JP2008269582A - Image processing apparatus, image forming apparatus, image transmitter, image reader, image processing system, image processing method, image processing program and the recording medium - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To prevent erroneous determination which prohibits the execution of image processing based on input image data to be originally allowed to or to prevent the erroneous determination which executes image processing based on input image data to be originally prohibited or restricted. <P>SOLUTION: A registration process section 35 stores, into an exceptional registration image list 103, discrimination information for discriminating a registration image which permits image processing and a registration image which prohibits or restricts image processing. In the case that a maximum value of similarity calculated by a voting process section 33 is not smaller than a threshold, a control section 7 determines whether a registration image having maximum similarity is the registration image which permits image processing or a registration image which prohibits or restricts image processing and determines whether or not it is necessary to prohibit or restrict image processing with respect to input image data according to a result of the determination. <P>COPYRIGHT: (C)2009,JPO&INPIT

Description

  The present invention relates to an image processing apparatus, an image forming apparatus, an image transmitting apparatus, an image reading apparatus, and an image processing system that determine the degree of similarity between input image data and registered image data registered in advance and perform control according to the determination result. The present invention relates to an image processing method, an image processing program, and a recording medium thereof.

  Conventionally, input image data obtained by reading a document image with a scanner is compared with a registered image registered in advance to determine the similarity between the two, and processing on the input image data based on the determination result (for example, Technology for controlling copying, transmission, editing, etc. is used.

  As a method for determining the similarity, for example, a keyword is extracted from an image using an OCR (Optical Character Reader) or the like and matching is performed based on the keyword, or the target image is limited to a form image having a ruled line, and matching is performed based on the characteristic of the ruled line. And the like (see Patent Document 1), the determination method based on the input image data and the color distribution of the registered image (see Patent Document 2), and the like. Patent Document 3 generates a descriptor that is selected so as to be invariant to distortion caused by digitization of the document from the characteristics of the input document and a difference between the input document and a matching document in the document database, A technique for matching an input document with a document in the document database by using this descriptor and a descriptor database that indicates a list of documents including a feature in which the descriptor is extracted and the descriptor is extracted is disclosed. In this technique, when the descriptor database is scanned, the voting results for each document in the document database are totaled, and a document having the maximum number of votes or a document whose number of votes exceeds a certain threshold value is regarded as a consistent document. ing.

  In Patent Document 4, a plurality of feature points are extracted from a digital image, a set of local feature points is determined for each extracted feature point, and a subset of feature points is selected from each determined set Then, as an amount to characterize each selected subset, invariants for geometric transformation are obtained based on a plurality of combinations of feature points in the subset, and feature amounts are calculated by combining the obtained invariants. A technique for searching for a document / image corresponding to the digital image by voting on a document / image in a database based on the calculated feature amount is disclosed.

Further, as a technique for controlling processing on input image data in accordance with the similarity determination result, for example, input based on a pattern detected from input image data in order to deal with counterfeit bills and securities by a color image forming apparatus. It is determined whether the image data is image data of banknotes, securities, etc. (registered images). If the image data is image data of registered images, the image forming apparatus that made the copy can be identified from the output image. There are known techniques for adding a specific pattern to an image to be output to the printer, painting a copy image, or prohibiting a copy operation.
JP-A-8-255236 (released on October 1, 1996) JP 5-110815 A (published April 30, 1993) Japanese Patent Laid-Open No. 7-282088 (released on October 27, 1995) International Publication No. 2006/092957 pamphlet (published on September 8, 2006)

  By the way, in an image processing apparatus that determines whether or not input image data is image data of a registered image, an erroneous determination may occur depending on conditions at the time of reading due to limitations on image reading accuracy and the like.

  For this reason, in the above-described conventional technology, when it is determined that the input image data is image data of a registered image, a specific pattern is added, or a copy image is filled to restrict processing contents, A process for prohibiting the copying operation is performed. For this reason, it is impossible to execute a process desired by the user on the input image data erroneously determined to be the image data of the registered image although it is not originally the image data of the registered image.

  Contrary to the conventional techniques described above, when it is determined that the image data is a registered image, image processing (for example, copying, printing, electronic distribution, facsimile transmission, filing, image data correction / editing, etc.) is performed. A configuration is possible in which execution is permitted and image processing execution is prohibited or restricted when it is determined that the image data is not registered image data. In this configuration, however, the input image data is erroneously determined to be registered image image data. In such a case, the execution of the image processing is permitted although the execution of the image processing should originally be prohibited or restricted. Therefore, there may be a security problem such as leakage of confidential information.

  The present invention has been made in view of the above problems, and an object of the present invention is to determine the similarity (similarity / not similar) between input image data and a registered image, and input image data according to the determination result. In the image processing apparatus that determines whether or not execution of image processing should be prohibited or restricted for image processing, it is impossible to execute image processing on input image data that should originally be allowed to execute due to an erroneous determination, or an execution is originally performed due to an erroneous determination. This is to prevent a problem that image processing of input image data to be prohibited or restricted is executed.

  In order to solve the above problems, an image processing apparatus of the present invention includes an input data acquisition unit that acquires input image data, a feature amount extraction unit that extracts a feature amount of the input image data, and a feature amount of a registered image At least one of a registered image acquisition unit that acquires a feature amount of a registered image from a storage unit that stores information and an external device connected to be communicable with the feature amount of the input image data and the feature amount of the registered image A similarity calculation unit that calculates the similarity between both images, and whether or not to prohibit or limit execution of image processing on the input image data depending on whether the similarity is equal to or greater than a predetermined threshold. An image processing apparatus including a control unit for determining, wherein the registration image includes a permission registration image that is a registration image that permits execution of image processing, and a registration image that prohibits or restricts execution of image processing. Limit climb An identification information acquisition unit that acquires identification information for identifying the permission registration image and the restriction registration image from the storage unit or the external device, and the control unit includes the similarity calculation unit If the maximum value of the calculated similarity is equal to or greater than the threshold value, if the registered image having the maximum similarity is a permitted registered image, execution of image processing on the input image data is permitted, and the similarity is When the registered image that is the maximum value is a restricted registered image, execution of image processing on the input image data is prohibited or restricted.

The image processing is not limited to narrowly defined image processing such as image transformation, conversion, and encoding. For example, copying, printing, electronic distribution, facsimile transmission, filing, image data correction / editing / conversion, This includes all processes for image data such as encoding. Further, the input data acquisition unit may acquire input image data by reading a document with a scanner, for example, and an input created by inputting necessary items using software as a format of electronic data Image data may be acquired, input image data directly created as electronic data may be acquired, and input transmitted from a device connected to be communicable with the image processing device Image data may be acquired.

  According to said structure, the feature-value extraction part extracts the feature-value of the input image data which the input data acquisition part acquired. Then, the similarity calculation unit is connected to the feature amount of the input image data extracted by the feature amount extraction unit and the feature amount of the registered image stored in the storage unit or the external device to which the registered image acquisition unit is communicably connected. The similarity between the two images is calculated by comparing the acquired feature amount of the registered image. The registered image includes a permitted registered image that is a registered image that permits execution of image processing, and a restricted registered image that is a registered image that prohibits or restricts execution of image processing. Then, the identification information acquisition unit acquires identification information for identifying the permission registration image and the restriction registration image from the storage unit or the external device, and the control unit determines that the maximum value of the similarity calculated by the similarity calculation unit is If the registered image having the maximum similarity is the permitted registered image when the threshold value is equal to or greater than the threshold value, execution of image processing on the input image data is permitted, and the registered image having the maximum similarity is the restricted registered image. If it is, execution of image processing on the input image data is prohibited or restricted.

  Thereby, since both the permission registration image and the restriction registration image are registered, when the maximum value of the similarity calculated by the similarity calculation unit is equal to or greater than the threshold value, the registration image having the maximum similarity is permitted registration. It is possible to determine whether to prohibit or restrict execution of image processing depending on whether the image is an image or a restricted registration image. Therefore, for example, by registering input image data that is not a restricted registered image but erroneously determined to be a restricted registered image, as an authorized registered image, an erroneous decision is subsequently made on the input image data. Can be prevented. On the contrary, by registering the input image data erroneously determined to be a permission registration image even though it is not a permission registration image as a restriction registration image, It is possible to prevent erroneous determination.

  An image processing apparatus according to the present invention includes: an input data acquisition unit that acquires input image data; a feature amount extraction unit that extracts a feature amount of the input image data; and features of a restricted registration image that prohibits or restricts execution of image processing At least one of a storage unit that stores the amount and a registered image acquisition unit that acquires a feature amount of the restricted registered image from an external device that is communicably connected, a feature amount of the input image data, and a feature amount of the restricted registered image A similarity calculating unit that calculates the similarity between both images, and a control unit that prohibits or restricts execution of image processing on the input image data when the similarity is equal to or greater than a predetermined threshold value. A feature amount of a permission registration image that permits execution of image processing, and identification information for identifying the restriction registration image and the permission registration image. Includes a registration processing unit that is stored in a second storage unit provided in the external device, and the similarity calculation unit includes a similarity of the input image data to the restricted registration image, and the permission registration image of the input image data. The control unit calculates the similarity with respect to the restriction registration image when the similarity with respect to the restriction registration image is equal to or greater than the threshold, and the similarity with respect to the permission registration image is greater than the similarity with respect to the restriction registration image. In such a case, the image processing may be permitted to be performed on the input image data.

According to said structure, the feature-value extraction part extracts the feature-value of the input image data which the input data acquisition part acquired. Then, the similarity calculation unit is an external device in which the feature amount of the input image data extracted by the feature amount extraction unit and the feature amount of the restricted registered image stored in the storage unit or the registered image acquisition unit are connected to be communicable Is compared with the feature amount of the restriction registration image obtained from the above, and the similarity between both images is calculated. When the similarity is equal to or greater than a predetermined threshold, the control unit performs image processing on the input image data. Prohibit or restrict execution. However, the feature amount of the permission registration image that permits execution of the image processing and the identification information for identifying the restriction registration image and the permission registration image are stored in the storage unit or the second storage unit provided in the external device. It has a registration processing part,
The similarity calculation unit calculates the similarity of the input image data to the restricted registration image and the similarity of the input image data to the permitted registration image. Then, even when the similarity to the restricted registration image is equal to or greater than the threshold value, the control unit performs image processing on the input image data when the similarity to the permitted registration image is larger than the similarity to the restricted registration image. Allow execution.

  As a result, input image data that is not originally restricted registration image image data but whose similarity to the restricted registration image is greater than or equal to a threshold value is registered as a permission registration image, so that image processing for this input image data is performed. Can be executed. For example, by registering input image data that is not a restricted registered image but is erroneously determined to be a restricted registered image as an authorized registered image, an erroneous determination is subsequently made for this input image data. It is possible to prevent the image processing on the input image data from being inappropriately prohibited or restricted.

