JP2011182126A - Image processing apparatus, image forming apparatus, determination method, program and computer-readable storage medium - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an image processing apparatus for surely detecting a specific pattern for specifying a copy inhibited image from read image data without performing special adjustment. <P>SOLUTION: An image determining part 40 uses a specific color range that stipulates the range of colors of a specific pattern to determine the colors of pixels in image data as a determination object. A parameter calculation part 561 performs correction such that readings, which are the values (R, G, B, G-R, G-B, R-B) of color parameters in a reference chart 23 that have actually been read by an image reading part 1, approximate target values, which are the values of the color parameters in sample data 157. Then, a specific range determining part 562 calculates the specific color range by using corrected values after correcting the readings in the reference chart 23 using the corrected parameters. Thus, the specific color range corresponding to the read characteristics of each image processing apparatus is calculated and the specific pattern is surely detected. <P>COPYRIGHT: (C)2011,JPO&INPIT

Description

  The present invention relates to an image processing apparatus that reads an image from a recorded matter of an image such as a document, and more specifically, detects a specific pattern that specifies a print prohibited image included in a copy prohibited image such as a banknote from the read image. The present invention relates to an image processing apparatus and the like.

  With the development of image processing technology, an image can be optically read from an original such as a document, and the read image can be reproduced precisely. For example, a high-quality full-color copy can be created, and a high-quality image can be read and stored with a high-definition scanner.

  An image processing apparatus capable of precisely copying such an image has a function for preventing copying of an image (hereinafter referred to as a copy-prohibited image) that should be prohibited from printing or copying banknotes or securities. It has been. Specifically, the image processing apparatus stores a specific pattern that specifies a copy-prohibited image and determines whether or not the specific pattern can be detected from the read image. Then, when a specific pattern can be detected from the image, it is determined that the image is a copy-prohibited image, and a process for prohibiting the copy of the image is performed.

  The specific pattern has a color and a shape. An image of a color in the color area of the specific pattern is extracted and binarized to determine whether the shape is the same as the specific pattern.

  In recent years, with the progress of image processing technology, the importance of preventing duplication of copy-prohibited images has increased, and the types of copy-prohibited images have increased. On the other hand, there are a wide variety of types of originals used in the image processing apparatus, which are general images that can be duplicated, such as an image of an original printed with a seal resembling a banknote stamp, which is a specific pattern of banknotes. Nevertheless, images with colors and shapes that resemble duplication-prohibited images are increasing. For this reason, there is an increased possibility that a graphic that is not a specific pattern is erroneously detected as a specific pattern, and a general image is erroneously determined to be a copy-prohibited image.

  If a standard for detecting a specific pattern is set widely so that the specific pattern can be reliably detected, the possibility that a general image is erroneously determined to be a copy-prohibited image increases. On the other hand, when the reference is set narrowly, there is a high possibility that a copy-prohibited image will be missed. Therefore, in order to be able to reliably discriminate duplication prohibited images (specific images) while reducing the possibility of erroneous determination, it is required to appropriately set the discrimination reference data.

  In order to appropriately adjust the discrimination reference data, it is desirable to reset the data every time the optical system is changed. The case where the optical system is changed is, for example, when the CCD is changed to a cheaper manufacturer, when the color of the light source is changed, when the model is changed, and the optical system is changed. Further, it is desirable to set for each machine (device).

  However, since identification of specific images such as banknotes is a secret operation, only a specific operator can perform the adjustment operation of the machine, and automatic adjustment is necessary to adjust one machine at a time. It is important that the automatic adjustment not only can be set correctly in accordance with the characteristics of each machine, but also that the adjustment does not take time with the recent price reduction of machines.

  For example, Patent Literature 1 and Patent Literature 2 disclose techniques relating to detection of such a specific image. Japanese Patent Application Laid-Open No. 2004-133260 discloses that the determination accuracy of a specific document such as a banknote is improved by determining the specific document based on the type of image determined by the determination unit and the color distribution information of the image data. Has been. Patent Document 1 is effective in improving the detection rate of a specific document and preventing erroneous detection in which a general document that is not a specific document is detected as a specific document.

  In Patent Document 2, parameters that define a color space in which a specific image exists are stored in a storage unit, and input image data is processed using the parameters stored in the storage unit. Then, the processing data of the input image data is compared with the ideal processing data for the input image data, and based on the result of the comparison, the above parameters are set so that the processing data of the input image data matches the ideal processing data. It is disclosed that it is amended. Patent Document 2 is effective for facilitating adjustment of image processing (color area of a specific image) for each model.

