image forming apparatus 10 is ready for copying, and indicates the set number of copies. An original selection tab 1404 is a tab for selecting the type of original to be copied. When the tab 1404 is pressed down, three types of selection menus of text, photo, and text / photo mode are displayed in a pop-up. A finishing tab 1406 is a tab for performing settings related to various finishings. A duplex setting tab 1407 is a tab for performing settings relating to duplex reading and duplex printing. A reading mode tab 1402 is a tab for selecting an original reading mode. When the tab 1402 is depressed, three types of selection menus of color / black / automatic (ACS) are popped up. Note that color copy is performed when color is selected, and monochrome copy is performed when black is selected. When ACS is selected, the copy mode is determined by the monochrome color determination signal described above.

  An area 1408 is a tab for selecting a paper fingerprint information registration process. An area 1409 is a tab for selecting a paper fingerprint information matching process. A paper fingerprint information (original data) registration process executed when the area 1408 is pressed and a paper fingerprint information matching process executed when the area 1409 is pressed will be described below.

<Operation when the tab for paper fingerprint information registration processing is pressed>
Next, a paper fingerprint information registration process (original registration) executed when the user presses the paper fingerprint information registration tab 1408 shown in FIG. 14 and then presses the start key will be described with reference to FIG. .

  In step 1501, the document read by the scanner unit 13 is sent as image data to the scanner image processing unit 312 via the scanner I / F 311 under the control of the CPU 301.

  In step 1502, the scanner image processing unit 312 sets a general gain adjustment value in the shading correction unit 500, and then performs the processing shown in FIG. 5 on the image data, and sets the attribute data together with the new image data. Generate. Further, this attribute data is attached to the image data. Further, the scanner image processing unit 312 sets a gain adjustment value smaller than the general gain adjustment value in the shading correction unit 500. Then, each luminance signal value obtained by applying the small gain adjustment value to the image data is output to the paper fingerprint information acquisition unit 507 to generate a grayscale image.

  In step 1503, the original is read again. At this time, the document is rotated 180 degrees and set, and the document is scanned in a different direction. In step 1504, a grayscale image is generated, and the image is simultaneously rotated by 180 degrees to match the orientation of the image with that obtained in step 1502. In step 1505, the two grayscale images are compared to generate a noise mask image. Finally, in step 1506, the grayscale image data generated in step 1502 and the noise mask image data generated in step 1505 are registered in the external database as paper fingerprint information.

  The paper fingerprint information may be stored in the RAM 302 as data obtained by deleting the noise mask image data from the grayscale image data. In this case, noise on the document table is removed from the first image data obtained by scanning the paper on the document table and the second image data obtained by scanning at different positions on the document table. The fiber information (paper fingerprint information) from which this noise has been excluded is registered in the RAM 302. This noise removal can be realized by taking the AND of the first image data and the second image data at the same position on the image to remove information contained only in one of the image data.

<Operation when paper fingerprint information matching tab is pressed>
Next, an operation when the start key is pressed after the user presses the paper fingerprint information verification tab 609 shown in FIG. 14 (paper scanning and verification with the original) will be described with reference to FIG.

  In step 1601, the document read by the scanner unit 13 is sent as image data to the scanner image processing unit 312 via the scanner I / F 311 under the control of the CPU 301.

  In step 1602, the scanner image processing unit 312 performs the processing shown in FIG. 5 on the image data, and generates attribute data together with new image data. Further, this attribute data is attached to the image data.

  Further, in step 1602, the paper fingerprint information acquisition unit 507 in the scanner image processing unit 312 acquires paper fingerprint information (the configuration such as the gain adjustment of the shading correction unit 500 is performed in order to acquire the paper fingerprint information). As described above). Then, the paper fingerprint information acquired this time is sent to the RAM 302 through a data bus (not shown).

  In step 1602, when there is a code image, the decoding unit 508 in the scanner image processing unit 312 decodes the code image to obtain information. Then, the paper fingerprint information acquired this time is sent to the RAM 302 through a data bus (not shown).