  The image processing apparatus according to the present invention also includes an input data acquisition unit that acquires input image data, a feature amount extraction unit that extracts a feature amount of the input image data, and a feature of a permission registration image that permits execution of image processing. At least one of a storage unit that stores the amount and a registered image acquisition unit that acquires a feature amount of the permitted registered image from an external device that is communicably connected, a feature amount of the input image data, and a feature amount of the permitted registered image, A similarity calculation unit that calculates the similarity between both images and an image processing device that permits execution of image processing on the input image data when the similarity is equal to or greater than a predetermined threshold. The storage unit or the external device includes a feature amount of a restricted registration image that prohibits or restricts execution of image processing, and identification information for identifying the permitted registration image and the restricted registration image. A registration processing unit to be stored in the second storage unit, wherein the similarity calculation unit calculates the similarity of the input image data to the permitted registration image and the similarity of the input image data to the restricted registration image. When the similarity to the permission registration image is equal to or greater than the threshold value and the similarity to the restriction registration image is greater than the similarity to the permission registration image, the control unit It may be configured to prohibit or restrict execution of image processing on image data.

  According to said structure, the feature-value extraction part extracts the feature-value of the input image data which the input data acquisition part acquired. Then, the similarity calculation unit is an external device in which the feature amount of the input image data extracted by the feature amount extraction unit and the feature amount of the permitted registered image stored in the storage unit or the registered image acquisition unit are connected to be communicable Is compared with the feature amount of the permission registration image obtained from the above, and the similarity between both images is calculated. When the similarity is equal to or greater than a predetermined threshold, the control unit performs image processing on the input image data. Allow execution. However, the feature quantity of the restricted registration image that prohibits or restricts the execution of the image processing and the identification information for identifying the restricted registration image and the permitted registration image are stored in the storage unit or the second storage unit provided in the external device. A registration processing unit is provided for storing, and the similarity calculation unit calculates the similarity of the input image data to the permitted registration image and the similarity of the input image data to the restricted registration image. Then, even when the similarity to the permission registration image is equal to or higher than the threshold, the control unit performs image processing on the input image data when the similarity to the restriction registration image is larger than the similarity to the permission registration image. Allow execution.

Thus, input image data that is not originally image data of a permission registration image but whose similarity to the permission registration image is equal to or greater than a threshold value is registered as a restricted registration image, whereby image processing for the input image data is performed. Execution can be prohibited or restricted. For example, by registering input image data that is not a permission registration image but erroneously determined to be a permission registration image as a restricted registration image, an erroneous determination is subsequently made for the input image data. It is possible to prevent the image processing for the input image data from being permitted, and to improve the security for the exception registered image. For example, it is possible to prevent the image processing such as copying, printing, transmission, conversion / editing, etc. from being performed illegally for the exception registered image.

  Further, the control unit is configured such that the registered image having the maximum similarity calculated by the similarity calculating unit is a permitted registered image, and the similarity to the restricted registered image is equal to or greater than a second threshold value that is greater than the threshold value. Alternatively, if the degree of similarity with respect to the restricted registered image is equal to or greater than the second threshold and the difference between the maximum value and the degree of similarity with respect to the restricted registered image is equal to or less than a predetermined value, execution of image processing on the input image data is performed. It is good also as a structure which prohibits or restrict | limits.

  According to the above configuration, even when the registered image having the maximum similarity is the permitted registered image, when the similarity with respect to the restricted registered image is equal to or greater than the second threshold greater than the threshold, or restricted registration If the similarity to the image is equal to or greater than the second threshold and the difference between the similarity to the permitted registered image and the similarity to the restricted registered image is less than or equal to a predetermined value, execution of image processing on the input image data is performed. Prohibited or restricted. Thereby, the security with respect to a restriction | limiting registration image can be improved.

  A temporary registration information storage unit that stores information about a registration target image that is an image for which registration is requested, and the control unit registers the registration target image when registering the registration target image as the registration image; A temporary registration identifier, a process of storing the temporary registration identifier and the feature amount extracted from the registration target image in the temporary registration information storage unit, and a document corresponding to the registration target image by an image reading unit. The re-read image obtained by re-reading is acquired, and based on the feature amount extracted from the re-read image, the registration target image stored in the temporary registration information storage unit and the storage unit or the second The degree of similarity with respect to the registered image registered in the storage unit is calculated, and it is determined that there are a plurality of images having a similarity equal to or higher than a predetermined threshold, and that there are not a plurality of images. In addition, when the registration processing unit officially registers the registration target image as a registered image in the storage unit or the second storage unit, and when it is determined that there are a plurality of images, the similarity of the plurality of images is determined. When the difference is greater than or equal to a predetermined value, the registration processing unit causes the registration target image to be formally registered as a registered image in the storage unit or the second storage unit, but is less than the predetermined value. In such a case, it may be configured to perform a process of prohibiting formal registration of the registration target image in the storage unit or the second storage unit.

  According to the above configuration, when registration of a registration target image is requested, it is determined whether or not the registration target image can be identified from a registered image that has already been registered. If the image cannot be identified, the registration of the registration target image can be prohibited. Therefore, it is possible to prevent a new registration of an image that cannot be distinguished from a registered image that has already been registered. Therefore, it is possible to accurately determine whether an input image is similar to a restricted registration image or a permission registration image.

  In addition, when the difference is less than a predetermined value, a registration data deletion unit that deletes information about the registration target image stored in the temporary registration information storage unit may be provided.

  According to the above configuration, the information about the registration target image that cannot be identified can be deleted from the temporary registration information storage unit, so that the information about the registration target image can be prevented from leaking.

An image forming apparatus of the present invention includes any one of the above-described image processing apparatuses and an image output unit that forms an image corresponding to input image data on a recording material. An image transmission apparatus according to the present invention includes any one of the above-described image processing apparatuses and a transmission apparatus that transmits input image data to another apparatus that is communicably connected. The image reading apparatus of the present invention includes an image input apparatus that reads an original image and acquires input image data, and any one of the image processing apparatuses described above.

  According to the image forming apparatus, the image transmitting apparatus, and the image reading apparatus, since both the restricted registered image and the permitted registered image are registered, the maximum value of the similarity calculated by the similarity calculating unit is equal to or more than the threshold value. In some cases, it is possible to determine whether to prohibit or restrict execution of image processing depending on whether the registered image having the maximum similarity is a permitted registered image or a restricted registered image.

  In order to solve the above problems, an image processing method of the present invention includes an input data acquisition step for acquiring input image data, a feature amount extraction step for extracting feature amounts of input image data, and a feature amount of a registered image. A registration data acquisition step to acquire, a similarity calculation step of calculating a similarity between both images by comparing the feature amount of the input image data and the feature amount of the registered image, and the similarity is equal to or greater than a predetermined threshold value A process restriction step for determining whether or not to prohibit or restrict execution of image processing on the input image data depending on whether or not there is an image processing method. An identification for acquiring identification information for identifying a permission registration image and a restriction registration image, that is, a permission registration image that is a registration image that is permitted and a restriction registration image that is a registration image that prohibits or restricts execution of image processing. Including the information acquisition step, and in the processing restriction step, when the maximum value of the similarity calculated in the similarity calculation step is equal to or greater than the threshold, or when the registered image having the maximum similarity is a permitted registered image Allows execution of image processing on the input image data, and prohibits or restricts execution of image processing on the input image data when the registered image having the maximum similarity is a restricted registered image. Yes.

  According to the above method, the feature amount of the input image data acquired in the input data acquisition step is extracted in the feature amount extraction step. In the similarity calculation step, the feature amount of the input image data extracted in the feature amount extraction step is compared with the feature amount of the registered image acquired in the registration data acquisition step to calculate the similarity between both images. The registered image includes a permitted registered image that is a registered image that permits execution of image processing, and a restricted registered image that is a registered image that prohibits or restricts execution of image processing. Then, in the identification information acquisition step, identification information for identifying the permission registration image and the restriction registration image is obtained from the storage unit or the external device, and in the processing restriction step, the maximum value of the similarity calculated in the similarity calculation step Is equal to or greater than the threshold value, if the registered image having the maximum similarity is the permitted registered image, execution of image processing is permitted for the input image data, and the registered image having the maximum similarity is registered for restriction. In the case of an image, execution of image processing on input image data is prohibited or restricted.

  Thereby, when the maximum value of the similarity calculated in the similarity calculation step is equal to or greater than the threshold value, it is possible to determine whether to prohibit or restrict execution of image processing according to the registered image having the maximum similarity. it can. Therefore, for example, by registering input image data that is not a restricted registered image but erroneously determined to be a restricted registered image, as an authorized registered image, an erroneous decision is subsequently made on the input image data. Can be prevented. On the contrary, by registering the input image data erroneously determined to be a permission registration image even though it is not a permission registration image as a restriction registration image, It is possible to prevent erroneous determination.

In order to solve the above problems, an image processing system of the present invention includes an image processing device and a server device that is communicably connected to the image processing device, and acquires input image data. A storage unit storing a feature amount of a registered image, a similarity calculation unit that compares the feature amount of the input image data and the feature amount of the registered image, and calculates the similarity of both images, and the similarity is A control unit that determines whether or not to prohibit or restrict execution of image processing on the input image data according to whether or not the threshold value is greater than or equal to a predetermined threshold is distributed between the image processing device and the server device. The registration image includes a permission registration image that is a registration image that permits execution of image processing, and a restriction registration image that is a registration image that prohibits or restricts execution of image processing. An identification information acquisition unit that acquires identification information for identifying the permission registration image and the restriction registration image from the storage unit or the external device, and the control unit calculates the similarity calculation unit. If the maximum similarity value is equal to or greater than the threshold value and the registered image having the maximum similarity value is a permitted registered image, the execution of image processing is permitted for the input image data, and the similarity level If the registered image having the maximum value is a restricted registered image, execution of image processing on the input image data is prohibited or restricted.

  According to said structure, the feature-value extraction part extracts the feature-value of the input image data which the input data acquisition part acquired. Then, the similarity calculation unit compares the feature amount of the input image data extracted by the feature amount extraction unit with the feature amount of the registered image stored in the storage unit, and calculates the similarity of both images. The registered image includes a permitted registered image that is a registered image that permits execution of image processing, and a restricted registered image that is a registered image that prohibits or restricts execution of image processing. Then, the identification information acquisition unit acquires identification information for identifying the permission registration image and the restriction registration image from the storage unit or the external device, and the control unit determines that the maximum value of the similarity calculated by the similarity calculation unit is If the registered image having the maximum similarity is the permitted registered image when the threshold value is equal to or greater than the threshold value, execution of image processing on the input image data is permitted, and the registered image having the maximum similarity is the restricted registered image. If it is, execution of image processing on the input image data is prohibited or restricted.

  Thereby, since both the permitted registered image and the restricted registered image are registered as registered images, when the maximum value of the similarity calculated by the similarity calculating unit is equal to or more than the threshold value, the registered image having the maximum similarity. Whether or not execution of image processing is prohibited or restricted can be determined depending on whether the image is a permission registration image or a restriction registration image. Therefore, for example, by registering input image data that is not a restricted registered image but erroneously determined to be a restricted registered image, as an authorized registered image, an erroneous decision is subsequently made on the input image data. Can be prevented. On the contrary, by registering the input image data erroneously determined to be a permission registration image even though it is not a permission registration image as a restriction registration image, It is possible to prevent erroneous determination.

  The image processing apparatus may be realized by a computer. In this case, an image processing program for causing the image processing apparatus to be realized by the computer by causing the computer to operate as the respective units, and the program are recorded. Computer-readable recording media are also included in the scope of the present invention.