JP-A-4-313166 JP 2003-333354 A

  However, the technique of Patent Document 1 does not automate the setting value of a specific color area for detection of a specific document. Moreover, there are the following two problems to adjust one by one at the time of machine production using the technique of Patent Document 2.

  The first problem is that an extra process is required because it is an operation that is necessary only for adjustment of detection of a specific image. The second problem is when the color patch chart for adjustment is adjusted by, for example, processing such as attaching vinyl to prevent contamination in the production department, or a malicious third party When the adjustment is performed by intentionally placing a color clear folder on the color patch chart, the specific image is not detected. In this case, it becomes possible to copy bills and the like.

  SUMMARY OF THE INVENTION The present invention has been made in view of the above problems, and its purpose is to ensure that a specific pattern for specifying a print-prohibited image included in the print-prohibited image is obtained from read image data without special adjustment. An object of the present invention is to provide an image processing apparatus that can be detected.

  In order to solve the above problems, the image processing apparatus of the present invention includes a reading unit that reads an original image in color and converts it into image data, and whether or not the image data includes a specific pattern that specifies copy prohibition. A determination unit configured to perform determination based on a specific color that is a color of the specific pattern and a shape of the specific pattern, and the determination unit performs the determination for each value of a plurality of color parameters included in the specific color. An image processing apparatus that determines whether a value of a plurality of color parameters included in a determination target color is included in a specific color range that defines a range that can be recognized as a color parameter included in the specific color, and has a density in advance A sample data storage unit that stores sample data generated as ideal read data of a reference chart including a plurality of color patches of which color is known; Correction parameter calculating means for calculating a correction parameter for correcting the color parameter value of the reference image data, which is the image data of the reference chart actually read by the reading means, so as to approach the value of the color parameter of the sample data; A parameter storage unit that stores the calculated correction parameter, a correction unit that corrects a value of a color parameter of the image data based on the calculated correction parameter, and the reference based on the calculated correction parameter And a specific color range determining unit that calculates the specific color range using the value of the color parameter after the image data is corrected by the correcting unit.

  According to the above configuration, the sample data generated as ideal read data of the reference chart including a plurality of color patches whose density is known in advance is stored in the sample data storage unit. Then, the correction parameter calculation unit calculates a correction parameter for correcting the color parameter value of the reference image actual data that is the data of the reference image read by the reading unit so as to approach the color parameter value of the sample data. . Then, the parameter storage unit stores the calculated correction parameter. Further, the correction means corrects the color parameter value of the image data based on the calculated correction parameter. Then, the specific color range determining means determines a specific color range that defines a range that can be recognized as a color parameter included in the specific color for each value of the plurality of color parameters included in the specific color as follows: decide. Based on the calculated correction parameter, the specific color range is calculated using the color parameter value after the color of the reference image data is corrected by the correction means. Then, a determination unit that determines whether or not the image data read by the reading unit includes a specific pattern that specifies copy prohibition is included in the calculated specific color range of the image data read by the reading unit. It is determined whether a plurality of color parameter values included in the color of the determination target (for example, pixel) are included.

  In this way, the specific color range is calculated using values that are actually corrected by individual image processing apparatuses, so that variations among image processing apparatuses, variations among models, and cost reduction of device parts in the middle. Can absorb all slight image changes caused by Thereby, the erroneous detection to the specific image of the general image very similar to the specific image can be prevented.

  Therefore, even if the image reading characteristics of the image processing apparatus differ from one image processing apparatus to another, a value that can reliably detect a specific pattern in a specific color range according to the image reading characteristics of each image processing apparatus. Can be adjusted. Thereby, the set value of the specific color range is optimally set for each image processing apparatus. Therefore, according to the above configuration, the specific pattern can be reliably detected from the read image data by non-special adjustment.

  Further, the correction parameter for correcting the color parameter value of the reference image data to be the same as the color parameter value of the sample data, the correction unit corrects the color of the input image data so that it is the same for all devices. In other words, it is calculated for color balance adjustment. Therefore, the calculation of the correction parameter can be used for color balance adjustment and setting of the specific color area, and since the specific color area can be set together with the color balance adjustment, no extra process is required.

  In the image processing apparatus according to the aspect of the invention, the specific color range determination unit may include a color parameter value after the reference image data is corrected by the correction unit based on the calculated correction parameter, and the sample data. The specific color range may be calculated by calculating a difference from the value of the color parameter and using different calculation formulas depending on whether the difference is within a predetermined allowable range or not.

  According to the above configuration, the specific color range determining unit determines the specific color range using different calculation formulas depending on whether the calculated difference is within the predetermined allowable range or not. To do. Therefore, even when the color balance adjustment is unsuccessful intentionally or accidentally, the specific color range can be set correctly.