  In step 1603, the paper fingerprint information acquired this time in step 1602 and the already registered paper fingerprint information registered in step 1506 by the control calculation of the CPU 301 are described with reference to FIG. The paper fingerprint information matching process is performed. Here, the image of the predetermined area acquired this time in steps 1601 and 1602 is collated with the original already registered by <paper fingerprint information registration processing> as described in detail above, and the originality of the paper scanned this time is confirmed. It is verified and the originality can be guaranteed.

  In step 1604, the verification result (valid or invalid) obtained by the <paper fingerprint information matching process> can be displayed on the display screen of the operation unit 12 under the control of the CPU 301.

  In the above embodiment, an example has been described in which a document (original) is rotated +90, +180, and +270 degrees on the original platen to scan the original. However, it is needless to say that document replacement other than the above-described rotation processing may be used as long as the configuration in which paper (document) is arranged at a position where the document cost is different and scanning is applied.

(Other examples)
Further, the present invention can be applied to a system constituted by a plurality of devices (for example, a computer, an interface device, a reader, a printer, etc.), and can also be applied to an apparatus (multifunction device, printer, facsimile machine, etc.) comprising a single device. It is also possible.

  Another object of the present invention is that a computer (or CPU or MPU) of a system or apparatus reads and executes the program code from a storage medium that stores the program code for realizing the procedure of the flowchart shown in the above-described embodiment. Is also achieved. In this case, the program code itself read from the storage medium realizes the functions of the above-described embodiment. Therefore, the program code and a storage medium storing the program code also constitute one of the present invention.

  As a storage medium for supplying the program code, for example, a floppy (registered trademark) disk, hard disk, optical disk, magneto-optical disk, CD-ROM, CD-R, magnetic tape, nonvolatile memory card, ROM, or the like is used. be able to.

  Further, by executing the program code read by the computer, not only the functions of the above-described embodiments are realized, but also an OS (operating system) operating on the computer based on the instruction of the program code is actually used. A case where part or all of the processing is performed and the functions of the above-described embodiments are realized by the processing is also included.

  Further, after the program code read from the storage medium is written in a memory provided in a function expansion board inserted into the computer or a function expansion unit connected to the computer, the function expansion board is based on the instruction of the program code. The CPU of the function expansion unit or the like performs part or all of the actual processing, and the functions of the above-described embodiments are realized by the processing.

1 is a block diagram illustrating an overall configuration of an image forming apparatus according to the present invention. 1 is an external view of an input / output device of an image forming apparatus used in the present invention. 1 is a block diagram illustrating an overall configuration of an image forming apparatus used in the present invention. It is explanatory drawing which shows tile data notionally. 2 is a block diagram of a scanner image processing unit provided in the image forming apparatus used in the present invention. FIG. It is a flowchart which shows the paper fingerprint information acquisition process in this invention. It is a figure which shows the dialog for rescan execution in the paper fingerprint information acquisition process in this invention. 2 is a block diagram of a printer image processing unit provided in the image forming apparatus used in the present invention. FIG. It is a flowchart which shows the paper fingerprint information collation process in this invention. It is a figure which shows the paper fingerprint information registered by this invention, and the paper fingerprint information obtained this time. It is explanatory drawing explaining the collation process with the original in this invention. It is explanatory drawing explaining the collation process with the original in this invention. It is explanatory drawing explaining the collation process with the original in this invention. It is explanatory drawing of the copy screen of an operation part. It is a flowchart which shows the paper fingerprint information registration process in this invention. It is a flowchart which shows the paper fingerprint information collation process in this invention.