  As described above, in the image processing apparatus of the present invention, when the maximum value of the similarity calculated by the similarity calculation unit is equal to or greater than the threshold value, the registered image having the maximum similarity is the permitted registered image. In the case of, the execution of the image processing for the input image data is permitted, and when the registered image having the maximum similarity is the restricted registered image, the execution of the image processing for the input image data is prohibited or restricted.

  Therefore, when the maximum value of the similarity calculated by the similarity calculation unit is equal to or greater than the threshold value, image processing is performed depending on whether the registered image having the maximum similarity is a permitted registered image or a restricted registered image. It is possible to determine whether execution is prohibited or restricted.

Embodiment 1
An embodiment of the present invention will be described. In the present embodiment, an example in the case where the present invention is applied to a digital color multifunction peripheral (MFP) will be described.

(1-1. Configuration of Digital Color Multifunction Machine 1)
FIG. 2 is a block diagram showing a schematic configuration of a digital color multifunction peripheral (image processing apparatus, image forming apparatus, image reading apparatus) 1 according to the present embodiment. The digital color multifunction peripheral 1 has a copy function, a printer function, a facsimile transmission function, a scanner function, a scan to e-mail function, and the like.

  As shown in FIG. 2, the digital color MFP 1 includes a color image input device 2, a color image processing device 3, a color image output device 4, a communication device 5, and an operation panel 6.

  The color image input device (image reading device) 2 is composed of a scanner unit (not shown) having a device that converts optical information into an electrical signal, such as a CCD (Charge Coupled Device), for example, and a reflected light image from a document. Are output to the color image processing apparatus 3 as analog signals of RGB (R: red, G: green, B: blue).

  The color image processing apparatus 3 includes an A / D conversion unit 11, a shading correction unit 12, a document matching processing unit 13, an input tone correction unit 14, a region separation processing unit 15, a color correction unit 16, and a black generation and under color removal unit 17. A spatial filter processing unit 18, an output tone correction unit 19, and a tone reproduction processing unit 20. An analog signal output from the color image input device 2 to the color image processing device 3 is converted into an A / D conversion unit 11, a shading correction unit 12, a document matching processing unit 13, and an input tone correction unit in the color image processing device 3. 14, the region separation processing unit 15, the color correction unit 16, the black generation and under color removal unit 17, the spatial filter processing unit 18, the output gradation correction unit 19, and the gradation reproduction processing unit 20 are sent in this order, and CMYK digital color The signal is output to the color image output device 4 as a signal.

  The A / D (analog / digital) converter 11 converts RGB analog signals into digital signals.

  The shading correction unit 12 performs a process for removing various distortions generated in the illumination system, the imaging system, and the imaging system of the color image input apparatus 2 on the digital RGB signal sent from the A / D conversion unit 11. Is. Further, the shading correction unit 12 performs a process of converting color balance adjustment and a signal such as a density signal that can be easily handled by the image processing system employed in the color image processing apparatus 3.

  The document collation processing unit 13 determines the similarity between the input image data and the registered image ((similarity / no similarity)). The document collation processing unit 13 directly inputs the input RGB signal to the subsequent input. The data is output to the gradation correction unit 14. The details of the document collation processing unit 13 will be described later.

  The input tone correction unit 14 performs image quality adjustment processing such as removal of background color (background color density component: background density) and contrast on the RGB signal from which various distortions have been removed by the shading correction unit.

  The region separation processing unit 15 separates each pixel in the input image into one of a character region, a halftone dot region, and a photo region from the RGB signal. Based on the separation result, the region separation processing unit 15 generates a region identification signal indicating which region the pixel belongs to, the color correction unit 16, the black generation and under color removal unit 17, the spatial filter processing unit 18, and the gradation reproduction. The output signal is output to the processing unit 20, and the input signal output from the input tone correction unit 14 is output to the subsequent color correction unit 16 as it is.

The color correction unit 16 performs a process of removing color turbidity based on spectral characteristics of CMY (C: cyan, M: magenta, Y: yellow) color materials including unnecessary absorption components in order to realize faithful color reproduction. Is.

  The black generation and under color removal unit 17 generates black (K) signals from the CMY three-color signals after color correction, and subtracts the K signals obtained by black generation from the original CMY signals to generate new CMY signals. The process to generate is performed. As a result, the CMY three-color signal is converted into a CMYK four-color signal.

  The spatial filter processing unit 18 performs spatial filter processing using a digital filter on the image data of the CMYK signal input from the black generation and under color removal unit 17 to correct the spatial frequency characteristics. As a result, blurring of the output image and deterioration of graininess can be reduced. Similar to the spatial filter processing unit 18, the gradation reproduction processing unit 20 also performs predetermined processing on the image data of the CMYK signal based on the region identification signal.

  For example, the region separated into characters by the region separation processing unit 15 has a high frequency enhancement amount in the sharp enhancement processing in the spatial filter processing by the spatial filter processing unit 18 in order to improve the reproducibility of black characters or color characters. Increased. At the same time, the tone reproduction processing unit 20 selects binarization or multi-value processing on a high-resolution screen suitable for high-frequency reproduction.

  Further, with respect to the region separated into halftone dot regions by the region separation processing unit 15, the spatial filter processing unit 18 performs low-pass filter processing for removing the input halftone component. The output tone correction unit 19 performs an output tone correction process for converting a signal such as a density signal into a halftone dot area ratio that is a characteristic value of the color image output device 4. Then, gradation reproduction processing (halftone generation) is performed so that the image is finally separated into pixels and each gradation is reproduced. For the region separated into photographs by the region separation processing unit 15, binarization or multi-value processing is performed on the screen with an emphasis on gradation reproducibility.

  The image data subjected to the above-described processes is temporarily stored in a storage device (not shown), read out at a predetermined timing, and input to the color image output device 4.

  The color image output device 4 outputs the image data input from the color image processing device 3 onto a recording material (for example, paper). The configuration of the color image output device 4 is not particularly limited, and for example, a color image output device using an electrophotographic method or an inkjet method can be used.

  The communication device 5 is composed of a modem or a network card, for example. The communication device 5 performs data communication with other devices (for example, personal computers, server devices, other digital multifunction peripherals, facsimile devices, etc.) connected to the network via a network card, a LAN cable, or the like.

  When the image data is transmitted, the communication device 5 performs the transmission procedure with the other party and secures a state in which the image data can be transmitted. Then, the communication device 5 compresses the image data (image data read by the scanner) in a predetermined format. ) Is read from the memory, and necessary processing such as changing the compression format is performed, and then sequentially transmitted to the other party via the communication line.

Further, when receiving the image data, the communication device 5 performs a communication procedure and receives the image data transmitted from the other party and inputs it to the color image processing device 3. The received image data is subjected to predetermined processing such as expansion processing, rotation processing, resolution conversion processing, output gradation correction, gradation reproduction processing, and the like by the color image processing apparatus 3 and is output by the color image output apparatus 4. The received image data may be stored in a storage device (not shown), and the color image processing device 3 may read it out as necessary to perform the predetermined processing.

  The operation panel 6 includes, for example, a display unit such as a liquid crystal display and setting buttons (none of which are shown), and information corresponding to an instruction from a main control unit (not shown) of the digital color multifunction peripheral 1 is described above. While displaying on a display part, the information input from a user via the said setting button is transmitted to the said main control part. The user requests processing of input image data via the operation panel 6 (for example, processing mode (copying, printing, electronic distribution, facsimile transmission, filing, image data correction, editing, etc.), processing number (number of copies, number of copies). , Input image data transmission destination, etc.) can be input. The main control unit includes, for example, a CPU (Central Processing Unit) and the like, and is based on programs and various data stored in a ROM (not shown) and the like, information input from the operation panel 6, and the like. To control the operation.

(1-2. Configuration of Document Collation Processing Unit)
Next, details of the document matching processing unit 13 will be described. The document matching processing unit 13 according to the present embodiment extracts a plurality of feature points from input image data, determines a set of local feature points for each extracted feature point, and features points from the determined sets. As a quantity that characterizes each selected subset, an invariant for geometric transformation is obtained based on a plurality of combinations of feature points in the subset, and the obtained invariants are combined. By calculating a hash value and voting for a registered image corresponding to the calculated hash value, a search for a registered image similar to the input image data and a determination process of similarity to the registered image (judgment of similarity / no similarity) I do.

  FIG. 1 is a block diagram illustrating a schematic configuration of the document matching processing unit 13. As shown in this figure, the document matching processing unit 13 includes a feature point calculation unit 31, a feature amount calculation unit 32, a voting processing unit 33, a similarity determination processing unit 34, a registration processing unit 35, a control unit 7, and a memory 8. I have.

  The control unit 7 controls the operation of each unit of the document collation processing unit 13. The control unit 7 may be provided in a main control unit for controlling the operation of each unit of the digital color multifunction peripheral 1, and is provided separately from the main control unit. It may control the operation of the processing unit 13.

  Further, when it is determined that there is no similarity (the input image data is not the image data of the registered image) as a result of the similarity determination processing by the document matching processing unit 13, the control unit 7 performs image processing (copying) on the input image data. Execution of processing such as printing, electronic distribution, facsimile transmission, filing, image data correction, and editing. Further, when it is determined that there is similarity (the input image data is image data of a registered image), the control unit 7 determines whether the registered image having the highest similarity is an exception registered image. When the image is an exception registered image, the execution of the image processing for the input image data is permitted. When the image is not the exception registered image, the execution of the image processing is prohibited or restricted. Here, if the image is not an exception registered image, the execution of the image processing is prohibited or restricted. However, the present invention is not limited to this. For example, a specific pattern is added to the image, or a part or all of the image is filled. You may add restrictions such as.

  The memory 8 stores various data used for processing of each unit of the document collation processing unit 13, processing results, and the like. Further, the memory 8 stores an administrator (a specific user; a pre-registered person who has authority to perform registration, editing, etc. of feature amounts of registered images and exception registered images, threshold values for similarity determination, and the like. An administrator folder 8A that is a folder (storage area) that can be browsed and edited only by a security officer at a store or the like (however, the control unit 7 can refer to information in the administrator folder 8A as necessary). ing.

  The administrator folder 8A includes an administrator information storage unit 101, a hash table 102, an exception registered image list 103, and the like.

  The administrator information storage unit 101 stores information for specifying an administrator who is permitted to view and edit the administrator folder 8A. When browsing or editing of the administrator folder 8A is requested, the control unit 7 performs an authentication process based on the administrator information storage unit 101 and determines whether to permit browsing or editing. . Note that the administrator authentication processing method is not particularly limited, and various conventionally known authentication processing methods can be used, for example. In this embodiment, the administrator transmits information necessary for authentication to the digital color multifunction device 1 from an external device (computer, server device, etc.) that is communicably connected to the digital color multifunction device 1. Although the authentication process is performed, the present invention is not limited to this. For example, the authentication process may be performed via the operation panel 6 of the digital color multifunction peripheral 1.

  The hash table 102 is a table that stores an index (ID) of a registered image and a feature amount of the registered image in association with each other. Details of the hash table 102 will be described later.