  In the image processing apparatus of the present invention, the reading unit reads an image obtained by adding another function to the function of adjusting the color balance of the image processing apparatus as the reference image when the image processing apparatus is produced. May be.

  According to the above configuration, the reading unit reads an image obtained by adding another function to the color balance adjustment function as the reference image when the image processing apparatus is produced. Therefore, as another function, for example, when a function such as tilt adjustment of the document feeder is added, during the production of the image processing device, in addition to color balance adjustment and setting of a specific color range, Tilt adjustment can be performed, and the time required for adjustment can be shortened.

  In addition, after shipping, for example, a serviceman causes the reading unit to read a reference image having only a color balance adjustment function, so that even if there is no special jig, the color balance adjustment can be easily performed simultaneously with the specific color range. Can be set.

  In the image processing apparatus of the present invention, the allowable range may be determined in advance in consideration of the influence on the image quality when the image data is printed.

  According to the above configuration, since the allowable range is determined in consideration of the effect at the time of printing, the difference is not large due to intentional or accident at the time of adjustment, but the difference is really large. Even if the detection of a specific color is not successful due to the change, the color of the printed one is different from the actual one, so it is not used as a counterfeit bill or counterfeit gift certificate.

  In the image processing apparatus according to the aspect of the invention, the specific color range determination unit may determine a color parameter after the reference image data is corrected by the correction unit when the calculated difference is within the allowable range. If the calculated difference is outside the allowable range in a calculation formula using a value, the specific color range may be calculated using a calculation formula using a color parameter value of the sample data.

  When the calculated difference is within the allowable range, the color after correcting the color parameter value of the reference image data is close to the color of the sample data. Therefore, the corrected color parameter value is set to the specific color range. Can be used in the calculation formula. By using the corrected color parameter values, differences between individual samples with respect to actual sample data can be absorbed, so that the color extraction system can be improved, and this can improve the detection rate. If the calculated difference is outside the allowable range, the color parameter value of the reference image data after correction is separated from the color of the sample data. It should be used in the formula for calculating the specific color range.

  An image forming apparatus of the present invention includes any one of the above-described image processing apparatuses and a printing unit that performs printing based on image data.

  According to the above configuration, the printing unit determines whether or not the image data instructed to be printed is a specific image including a specific pattern that specifies printing prohibition. Based on the above, it is possible to determine whether printing is possible. Thereby, it is possible to prevent a situation where unauthorized printing is performed in the printing unit.

  According to the determination method of the present invention, a reading unit that reads an original image in color and converts it into image data, and a determination as to whether or not the image data includes a specific pattern that specifies copy prohibition is performed using the color of the specific pattern. A determination unit configured to perform determination based on a specific color and the shape of the specific pattern, wherein the determination unit recognizes each value of a plurality of color parameters included in the specific color as a color parameter included in the specific color. A method for determining the specific color range of an image processing apparatus for determining whether or not a specific color range that defines a range that can be included includes a plurality of color parameter values included in a color to be determined. A sample data storage step for storing sample data generated as ideal read data of a reference chart including a plurality of color patches of which color is known; A correction parameter calculating step for calculating a correction parameter for correcting the color parameter value of the reference image data, which is the image data of the reference chart actually read by the reading means, to approach the value of the color parameter of the sample data; A parameter storing step for storing the calculated correction parameter, a correction step for correcting a color parameter value of the image data based on the calculated correction parameter, and the reference based on the calculated correction parameter And a specific color range determining step of calculating the specific color range using the color parameter value after correcting the color parameter value of the image data.

  According to the above method, the same effect as that of the image processing apparatus can be obtained, and the specific color range can be adjusted to a value that can reliably detect the specific pattern according to the image reading characteristics of the individual image processing apparatuses. it can. Therefore, the set value of the specific color range is optimally set for each image processing apparatus.

  The image processing apparatus according to the present invention may be realized by a computer. In this case, the image processing apparatus is realized by the computer by causing the computer to operate as each unit in the image processing apparatus. A processing program and a computer-readable recording medium on which the image processing program is recorded also fall within the scope of the present invention.

  According to these configurations, the same operational effects as those of the image processing apparatus can be realized by causing the computer to read and execute the image processing program.

  As described above, the image processing apparatus of the present invention stores a sample data storage unit that stores sample data generated as ideal read data of a reference chart including a plurality of color patches whose densities are known in advance. And correction parameter calculation for calculating a correction parameter for correcting the color parameter value of the reference image data, which is the image data of the reference chart actually read by the reading unit, to approach the value of the color parameter of the sample data Means, a parameter storage unit that stores the calculated correction parameter, a correction unit that corrects the value of the color parameter of the image data based on the calculated correction parameter, and based on the calculated correction parameter The specific color range is calculated using the color parameter value after the reference image data is corrected by the correcting means. It includes a specific color range determination means for, the.