Explanation of symbols

10, 20, 30 Image forming apparatus 11, 21, 31 Controller (Controller Unit)
12, 22, 32 Operation unit (user interface)
13, 23 Scanner unit 40 Host computer (PC)
100 Database 301 CPU in controller 11
302 RAM
306 Network I / F
312 Scanner Image Processing Unit 501 Masking Processing Unit 506 Character Photo Determination Unit 507 Paper Fingerprint Information Acquisition Unit 701 Rescan Execution Button 1404 Document Selection Tabs 1408 and 1409 Areas (tabs for selecting paper fingerprint information registration processing and paper fingerprint information collation processing)

Claims (10)

In an image processing apparatus that performs image processing for guaranteeing the originality of the paper based on the characteristics of the fibers constituting the paper included in the scanned image of the paper,
Means for acquiring first image data of an image obtained by scanning a sheet by an image scanning means;
Means for acquiring second image data of an image obtained by scanning the paper in a different direction by the image scanning means;
Means for creating mask data based on the first and second image data for masking noise generated by the image scanning means and included in the first and second image data; and
An image processing apparatus comprising registration means for registering the mask data and registering an image obtained by scanning as an original. The first and second image data is data obtained from a scanned image of a paper fingerprint information acquisition area of the paper,
The image processing apparatus according to claim 1, wherein the mask data masks noise generated in a portion corresponding to the paper fingerprint information acquisition region of the image scanning unit. In an image processing apparatus that performs image processing for examining the originality of the paper based on the characteristics of the fibers constituting the paper included in the scanned image of the paper,
Means for acquiring image data of an image obtained by scanning a sheet by an image scanning means;
Means for acquiring mask data and original images registered in a registration means provided in the image processing apparatus according to claim 1; and
A means for excluding noise generated by the image scanning means provided in the image processing apparatus according to claim 1 or 2 from the target by using the acquired mask data, and collating the scanned image of the paper with the original image. An image processing apparatus comprising the image processing apparatus. In an image processing method for performing image processing for guaranteeing the originality of the paper based on the characteristics of the fibers constituting the paper included in the scanned image of the paper,
Obtaining first image data of an image obtained by scanning a sheet with an image scanning unit;
Obtaining second image data of an image obtained by scanning the paper in a different direction by the image scanning unit;
Creating mask data based on the first and second image data to mask noise generated by the image scanning means and included in the first and second image data; and
An image processing method comprising a registration step of registering the mask data and registering an image obtained by the scan as an original. The first and second image data is data obtained from a scanned image of a paper fingerprint information acquisition area of the paper,
5. The method according to claim 4, wherein the mask data masks noise generated at a portion corresponding to the paper fingerprint information acquisition region of the image scanning unit. In the image processing method for performing image processing for examining the originality of the paper based on the characteristics of the fibers constituting the paper included in the scanned image of the paper,
Acquiring image data of an image obtained by scanning a sheet with an image scanning unit, and mask data and an original image registered by the image processing method according to claim 4 or 5, and
6. The step of collating the scanned image of the paper with the original image by excluding the noise generated by the image scanning means from the target by executing the image processing method of claim 4 or 5 by using the acquired mask data An image processing method comprising: An image processing method program for performing image processing for guaranteeing the originality of the paper based on the characteristics of the fibers constituting the paper included in the scanned image of the paper, the processing device comprising:
Means for acquiring first image data of an image obtained by scanning a sheet by an image scanning means;
Means for acquiring second image data of an image obtained by scanning the paper in a different direction by the image scanning means;
Means for creating mask data based on the first and second image data for masking noise generated by the image scanning means and included in the first and second image data; and
A program which functions as a registration means for registering the mask data and registering an image obtained by scanning as an original. An image processing method program for performing image processing for examining the originality of a paper based on the characteristics of fibers constituting the paper included in a scanned image of the paper, the processing device comprising:
Means for obtaining image data of an image obtained by scanning a sheet by an image scanning means, and mask data and an original image registered by the program of the image processing method of claim 7, and
The means for collating the scanned image of the paper with the original image by excluding noise generated by the image scanning means by executing the program of the image processing method according to claim 7 by using the acquired mask data A program characterized by functioning as   A storage medium storing the program according to claim 7 and / or 8. An image processing apparatus that performs image processing for guaranteeing the originality of the paper based on the characteristics of the fibers constituting the paper,
Means for acquiring first image data obtained by scanning paper on a document table by image scanning means;
Means for acquiring second image data obtained by scanning the paper at different positions on the document table by the image scanning means; and
Means for removing noise on the platen of the image scanning means based on the first and second image data;
An image processing apparatus comprising registration means for registering information on the fiber based on the image data removed by the removing means.

Images