  The exception registered image list 103 is a list of exception registered images that are registered images that are permitted to be subjected to image processing even when it is determined that the input image data is image data of the registered image. That is, when the control unit 7 determines that the input image data is image data of a registered image, the control unit 7 prohibits or restricts execution of image processing on the input image data in principle, but the registered image is an exception registered image. In this case, the execution of image processing is permitted exceptionally.

  The feature point calculation unit 31 extracts a connected part of a character string or a ruled line, and calculates the center of gravity of the connected part as a feature point. However, the configuration of the feature point calculation unit 31 is not limited to this. For example, the feature points may be calculated by various conventionally known methods.

  FIG. 3 is a block diagram illustrating a schematic configuration of the feature point calculation unit 31. As shown in this figure, the feature point calculation unit 31 includes a signal processing unit (achromatic processing unit) 41, a resolution conversion unit 42, an MTF processing unit 43, a binarization processing unit 44, and a centroid calculation unit 45. Yes.

  When the image data (RGB signal) input from the shading correction unit 12 is a color image, the signal processing unit 41 achromatically converts the image data into a lightness signal or a luminance signal.

  For example, the signal processing unit 41 converts the RGB signal into the luminance signal Y by the following equation (1).

Yi = 0.30Ri + 0.59Gi + 0.11Bi (1)
Here, Y is a luminance signal of each pixel, R, G, and B are each color component in the RGB signal of each pixel, and the subscript i is a value assigned to each pixel (i is an integer of 1 or more). It is.

Alternatively, the RGB signal may be converted into a CIE 1976 L ^* a ^* b ^* signal (CIE: Commission International de l'Eclairage, L ^* : brightness, a ^* , b ^* : chromaticity).

The resolution conversion unit 42 performs a scaling process on the input image data. For example, when the input image data is optically scaled by the color image input device 2, the resolution conversion unit 42 scales the input image data again so that the predetermined resolution is obtained. Further, the resolution conversion unit 42 may perform resolution conversion for lowering the resolution than the resolution read at the same magnification in the color image input device 2 in order to reduce the processing amount in each processing unit in the subsequent stage. (For example, 600dp
For example, image data read in i (dot per inch) is converted to 300 dpi).

  An MTF (modulation transfer function) processing unit 43 is used to absorb (adjust) that the spatial frequency characteristics of the color image input device 2 are different for each model. In the image signal output by the CCD, MTF degradation occurs due to optical components such as lenses and mirrors, aperture aperture of the light receiving surface of the CCD, transfer efficiency and afterimages, integration effects due to physical scanning, and uneven operation. ing. Due to the deterioration of the MTF, the read image is blurred. The MTF processing unit 43 performs a process of repairing the blur caused by the deterioration of the MTF by performing an appropriate filter process (enhancement process). Further, it is also used to suppress high-frequency components that are not necessary for the feature point extraction processing in the latter-stage gravity center calculation unit 45. That is, enhancement and smoothing processing is performed using a mixing filter (not shown). FIG. 4 shows an example of the filter coefficient in this mixed filter.

  The binarization processing unit 44 binarizes the image data by comparing the achromatic image data (brightness value (brightness signal) or brightness value (brightness signal)) with a preset threshold value. .

  The center-of-gravity calculation unit 45 performs labeling (labeling processing) on each pixel based on the image data binarized by the binarization processing unit 44 (for example, represented by “1” and “0”). I do. Then, a connected area where pixels with the same label are connected is specified, and the center of gravity of the specified connected area is extracted as a feature point. Further, the extracted feature points are output to the feature amount calculation unit 32. FIG. 5 is an explanatory diagram showing an example of the connected area extracted from the input image data and the center of gravity of the connected area, and shows the connected area and the center of gravity corresponding to the character string “A”. FIG. 6 is an explanatory diagram showing an example of each center of gravity (feature point) of a plurality of connected regions extracted from a character string included in input image data. The feature points can be represented by coordinate values (x coordinate, y coordinate) in the binary image.

  The feature amount calculation unit 32 includes a feature point extraction unit 32a, an invariant calculation unit 32b, and a hash value calculation unit 32c. The feature point calculated by the feature point calculation unit 31 is used to rotate and parallelize a document image. A feature amount (hash value and / or invariant) that is an invariable amount with respect to geometric deformation such as movement, enlargement, reduction, and parallel movement is calculated.

  As shown in FIG. 7, the feature point extraction unit 32a sets one feature point as a target feature point, and sets a predetermined number of feature points in the vicinity of the target feature point in order from the closest distance from the target feature point (here 4 points) are extracted as peripheral feature points. In the example of FIG. 7, when the feature point a is the feature point of interest, four feature points b, c, d, and e are extracted as the peripheral feature points, and when the feature point b is the feature point of interest. Four points of feature points a, c, e, and f are extracted as peripheral feature points.

  Further, the feature point extraction unit 32a extracts a combination of three points that can be selected from the four peripheral feature points extracted as described above. For example, as shown in FIGS. 8A to 8C, when the feature point a shown in FIG. 7 is the target feature point, three of the peripheral feature points b, c, d, and e Combinations, that is, combinations of peripheral feature points b, c, d, peripheral feature points b, c, e, and peripheral feature points b, d, e are extracted.

Next, the invariant calculation unit 32b calculates an invariant (one of feature quantities) Hij with respect to geometric deformation for each extracted combination. Here, i is a number indicating the feature point of interest (i is an integer equal to or greater than 1), and j is a number indicating a combination of three peripheral feature points (j is an integer equal to or greater than 1). In the present embodiment, the ratio of two of the lengths of the line segments connecting the peripheral feature points is set as the invariant Hij. The length of the line segment may be calculated based on the coordinate value of each peripheral feature point. For example, in the example of FIG. 8A, if the length of the line segment connecting the feature point c and the feature point d is A11 and the length of the line segment connecting the feature point c and the feature point b is B11, The variable H11 is H11 = A11 / B1
1. In the example of FIG. 8B, if the length of the line segment connecting the feature point c and the feature point b is A12 and the length of the line segment connecting the feature point b and the feature point e is B12, The variable H12 is H12 = A12 / B12. In the example of FIG. 8C, if the length of the line segment connecting the feature point d and the feature point b is A13 and the length of the line segment connecting the feature point b and the feature point e is B13, The variable H13 is H13 = A13 / B13. In this way, invariants H11, H12, and H13 are calculated in the examples of FIGS. 8 (a) to 8 (c). In the above example, the line segment connecting the peripheral feature point located on the left side in the horizontal direction and the peripheral feature point located in the center in the horizontal direction is Aij, and the peripheral feature point located in the center in the horizontal direction is located on the right side in the horizontal direction. The line segment connecting the peripheral feature points is Bij. However, the present invention is not limited to this, and the line segment used for calculating the invariant Hij may be selected by an arbitrary method.

Next, the hash value calculation unit 32c calculates a remainder value of (Hi1 × 10 ² + Hi2 × 10 ¹ + Hi3 × 10 ⁰ ) / D as a hash value (one of feature quantities) Hi and stores it in the memory 8. . Note that D is a constant set in advance according to how much the range of values that the remainder can take is set.

  Note that the method for calculating the invariant Hij is not particularly limited. For example, the cross ratio of five points in the vicinity of the feature point of interest, or the double ratio of five points extracted from the neighboring n points (n is an integer of n ≧ 5). The value calculated based on the arrangement of m points extracted from n points in the vicinity (m is an integer of m <n and m ≧ 5) and the cross ratio of the five points extracted from m points, etc. The invariant Hij may be used. The cross ratio is a value obtained from four points on a straight line or five points on a plane, and is known as an invariant with respect to projective deformation which is a kind of geometric transformation.

  Also, the formula for calculating the hash value Hi is not limited to the above formula (2), and other hash functions (for example, any one of the hash functions described in Patent Document 4) may be used. Good.

  Further, each part of the feature quantity calculation unit 32, after completing the extraction of the peripheral feature points for one target feature point and the calculation of the hash value Hi, changes the target feature point to another feature point, A hash value is calculated, and hash values for all feature points are calculated.

  In the example of FIG. 7, when the extraction of the peripheral feature point and the hash value when the feature point a is the target feature point is finished, the extraction of the peripheral feature point and the hash value when the feature point b is the target feature point is completed. I do. In the example of FIG. 7, when the feature point b is set as the feature point of interest, four feature points a, c, e, and f are extracted as the peripheral feature points. Then, as shown in FIGS. 9A to 9C, a combination of three points selected from these peripheral feature points a, c, e, and f (peripheral feature points a, e, f, and peripheral points) Feature points c, e, f, peripheral feature points a, c, f) are extracted, and a hash value Hi is calculated for each combination and stored in the memory 8. Then, this process is repeated for each feature point, and a hash value when each feature point is a feature point of interest is obtained and stored in the memory 8.

  Note that the invariant calculation method when the feature point a is the feature point of interest is not limited to the above method. For example, as shown in FIGS. 20A to 20D, when the feature point a shown in FIG. 7 is the feature point of interest, three of the peripheral feature points b, c, d, and e are selected. Combinations, that is, peripheral feature points b, c, d, peripheral feature points b, c, e, peripheral feature points b, d, e, peripheral feature points c, d, e are extracted, and each extracted combination , An invariant (one of feature quantities) Hij with respect to geometric deformation may be calculated.

Further, when the feature point b shown in FIG. 7 is set as a feature point of interest, as shown in FIGS. 21A to 21D, four peripheral feature points of feature points a, c, e, and f are used. A combination of three points (peripheral feature points a, e, f, peripheral feature points a, c, e, peripheral feature points a, f, c, peripheral feature point e
, F, c) may be extracted, and an invariant Hij with respect to geometric deformation may be calculated for each combination. In this case, the remainder of (Hi1 × 10 ³ + Hi2 × 10 ² + Hi3 × 10 ¹ + Hi4 × 10 ⁰ ) / D may be calculated as a hash value and stored in the memory 8.

  In the above example, the line segment connecting the peripheral feature point closest to the target feature point and the second closest peripheral feature point is Aij, and the peripheral feature point closest to the target feature point and the third closest peripheral feature point are The line segment connecting the two is connected to Bij. However, the present invention is not limited to this, and the line segment used for calculating the invariant Hij may be selected by an arbitrary method such as selecting based on the length of the line segment connecting the neighboring feature points. That's fine.

  Note that, when performing registration processing for registering input image data as a registered image, the feature amount calculation unit 32 performs registration processing for hash values (feature amounts) for each feature point of the input image data calculated as described above. Send to part 35.

  The registration processing unit 35 sequentially registers a hash value for each feature point calculated by the feature amount calculation unit 32 and an index (document ID) representing a document (registered image) in the hash table 102 provided in the memory 8. (See FIG. 10A). If the hash value is already registered, the document ID is registered in association with the hash value. Document IDs are sequentially assigned numbers without duplication. When the number of documents registered in the hash table 102 exceeds a predetermined value (for example, 80% of the number of documents that can be registered), the old document ID may be searched and sequentially deleted. . The deleted document ID may be used again as the document ID of a new registered image. Further, when the calculated hash values are the same value (H1 = H5 in the example of FIG. 10B), these may be combined and registered in the hash table 102.

  In addition, when performing a determination process (similarity determination process) on whether or not the input image data is image data of a registered image that has already been registered, the feature amount calculation unit 32 calculates the input image calculated as described above. A hash value for each feature point of the data is sent to the voting processing unit 33.

  The voting processing unit 33 compares the hash value of each feature point calculated from the input image data with the hash value registered in the hash table 102, and votes for registered images having the same hash value. In other words, for each registered image, the number of times the same hash value as the hash value of the registered image is calculated from the input image data is counted, and the count value is stored in the memory 8. FIG. 11 is a graph showing an example of the number of votes for registered images ID1, ID2, and ID3.

  The similarity determination processing unit 34 reads the voting result (the index of each registered image and the number of votes for each registered image; similarity) of the voting processing unit 33 from the memory 8 and obtains the maximum number of votes and the maximum number of votes obtained. Extract image index. Then, the extracted maximum number of votes is compared with a predetermined threshold value to determine similarity (whether or not the input image data is image data of a registered image), and a determination signal indicating the determination result is transmitted to the control unit 7. Send to. That is, if the maximum number of votes is greater than or equal to a predetermined threshold, it is determined that there is similarity (the input image data is image data of a registered image), and if it is less than the threshold, there is no similarity. (The input image data is not image data of a registered image).

  Alternatively, the similarity determination processing unit 34 calculates the similarity by dividing and normalizing the number of votes obtained for each registered image by the total number of votes (the total number of feature points extracted from the input image data). The similarity may be determined by comparing with a predetermined threshold value (for example, 80% of the total number of votes).

In addition, the similarity determination processing unit 34 normalizes the number of votes obtained for each registered image by dividing by the number of registered hash values (maximum registered number) for the registered image having the largest number of registered hash values. The degree of similarity may be determined by calculating the degree and comparing the degree of similarity with a predetermined threshold (for example, 80% of the total number of votes). That is, if the calculated similarity is equal to or greater than the threshold value TH2, it is determined that “there is similarity”, and if it is less than the threshold value TH2, it is determined that “there is no similarity”. In this case, the total number of hash values extracted from the input image data may be larger than the maximum registered number (particularly when at least a part of the original and / or registered image has a handwritten part). The calculated value of similarity may exceed 100%.

  Further, the threshold value TH2 for determining similarity may be constant for each registered image, or may be set for each registered image according to the importance of each registered image. The importance of the registered image depends on the registered image, for example, the importance is maximized for banknotes, securities, confidential documents, confidential documents, etc., and the importance is lower for banknotes, etc. May be set step by step. In this case, a weighting coefficient corresponding to the importance of the registered image is stored in the memory 8 in association with the index of the registered image, and the similarity determination processing unit 34 corresponds to the registered image that has obtained the maximum number of votes. The similarity may be determined using the threshold value TH2.

  Further, when determining the similarity, the threshold value TH2 is kept constant, while the similarity is determined by multiplying the number of votes for each registered image (the number of votes of each registered image) by the weighting coefficient of each registered image. Good. In this case, a weighting coefficient corresponding to the importance of each registered image is stored in the memory 8 in association with the index of each registered image, and the similarity determination processing unit 34 determines the number of registered images for each registered image. The number of corrected votes multiplied by the weighting coefficient is calculated, and the similarity may be determined based on the number of corrected votes. For example, the maximum corrected number of votes may be compared with the threshold TH2, or the maximum corrected number of votes normalized with the total number of votes may be compared with the threshold TH2, and the maximum corrected number of votes is normalized with the maximum number of registrations. This may be compared with the threshold value TH2. In this case, for example, the weighting factor may be set to a value larger than 1, and to a larger value as the importance of the registered image becomes higher.

  In this embodiment, one hash value is calculated for one feature point (attention feature point). However, the present invention is not limited to this, and a plurality of one feature point (attention feature point) may be calculated. A hash value may be calculated. For example, 6 points are extracted as the peripheral feature points of the feature point of interest, and for each of the 6 combinations obtained by extracting 5 points from these 6 points, 3 points are extracted from 5 points to obtain an invariant and a hash value is calculated. You may use the method to do. In this case, six hash values are calculated for one feature point.

(1-3. Processing in the digital color multifunction peripheral 1)
Next, processing in the digital color multifunction peripheral 1 will be described with reference to the flowchart shown in FIG. In the following description, it is assumed that administrator information is registered in the administrator information storage unit 101 in advance.

  First, the control unit 7 acquires input image data and a processing request (instruction input) input from the user via the operation panel 6 or the communication device 5 (S1, S2). The input image data may be acquired by reading a document image with the color image input device 2, or input image data transmitted from an external device may be acquired with the communication device 5. The input image data may be read and acquired from various recording media via a card reader (not shown) provided in FIG.

Next, the control unit 7 determines whether or not the process requested by the process request is a registration process (S3). If it is a registration process, an authentication process is performed to determine whether or not the user requesting the process is an administrator registered in the administrator information storage unit 101 (S4). For example, the control unit 7 acquires user information (user ID, password, etc.) input by the user via the operation panel 6 or the communication device 5 and is registered in the acquired user information and administrator information storage unit 101. Authentication processing is performed by collating with administrator information (administrator user information).

  Then, it is determined whether or not the authentication is successful (S5). If it is determined that the authentication is not successful, the process is terminated. If authentication fails, the user may be allowed to re-enter user information a predetermined number of times, and the authentication process may be performed a predetermined number of times.

  On the other hand, when the authentication process is successful in S4, the control unit 7 controls each unit of the document matching processing unit 13, and performs the feature point calculation process (S6) and the feature amount calculation process (S7) for the input data acquired in S1. The calculated feature value and the document ID (registered image ID) are associated with each other and registered in the hash table 102 (S8).

  Next, the control unit 7 determines whether the process requested by the process request is a registration process of a registered image (an image that prohibits or restricts execution of the process) or an exception registration image (an image that permits execution of the process). It is determined whether it is a registration process (S9).

  If it is not an exception registration image registration process, the control unit 7 ends the process. On the other hand, in the case of the exception registration image registration process, the control unit 7 controls the registration processing unit 35 to register the ID of the image in the exception registration image list 103 (S10), and ends the process. FIG. 13 is an explanatory diagram showing an example of the exception registered image list 103.

  When it is determined that the registration process is not performed in S3, the control unit 7 controls each unit of the document collation processing unit 13, and performs feature point calculation processing (S11), feature amount calculation processing (S12), and input data acquired in S1. A voting process (S13) and a similarity determination process (S14) are performed. Then, the control unit 7 determines whether or not it is determined that there is similarity as a result of the similarity determination process (S15). If it is determined that there is no similarity, the control unit 7 permits execution of image processing (copying, electronic distribution, facsimile transmission, filing, image data correction, editing, etc.) on the input image data (S16). The process is terminated.

  On the other hand, if it is determined in S15 that there is similarity, the control unit 7 determines whether or not the registered image having the highest similarity is an exception registered image as a result of the voting process (S17). That is, the control unit 7 determines whether or not the ID of the registered image having the highest similarity as a result of the voting process is registered in the exception registered image list 103, so that this registered image is an exception registered image. Judge whether there is. However, the present invention is not limited to this. For example, when registering the feature amount of the registered image and the document ID in the hash table 102, a flag is added to the document ID (for example, flag “1” for an exception registered image, If it is not a registered image flag “0”), in the processing of S17, the control unit 7 may determine whether or not it is an exceptional registered image by referring to this flag.

  Note that the control unit 7 stores the input image data determined to be similar in S15 and determined not to be an exception registered image in S17 (or compressed image data obtained by compressing the input image data) in the administrator folder 8A. You may do it. Thereby, the appropriateness of the determination result can be easily confirmed by the administrator viewing the image data stored in the administrator folder 8A later.

On the other hand, if it is determined in S17 that the image is not an exception registered image, execution of image processing on the input image data is prohibited (S18), and the processing is terminated. On the other hand, if it is determined in S15 that the image is an exception registered image, execution of image processing on the input image data is permitted (S16), and the processing is terminated.

  As described above, in the digital color multifunction peripheral 1 according to the present embodiment, the feature amount of a registered image (restricted registered image) that prohibits or restricts execution of image processing and the registered image (permitted registered image) that permits execution of image processing. ) Is stored. In addition, information indicating whether each registered image is a registered image that permits execution of image processing or a registered image that prohibits or restricts execution of image processing is stored. If it is determined that there is similarity as a result of the similarity determination process between the input image data and the registered image, the control unit 7 determines whether the registered image with the highest similarity is a registered image that permits execution of the image processing. Then, it is determined whether the image is a registered image that prohibits or restricts execution of image processing, and image processing is prohibited, restricted, or permitted according to the determination result.

  Accordingly, the control unit 7 can determine whether to prohibit or restrict the execution of the image processing in accordance with the registration content of the registered image having the highest degree of similarity (whether it is an exception registered image).

  This point will be described in more detail with reference to FIGS. 14 (a) to 14 (c) and FIGS. 15 (a) to 15 (c).

  FIG. 14A to FIG. 14C show the input to the registered image IDa when the registered image IDa is registered as a registered image that prohibits execution of image processing and no exception registered image is registered. It is a graph which shows the result of having calculated the similarity of image data IDa ', IDb', and IDc '. The input image data IDa ′ is input image data acquired by reading the registered image IDa with a scanner. Further, the input image data IDb ′ is input image data obtained by reading an image IDb which is not a registered image but has a relatively high similarity to the registered image with a scanner. The input image data IDc ′ is input image data acquired by reading an image having a relatively low similarity to the registered image with a scanner.

  As shown in FIG. 14A, since the input image data IDa 'is actually image data of the registered image IDa, the calculated similarity is high (in this example, the similarity is 100%). Accordingly, in this case, it is determined that the input image data IDa ′ is image data of the registered image IDa, and execution of image processing on the input image data IDa ′ is prohibited.

  Further, as shown in FIG. 14B, the input image data IDb ′ is not actually image data of a registered image, but is calculated because it is data read from an image having a relatively high similarity to the registered image. The similarity is a relatively high value (85% in this example). For this reason, the calculated similarity is higher than the threshold value for similarity determination (80% in this example), and execution of image processing is prohibited even though it is not originally image data of a registered image. May occur.

  As shown in FIG. 14C, for the input image data IDc ', the calculated similarity is lower than the threshold value, and execution of image processing is permitted.

  On the other hand, in FIGS. 15A to 15A, the registered image IDa is registered as a registered image that prohibits execution of image processing, and is registered as an exception registered image (registered image that permits execution of image processing). It is a graph which shows the result of having calculated the similarity of input image data IDa ', IDb', and IDc 'with respect to registration image IDa when image IDb is registered.

As shown in FIG. 15A, since the input image data IDa ′ is actually image data of the registered image IDa, the similarity to the registered image IDa is the highest (similarity 100% in the example of this figure). Therefore, in this case, it is determined that the input image data IDa ′ is image data of the registered image IDa, and execution of image processing on the input image data IDa ′ is prohibited.

  As shown in FIG. 15B, since the input image data IDb 'is actually image data of the registered image IDb, the similarity to the registered image IDb is the highest (similarity 100% in the example of this figure). Since the registered image IDb and the registered image IDa originally have a relatively high similarity, the similarity of the input image data IDb ′ to the registered image IDa is also relatively high (85% in the example shown in this figure). However, since the input image data IDb ′ is data obtained by reading the registered image IDb, the similarity to the registered image IDa does not become higher than the similarity to the registered image IDb. Therefore, it is determined that the input image data IDb 'is image data of the registered image IDb, and execution of image processing is permitted.

  As shown in FIG. 15C, for the input image data IDc ', the calculated similarity is lower than the threshold value, and execution of image processing is permitted.

  Therefore, for example, an input that is erroneously determined by the administrator as image data of a registered image although it is not image data of a registered image that originally prohibits execution of image processing as shown in FIG. By registering the image data (input image data IDb ′) as an exception registration image, it is possible to execute image processing on the input image data thereafter. That is, it is possible to prevent the execution of image processing from being prohibited or restricted due to erroneous determination.

  In the example of FIG. 15B, both the similarity (100%) for the registered image IDb and the similarity (85%) for the registered image IDa exceed the similarity determination threshold (80%). In this embodiment, when the similarity to a plurality of registered images exceeds the similarity determination threshold, the registered image having the highest similarity is registered as an exception based on the registered image having the highest similarity. Whether or not execution of image processing is prohibited or restricted is determined based on whether the image is an image. However, the present invention is not limited to this. For example, when the similarity to a registered image that prohibits or restricts execution of image processing is equal to or higher than a second threshold (for example, 90%) higher than the threshold for similarity determination, or execution of image processing is performed. When the ratio of the similarity to the maximum value of the registered image that permits the execution of the image processing of the similarity to the registration image to be prohibited or restricted is a predetermined value (for example, 90%) or more, or the registered image that permits the execution of the image processing Registration that prohibits or restricts execution of image processing, for example, when the difference between the maximum value of similarity to the image and the similarity to registered images that prohibit or restrict execution of image processing is less than a predetermined value (for example, 5%). Execution of image processing is prohibited or restricted even when the similarity to images is lower than the similarity to registered images that allow execution of image processing. It may be. Thereby, it is possible to improve the security of a registered image that prohibits or restricts execution of image processing.

In this embodiment, even if the similarity to a registered image that prohibits or restricts execution of image processing is equal to or higher than a threshold for similarity determination, the similarity to an exception registered image that permits execution of image processing is higher than the similarity. If the degree is greater, all image processing executions are permitted, but the present invention is not limited to this. For example, when the similarity to a registered image that prohibits or restricts execution of image processing is equal to or greater than a threshold for similarity determination, and the similarity to an exception registered image that permits execution of image processing is greater than this similarity May be set to allow execution of image processing (for example, copying, printing, filing, image data correction, and editing are permitted, but the rest of the processing is permitted. For example, set the processing not to allow execution). In this case, for example, the exception registration image list 103 stores the ID of the exception registration image in association with the information indicating the content permitted to execute the image processing, and the control unit 7 performs the requested image processing. Based on the contents and the information stored in association with the corresponding exception registered image, it may be determined whether the execution of the image processing should be permitted or prohibited.

  In this embodiment, if it is determined that there is similarity to the registered image, the execution of the process is prohibited in principle, and if this registered image is an exception registered image, the execution of the process is exceptionally permitted. The configuration to be described has been described. However, the present invention is not limited to this. For example, when it is determined that the registered image is similar, the execution of the process is permitted in principle (if the similarity is not similar, the execution of the process is prohibited). In the case of a registered image, it may be configured to prohibit or restrict the execution of processing exceptionally.

  In the present embodiment, the case where the present invention is applied to the digital color multifunction peripheral 1 has been described. However, the application target of the present invention is not limited to this. For example, the present invention may be applied to a monochrome multifunction device. Further, the present invention is not limited to a multifunction machine, and may be applied to, for example, a single facsimile communication apparatus, a copying machine, an image reading apparatus, or the like.

  FIG. 16 is a block diagram showing a configuration example when the present invention is applied to a flatbed scanner (image reading apparatus, image processing apparatus) 1 ′.

  As shown in this figure, the flatbed scanner 1 'includes a color image input device 2 and a color image processing device 3'. The color image processing device 3 ′ includes an A / D conversion unit 11, a shading correction unit 12, a document collation processing unit 13, a control unit 7 (not shown in FIG. 16), and a memory 8 (not shown in FIG. 16). The color image input device 2 is connected to the image reading device 1 ′ as a whole. The functions of the A / D conversion unit 11, the shading correction unit 12, the document collation processing unit 13, the control unit 7, and the memory 8 in the color image input device (image reading unit) 2 are substantially the same as those of the digital color multifunction peripheral 1 described above. Since it is the same, description is abbreviate | omitted here.

  In the present embodiment, the administrator folder 8A is provided in the digital color multifunction peripheral 1. However, the present invention is not limited to this. For example, an external device (server apparatus) connected to the digital color multifunction peripheral 1 so as to be communicable is used. Etc.) may be provided with an administrator folder 8A.

  17 shows a server device 50 having an administrator folder 8A, and multifunction devices (MFPs) A, B,..., Printers A, B,. .. Configuration of image processing system 100 including facsimile machines A, B,..., Computers A, B,..., Digital cameras A, B,. It is explanatory drawing which shows. The configuration of the image processing system 100 is not limited to this. For example, the server device 50, a multifunction device, a printer (image forming device), a facsimile, a computer, a digital camera (image reading device), a scanner (image reading device). ) May be included.

The scanner includes a document table, an optical scanning unit, a CCD (charge coupled device), etc., and scans the document image placed on the document table by the optical scanning unit to read the document image and generate image data. To do. The digital camera includes an imaging lens, a CCD, and the like (image input device), and shoots a document image, a person, a landscape, and the like to generate image data. The scanner and the digital camera may have a function of performing predetermined image processing (for example, various correction processes) in order to appropriately reproduce the image. The printer prints an image based on image data generated by a computer, a scanner, and a digital camera on a sheet (recording paper). Further, the facsimile performs processing such as binarization processing, resolution conversion processing, and rotation on the image data read from the image input device, and transmits the image data compressed to a predetermined format to the other party. Then, the image data transmitted from the other party is decompressed, subjected to rotation processing, resolution conversion processing, and halftone processing according to the performance of the image output apparatus, and output as a page unit image. The multifunction machine has at least two of a scanner function, a facsimile transmission function, and a printing function (copying function, printer function). The computer edits image data read by a scanner or a digital camera, or creates a document using application software.

  Each of the above devices connected to the server device 50 via the network includes a control unit 7 and a document collation processing unit 13. As a result of the similarity determination, when it is determined that there is similarity (the input image data is the image data of the registered image), the control unit 7 transmits the input image data, the device ID, etc. (the input image data is transmitted to the server device 50). Information for specifying the device) is transmitted to the server device 50, and the control unit (not shown) of the server device 50 stores the received information in the administrator folder 8A provided in the server device 50. ing. If it is determined that there is a similarity, and the user wishes to continue the process and, as a result of the user authentication process, permits the process to be continued, the control unit 7 logs the input image data and The server ID 50 is transmitted to the server device 50, and the control unit (not shown) of the server device 50 stores the received information in the administrator folder 8A provided in the server device 50.

  In the present embodiment, the similarity determination process is performed by the document collation processing unit 13 provided in the digital color multifunction peripheral 1, but the present invention is not limited to this. For example, some or all of the functions of the control unit 7 and the document collation processing unit 13 may be executed by an external device that is communicably connected to the digital color multifunction peripheral 1.

  FIG. 18 is a block diagram illustrating a configuration example when the server device 50 includes some of the functions of the control unit 7 and the document matching processing unit 13.

  As shown in FIG. 18, the color image processing apparatus 3 of the digital color multifunction peripheral 1 controls the operation of the document collation processing unit 13a including the feature point calculation unit 31 and the feature amount calculation unit 32 and the document collation processing unit 13a. Control unit 7a, a memory 8a for storing information necessary for processing of the document collation processing unit 13a, and a communication device 5 for communicating with an external device. The server device 50 includes a communication device 51 that communicates with an external device, a document collation processing unit 13b that includes a voting processing unit 33, a similarity determination processing unit 34, and a registration processing unit 35, and a document collation process. A control unit 7b for controlling the unit 13b, and a memory 8b for storing information necessary for processing of the document collation processing unit 13b. When data transmission / reception is required between each functional block provided in the digital color multifunction peripheral 1 and each functional block provided in the server device 50, the control unit 7a and the control unit 7b are connected to the communication devices 5 and 51, respectively. To transmit and receive data as appropriate. Other functions are the same as those described above.

  In the example of FIG. 18, all of the feature amount calculation unit 32 (the feature point extraction unit 32 a, the invariant calculation unit 32 b, and the hash value calculation unit 32 c) are provided in the digital color multifunction peripheral 1, but this is not limitative. Instead, for example, as shown in FIG. 19, the feature point extraction unit 32 a and the invariant calculation unit 32 b may be provided in the digital color multifunction peripheral 1, while the hash value calculation unit 32 c may be provided in the server device 50.

Each unit of the feature amount calculation unit 32 is provided in the server device 50, and data related to the feature points calculated by the feature point calculation unit 31 is transmitted from the digital color multifunction peripheral 1 to the server device 50, and is provided in the server device 50. The feature amount calculation unit 32 may calculate a hash value based on the hash table 102 stored in the memory 8b and the received feature point data. Further, each of the feature point calculation unit 31 and the feature amount calculation unit 32 is provided in the server device 50, and the input image data is transmitted from the digital color multifunction peripheral 1 to the server device 50.
The feature point calculation unit 31 and the feature amount calculation unit 32 provided in the server device 50 calculate hash values based on the input image data received from the server device 50 and the hash table 102 stored in the memory 8b. Also good.

  Further, in the above description, an example in which the similarity determination process is performed has been described. However, in the case of performing the registration process, the registration processing unit 35 provided in the server device 50 has received from the digital color multifunction peripheral 1. The document ID and the hash value (or the hash value calculated by the hash value calculation unit 32c provided in the server device 50) may be registered in the hash table 102 provided in the memory 8b. Whether the similarity determination process or the registration process is performed is designated by the user of the digital color multifunction peripheral 1 via the operation panel 6, and a signal indicating which process is performed is transmitted to the server device 50. Alternatively, the registration process may be performed for the input image that the server device 50 has determined as not similar as a result of the similarity determination process.

  When the server device 50 includes the hash value calculation unit 32c, the hash value is calculated by using a method different from the method for calculating the hash value stored in the hash table 102 (using another hash function). The hash table 102 may be updated using a hash value. As a result, for example, an appropriate hash value referring to a feature value (invariant) according to the type of document image or the like can be registered (updated) in the hash table 102, and voting processing can be performed using it. The accuracy (similarity determination accuracy) can be improved.

  In this embodiment, when it is determined that there is similarity as a result of the similarity determination, the input image data is stored in the administrator folder 8A. In addition to this, for example, OCR (Optical Character Recognition) processing The character information extracted from the input image data may be stored. In this case, for example, the digital color multifunction peripheral 1 is provided with an OCR processing unit that extracts character information (text data) from the input image data, and the control unit 7 uses the administrator folder 8A for the text data extracted by the OCR processing unit. Can be stored in the.

[Embodiment 2]
Another embodiment of the present invention will be described. For convenience of explanation, members having the same functions as those explained in the embodiment are given the same reference numerals, and explanation thereof is omitted.

  FIG. 22 is a block diagram illustrating a schematic configuration of the document matching processing unit 13b provided in the digital color multifunction peripheral 1 according to the present embodiment. The digital color multifunction peripheral 1 according to the present embodiment has the same configuration as that of the digital color multifunction peripheral 1 according to the first embodiment except that a document collation processing unit 13b is provided instead of the document collation processing unit 13.

  As shown in FIG. 22, the document matching processing unit 13b includes a temporary registration information storage unit 9 and a registered data deleting unit 36 provided in the memory 8 in addition to the document matching processing unit 13 in the first embodiment. Yes.

  In the first embodiment, the similarity determination processing unit 34 calculates the number of votes obtained for each registered image based on the voting process result of the voting processing unit 33, and the number of votes obtained is equal to or greater than a threshold value and the number of votes obtained is the highest. It was determined that there was similarity to the image. However, there may occur a case where the similarity to the registered image cannot be accurately determined only by this determination method.

This point will be described in detail with a specific example. FIG. 23A is an explanatory diagram showing the voting result for the registered images A and B with respect to the matching target image α, the registered images A and B included in the input image data, and the matching target image α by the voting processing unit 33. . The verification target image α is the same image as the registered image B. FIG. 23B shows the comparison target image α ′, the registration images A ′ and B ′ included in the input image data, and the registration images A ′ and B ′ for the verification target image α ′ by the voting processing unit 33. It is explanatory drawing which shows a voting result. The collation target image α ′ is the same image as the registered image B ′.

  As shown in FIG. 23A, when the similarity between the registered images A and B is low, the same content portion in each of the registered images and the verification target image α is relatively small with respect to the entire image, and the different contents The part becomes relatively large. In this case, as shown in the voting result of FIG. 23A, even if the vote result for both registered images includes a vote due to noise, the difference in the number of votes for different content portions becomes large. Is relatively difficult to occur.

  On the other hand, as shown in FIG. 23B, when the similarity between the registered images A ′ and B ′ is high, the same content portion in each of the registered images and the verification target image α ′ is relatively relative to the entire image. More content and relatively less content. In this case, as shown in the voting result of FIG. 23B, the difference in the number of votes for different content portions is small. Therefore, if the vote result for both registered images includes a vote due to noise, an erroneous determination is made. Prone to occur. Note that it is difficult to identify whether the difference in the total number of votes of both registered images is a difference due to noise or a difference based on a difference in actual image contents.

  Therefore, in the present embodiment, when registering a restricted registration image or a permission registration image, first, a temporary registration of an image to be newly registered is performed, and then an image to be newly registered is read again by the color image reading device 2. Then, the similarity determination between the registered image and the provisionally registered pixel is performed. If the difference between the similarity to the registered image and the similarity to the temporarily registered image is greater than or equal to a preset threshold value, the provisionally registered image is registered. It is determined that identification is impossible and registration of the temporarily registered image is not performed.

  The temporary registration information storage unit 9 is a memory that stores the ID (temporary registration ID; temporary registration identifier) of the image to be temporarily registered and a feature amount in association with each other. Note that the feature amount of the temporarily registered image may be stored in the hash table 102 in association with the temporary registration ID, or in a table (not shown) different from the hash table 102 in association with the temporary registration ID. May be stored.

  When the registration data deletion unit 36 determines that the temporarily registered image cannot be identified, the registration data deletion unit 36 deletes the temporary registration ID and the feature amount of the image from the temporary registration information storage unit 9. When the feature amount is stored in the hash table 102 or other table, the temporary registration ID is deleted from the temporary registration information storage unit 9 and the feature stored in the hash table 102 or other table is stored. Delete the amount.

  FIG. 23 is a flowchart showing the flow of processing in the document matching processing unit 13b.

  First, as in the first embodiment (see FIG. 12), the control unit 7 acquires input image data and a processing request (instruction input) input from the user via the operation panel 6 or the communication device 5 (S1). , S2), it is determined whether the process requested by the process request is a registration process (S3). And when it is not a registration process, the process of S11-S18 in FIG. 12 is performed.

On the other hand, when it is a registration process, the control part 7 performs the authentication process whether the user who has requested | required the process is an administrator registered into the administrator information storage part 101 (S21). For example, the control unit 7 acquires user information (user ID, password, etc.) input by the user via the operation panel 6 or the communication device 5 and is registered in the acquired user information and administrator information storage unit 101. Authentication processing is performed by collating with administrator information (administrator user information).

  Then, it is determined whether or not the authentication is successful (S22). If it is determined that the authentication is unsuccessful, the process is terminated.

  On the other hand, when the authentication process is successful in S21, the control unit 7 controls each unit of the document matching processing unit 13, and performs the feature point calculation process (S23) and the feature amount calculation process (S24) for the input data acquired in S1. The temporary registration ID and the feature amount of the original are stored in the temporary registration ID storage unit 9 (S25).

  Next, image data obtained by re-reading the document to be temporarily registered with the color image input device 2 is acquired, and the feature points and feature amounts of the re-read image are calculated and registered in the hash table 102. A voting process (S26) and a similarity determination process (S27) are performed on the registered image and the temporarily registered image stored in the temporarily registered information storage unit 9.

  Then, as a result of the similarity determination process, it is determined whether or not there are a plurality of documents determined to have similarity (S28). Here, when it is determined that there are not a plurality of originals determined to have similarities, the control unit 7 performs processing after S31 described later.

  On the other hand, if it is determined that there are a plurality of documents determined to be similar, the control unit 7 calculates a difference in similarity for each document determined to be similar (S29), and the difference is determined in advance. It is determined whether or not the threshold value is exceeded (S30). In the present embodiment, the above threshold is set to 5% of the similarity of the document having the largest number of votes.

  When it is determined that there are not a plurality of documents determined to have similarity in S28, and when it is determined in S30 that the difference is greater than or equal to a threshold value, the control unit 7 identifies the temporarily registered document. If it is determined that it is possible, the registration processing unit 35 is controlled to formally register the temporary registration document in the hash table 102 (S31). For example, when the temporary registration ID and the feature amount are stored in the temporary registration information storage unit 9, the feature amount and the formal registration ID may be associated with each other and registered in the hash table 102. When the temporary registration ID and the feature amount are stored in the hash table 102 in association with each other, the stored temporary registration ID may be changed to an ID for formal registration. Further, after the formal registration to the hash table 102, the control unit 7 may control the registration data deletion unit 36 to delete the information stored in the temporary registration information storage unit 9.

  Thereafter, the control unit 7 determines whether the process requested by the process request is a registration process for a registered image (an image for which execution of the process is prohibited or restricted) or an exception registration image (an image for which execution of the process is permitted). It is determined whether it is a registration process (S32). If it is not an exception registration image registration process, the control unit 7 ends the process. On the other hand, in the case of the exception registration image registration process, the control unit 7 controls the registration processing unit 35 to register the ID of the image in the exception registration image list 103 (S33), and ends the process.

  On the other hand, if it is determined in S30 that the difference is less than the threshold value, the control unit 7 determines that the temporary registration document cannot be identified, and displays on the display unit of the operation panel 6 that registration is not possible. (S34), the registration data deletion unit 36 is controlled to delete the information stored in the temporary registration information storage unit 9, and the process ends.

When it is determined that there are a plurality of documents determined to have similarities in S28, it is further determined whether or not both the permitted registration image and the restricted registration image are included in the plurality of documents. May be processed after S29, while only one of them may be processed after S31.

  In each of the above embodiments, each unit (each block) constituting the document collation processing unit and the control unit provided in the digital color multifunction peripheral 1 and / or the server device 50 is realized by software using a processor such as a CPU. The That is, the digital color multifunction peripheral 1 and / or the server device 50 develops a central processing unit (CPU) that executes instructions of a control program that realizes each function, a read only memory (ROM) that stores the program, and the program. A random access memory (RAM), and a storage device (recording medium) such as a memory for storing the program and various data. An object of the present invention is to read the program code (execution format program, intermediate code program, source program) of the control program of the digital color multifunction peripheral 1 and / or the server device 50, which is software that realizes the functions described above, with a computer. This is achieved by supplying the recording medium recorded as possible to the digital color multifunction peripheral 1 and / or the server device 50, and reading out and executing the program code recorded on the recording medium by the computer (or CPU or MPU). .

  Examples of the recording medium include tapes such as magnetic tapes and cassette tapes, magnetic disks such as floppy (registered trademark) disks / hard disks, and disks including optical disks such as CD-ROM / MO / MD / DVD / CD-R. Card system such as IC card, IC card (including memory card) / optical card, or semiconductor memory system such as mask ROM / EPROM / EEPROM / flash ROM.

  Further, the digital color multifunction peripheral 1 and / or the server device 50 may be configured to be connectable to a communication network, and the program code may be supplied via the communication network. The communication network is not particularly limited. For example, the Internet, intranet, extranet, LAN, ISDN, VAN, CATV communication network, virtual private network, telephone line network, mobile communication network, satellite communication. A net or the like is available. Also, the transmission medium constituting the communication network is not particularly limited. For example, even in the case of wired such as IEEE 1394, USB, power line carrier, cable TV line, telephone line, ADSL line, etc., infrared rays such as IrDA and remote control, Bluetooth ( (Registered trademark), 802.11 wireless, HDR, mobile phone network, satellite line, terrestrial digital network, and the like can also be used. The present invention can also be realized in the form of a computer data signal embedded in a carrier wave in which the program code is embodied by electronic transmission.

  In addition, each block of the digital color multifunction peripheral 1 and / or the server device 50 is not limited to being realized using software, and may be configured by hardware logic, and performs a part of the processing. A combination of hardware and arithmetic means for executing software for controlling the hardware and performing the remaining processing may be used.

  The computer system of the present invention includes an image input device such as a flatbed scanner, a film scanner, and a digital camera, a computer in which various processes such as the similarity calculation process and the similarity determination process are performed by loading a predetermined program, You may comprise by image formation prosecution, such as an image display apparatus, such as a CRT display and a liquid crystal display which displays the process result of a computer, and a printer which outputs the process result of a computer on paper. Furthermore, a network card, a modem, or the like as communication means for connecting to a server or the like via a network may be provided.

The present invention is not limited to the above-described embodiments, and various modifications can be made within the scope shown in the claims. That is, embodiments obtained by combining technical means disclosed in different embodiments and technical means appropriately modified within the scope of the claims are also included in the technical scope of the present invention.

  The present invention can be applied to an image processing apparatus and an image processing method that determine the degree of similarity between input image data and a registered image registered in advance and perform control according to the determination result.

It is a block diagram which shows schematic structure of the document collation process part with which the image processing apparatus concerning one Embodiment of this invention is equipped. 1 is a block diagram illustrating a schematic configuration of an image processing apparatus according to an embodiment of the present invention. It is a block diagram which shows schematic structure of the feature point calculation part with which the image processing apparatus shown in FIG. 2 is equipped. It is explanatory drawing which shows an example of the filter coefficient of the mixing filter with which the MTF process part of the image processing apparatus shown in FIG. 2 is provided. FIG. 3 is an explanatory diagram illustrating an example of a connected region extracted from input image data by a feature point calculation unit of the image processing apparatus illustrated in FIG. 2 and a center of gravity of the connected region. It is explanatory drawing which shows an example of each gravity center (feature point) of the some connection area | region extracted from the character string contained in input image data by the feature point calculation part of the image processing apparatus shown in FIG. FIG. 3 is an explanatory diagram illustrating an example of a feature point of interest and peripheral feature points extracted when a feature amount is calculated by a feature amount calculation unit of the image processing apparatus illustrated in FIG. 2. (A)-(c) is explanatory drawing which shows an example of the combination of the attention feature point and surrounding feature point which are extracted when the feature-value calculation part of the image processing apparatus shown in FIG. 2 calculates a feature-value. . (A)-(c) is explanatory drawing which shows an example of the combination of the attention feature point and surrounding feature point which are extracted when the feature-value calculation part of the image processing apparatus shown in FIG. 2 calculates a feature-value. . (A) And (b) is explanatory drawing which shows an example of the index showing the hash value and input image data about each feature point registered into a hash table in the image processing apparatus shown in FIG. 3 is a graph showing an example of the number of votes for each registered image in the voting processing unit of the image processing apparatus shown in FIG. 2. It is a flowchart which shows the flow of a process in the image processing apparatus shown in FIG. FIG. 3 is an explanatory diagram illustrating an example of an exception registration image list used in the image processing apparatus illustrated in FIG. 2. (A)-(c) is a graph which shows an example of the similarity calculation result in the image processing apparatus shown in FIG. (A)-(c) is a graph which shows an example of the similarity calculation result in the image processing apparatus shown in FIG. It is a block diagram which shows the modification of the image processing apparatus concerning one Embodiment of this invention. It is explanatory drawing which shows the structure of the image processing system concerning one Embodiment of this invention. 1 is a block diagram illustrating a configuration example of an image processing system according to an embodiment of the present invention. It is a block diagram which shows the other structural example of the image processing system concerning one Embodiment of this invention. (A)-(d) is description which shows an example of the combination of the attention feature point and peripheral feature point which are extracted when the feature-value calculation part of the image processing apparatus concerning one Embodiment of this invention calculates a feature-value. FIG. (A)-(d) is description which shows an example of the combination of the attention feature point and peripheral feature point which are extracted when the feature-value calculation part of the image processing apparatus concerning one Embodiment of this invention calculates a feature-value. FIG. It is a block diagram which shows schematic structure of the document collation process part with which the image processing apparatus concerning other embodiment of this invention is equipped. (A) And (b) is explanatory drawing which shows an example of the collation target image which is collated in the document collation process part shown in FIG. 1, a registered image, and a voting result. It is a flowchart which shows the flow of a process in the document collation process part shown in FIG.

Explanation of symbols

1 Digital color MFP (image processing device, image forming device, image reading device, image processing device)
1 'Flatbed scanner (image processing device, image reading device)
2 Color image input device (input data acquisition unit, image input device)
3,3 'color image processing device (image processing device)
4 color image output device (image output unit)
5 Communication devices (input data acquisition unit, transmission device)
6 Operation panel (Processing input section)
7, 7a, 7b Control unit 8, 8a, 8b Memory (storage unit)
8A Administrator folder 9 Temporary registration information storage unit 13, 13a, 13b Document collation processing unit (similarity calculation unit)
31 feature point calculation unit 32 feature amount calculation unit 32a feature point extraction unit 32b invariant calculation unit 32c hash value calculation unit 33 voting processing unit (similarity calculation unit)
34 Similarity determination processing unit 35 Registration processing unit 36 Registration data deletion unit 50 Server apparatus 100 Image processing system 101 Administrator information storage unit 102 Hash table 103 Exception registered image list (identification information)

Claims (13)

An input data acquisition unit that acquires input image data, a feature amount extraction unit that extracts the feature amount of the input image data, a storage unit that stores the feature amount of the registered image, and a registered image from an external device that is communicably connected At least one of the registered image acquisition units that acquire the feature amount of the input image, the similarity calculation unit that compares the feature amount of the input image data with the feature amount of the registered image, and calculates the similarity of both images, and the similarity An image processing apparatus comprising: a control unit that determines whether or not execution of image processing on the input image data is prohibited or restricted depending on whether the degree is equal to or greater than a predetermined threshold value;
The registration image includes a permission registration image that is a registration image that permits execution of image processing, and a restriction registration image that is a registration image that prohibits or restricts execution of image processing.
An identification information acquisition unit that acquires identification information for identifying the permission registration image and the restriction registration image from the storage unit or the external device;
When the maximum value of the similarity calculated by the similarity calculation unit is equal to or greater than the threshold value, and when the registered image having the maximum similarity is the permitted registered image, the control unit is configured to generate an image corresponding to the input image data. An image processing apparatus that permits execution of processing and prohibits or restricts execution of image processing on the input image data when a registered image having a maximum similarity is a restricted registered image. An input data acquisition unit that acquires input image data, a feature amount extraction unit that extracts a feature amount of the input image data, a storage unit that stores a feature amount of a restricted registration image that prohibits or restricts execution of image processing, and communication Compare at least one of the registered image acquisition units that acquire the feature quantity of the restricted registered image from an external device that can be connected, and compare the feature quantity of the input image data with the feature quantity of the restricted registered image. An image processing apparatus comprising: a similarity calculation unit that calculates a degree; and a control unit that prohibits or restricts execution of image processing on the input image data when the similarity is equal to or greater than a predetermined threshold. And
A feature amount of a permission registration image that permits execution of image processing and identification information for identifying the restriction registration image and the permission registration image are stored in the storage unit or a second storage unit provided in the external device. A registration processing unit for storing
The similarity calculation unit calculates a similarity between the input image data and the restricted registration image, and a similarity between the input image data and the permission registration image;
When the similarity to the restricted registration image is equal to or greater than the threshold value and the similarity to the permitted registration image is greater than the similarity to the restricted registration image, the control unit An image processing apparatus that permits execution of image processing on a computer. An input data acquisition unit that acquires input image data, a feature amount extraction unit that extracts a feature amount of the input image data, a storage unit that stores a feature amount of a permission registration image that permits execution of image processing, and communication Compare at least one of the registered image acquisition units that acquire the feature amount of the permission registration image from the connected external device, the feature amount of the input image data and the feature amount of the permission registration image, and determine the similarity between both images A similarity calculation unit to calculate, and an image processing device that permits execution of image processing on the input image data when the similarity is equal to or greater than a predetermined threshold,
A second memory provided in the storage unit or the external device includes a feature amount of a restricted registration image that prohibits or restricts execution of image processing, and identification information for identifying the permitted registration image and the restricted registration image. A registration processing unit to be stored in the unit,
The similarity calculation unit calculates a similarity between the input image data and the permission registration image, and a similarity between the input image data and the restricted registration image,
If the similarity to the permission registration image is equal to or greater than the threshold and the similarity to the restriction registration image is greater than the similarity to the permission registration image, the control unit An image processing apparatus that prohibits or restricts execution of image processing on the image processing apparatus.   The control unit, when the registered image having the maximum similarity calculated by the similarity calculating unit is a permitted registered image, and the similarity to the restricted registered image is equal to or greater than a second threshold greater than the threshold, or Execution of image processing on the input image data is prohibited when the similarity to the restricted registered image is equal to or greater than the second threshold and the difference between the maximum value and the similarity to the restricted registered image is less than or equal to a predetermined value. The image processing apparatus according to claim 1, wherein the image processing apparatus is limited. A provisional registration information storage unit that stores information about a registration target image that is an image for which registration is requested;
When the control unit registers the registration target image as the registration image,
A process of assigning a temporary registration identifier to the registration target image and storing the temporary registration identifier and a feature amount extracted from the registration target image in the temporary registration information storage unit;
A reread image obtained by rereading the document corresponding to the registration target image by the image reading unit is acquired, and stored in the temporary registration information storage unit based on the feature amount extracted from the reread image. Processing for calculating similarity between the registration target image and a registered image that has already been registered in the storage unit or the second storage unit, and determining whether or not there are a plurality of images having a similarity greater than or equal to a predetermined threshold When,
A process for officially registering the registration target image as a registered image in the storage unit or the second storage unit by the registration processing unit when it is determined that there are not plural;
When it is determined that there are a plurality of images, a difference in the similarity between the plurality of images is calculated. If the difference is greater than or equal to a predetermined value, the registration processing unit stores the registration target image in the storage unit or the second image. A process for officially registering as a registered image in the storage unit, and performing processing for prohibiting formal registration of the registration target image in the storage unit or the second storage unit if the registered image is less than a predetermined value. The image processing apparatus according to claim 1.   6. A registration data deletion unit that deletes information about the registration target image stored in the temporary registration information storage unit when the difference is less than a predetermined value. An image processing apparatus according to 1.   An image forming apparatus comprising: the image processing apparatus according to claim 1; and an image output unit that forms an image corresponding to input image data on a recording material.   An image transmission apparatus comprising: the image processing apparatus according to claim 1; and a transmission apparatus that transmits input image data to another apparatus connected to be communicable. An image input device that reads a document image and obtains input image data;
An image reading apparatus comprising: the image processing apparatus according to claim 1. Input data acquisition step for acquiring input image data, feature amount extraction step for extracting feature amount of input image data, registration data acquisition step for acquiring feature amount of registered image, feature amount of input image data and registered image A similarity calculation step of calculating the similarity between the two images by comparing the feature quantities of the two images, and execution of image processing on the input image data depending on whether the similarity is equal to or greater than a predetermined threshold. An image processing method including a processing restriction step for determining whether to prohibit or restrict,
The registration image includes a permission registration image that is a registration image that permits execution of image processing, and a restriction registration image that is a registration image that prohibits or restricts execution of image processing.
Including an identification information acquisition step of acquiring identification information for identifying a permission registration image and a restriction registration image,
In the processing restriction step, when the maximum value of the similarity calculated in the similarity calculation step is equal to or greater than the threshold value, and when the registered image having the maximum similarity is the permitted registered image, the input image data An image processing method, wherein execution of image processing is permitted, and execution of image processing on the input image data is prohibited or restricted when a registered image having a maximum similarity is a restricted registered image. An image processing device and a server device communicably connected to the image processing device;
An input data acquisition unit that acquires input image data, a storage unit that stores a feature amount of a registered image, and a similarity that compares the feature amount of the input image data and the feature amount of the registered image to calculate the similarity between both images A degree calculation unit, and a control unit that determines whether to prohibit or restrict execution of image processing on the input image data according to whether the similarity is equal to or greater than a predetermined threshold value. An image processing system provided in a distributed manner in a device and the server device,
The registration image includes a permission registration image that is a registration image that permits execution of image processing, and a restriction registration image that is a registration image that prohibits or restricts execution of image processing.
An identification information acquisition unit that acquires identification information for identifying the permission registration image and the restriction registration image from the storage unit or the external device;
When the maximum value of the similarity calculated by the similarity calculation unit is equal to or greater than the threshold value and the registered image having the maximum similarity is the permitted registered image, the control unit is configured to input the input image. An image processing system that permits execution of image processing on data and prohibits or restricts execution of image processing on the input image data when a registered image having a maximum similarity is a restricted registered image .   A program for operating the image processing apparatus according to any one of claims 1 to 6, wherein the program causes a computer to function as each unit.   A computer-readable recording medium on which the program according to claim 12 is recorded.

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