  According to the above configuration, the sample data generated as ideal read data of the reference chart including a plurality of color patches whose density is known in advance is stored in the sample data storage unit. Then, the correction parameter calculation unit calculates a correction parameter for correcting the color parameter value of the reference image actual data that is the data of the reference image read by the reading unit so as to approach the color parameter value of the sample data. . Then, the parameter storage unit stores the calculated correction parameter. Further, the correction means corrects the color parameter value of the image data based on the calculated correction parameter. Then, the specific color range determining means determines a specific color range that defines a range that can be recognized as a color parameter included in the specific color for each value of the plurality of color parameters included in the specific color as follows: decide. Based on the calculated correction parameter, the specific color range is calculated using the color parameter value after the color of the reference image data is corrected by the correction means. Then, a determination unit that determines whether or not the image data read by the reading unit includes a specific pattern that specifies copy prohibition is included in the calculated specific color range of the image data read by the reading unit. It is determined whether a plurality of color parameter values included in the color of the determination target (for example, pixel) are included.

  In this way, the specific color range is calculated using values that are actually corrected by individual image processing apparatuses, so that variations among image processing apparatuses, variations among models, and cost reduction of device parts in the middle. Can absorb all slight image changes caused by Thereby, the erroneous detection to the specific image of the general image very similar to the specific image can be prevented.

  Therefore, even if the image reading characteristics of the image processing apparatus differ from one image processing apparatus to another, a value that can reliably detect a specific pattern in a specific color range according to the image reading characteristics of each image processing apparatus. Can be adjusted. Thereby, the set value of the specific color range is optimally set for each image processing apparatus. Therefore, according to the above configuration, the specific pattern can be reliably detected from the read image data by non-special adjustment.

  Further, the correction parameter for correcting the color parameter value of the reference image data to be the same as the color parameter value of the sample data, the correction unit corrects the color of the input image data so that it is the same for all devices. In other words, it is calculated for color balance adjustment. Therefore, the calculation of the correction parameter can be used for color balance adjustment and setting of the specific color area, and since the specific color area can be set together with the color balance adjustment, no extra process is required.

It is a block diagram which shows the internal structure of the image process part of embodiment of this invention. It is a schematic diagram which shows the example of a reference | standard chart. It is a block diagram which shows the structure of the image processing apparatus of embodiment of this invention. It is a conceptual diagram which shows the outline | summary of the method of calculating a gamma correction value. It is a conceptual diagram which shows the outline | summary of the method of calculating the correction coefficient of color conversion correction. It is a block diagram which shows the internal structure of a specific color extraction part, and the input / output in an image determination part. It is a schematic diagram which shows the example of a printing prohibition image. It is a schematic diagram which shows the example of a specific pattern. It is a schematic diagram which shows the example of the partial pattern which comprises a part of specific pattern. It is a schematic diagram which shows the example of a specific pattern candidate image. It is a schematic diagram which shows the example of a determination window. (A), (b) is a schematic diagram which shows the example of a template. It is a chart which shows the example of a pixel number range. It is a schematic diagram which shows the example which divided | segmented the specific pattern candidate image into several area | region according to area | region setting data. It is a conceptual diagram which shows the example of the content of a specific color pixel number range. It is a schematic diagram which shows the example of the general pattern very similar to the specific pattern. FIG. 6 is an explanatory diagram of a reference chart that is also used for tilt adjustment of a document feeder and gamma adjustment of an image forming apparatus. It is a block diagram which shows the structure of the resolution conversion part shown in FIG. It is a schematic diagram which shows the example of the specific pattern with a base pattern. It is a schematic diagram which shows the structure of the image forming system provided with the image processing apparatus shown in FIG. It is a figure which shows the calculation formula for determining a specific color range. It is a figure which shows the calculation formula for determining a specific color range.

  Hereinafter, the present invention will be specifically described with reference to the drawings showing embodiments thereof.

(Image processing device)
FIG. 3 is a block diagram showing an electrical configuration of the image processing apparatus 100 according to the present embodiment. The image processing apparatus 100 includes a CPU 51 that performs calculations, a ROM 52 that stores programs necessary for the operation of the image processing apparatus 100, a RAM 53 that is a volatile memory that stores temporary data such as image data, and a display such as a liquid crystal panel. And an operation unit 55 such as a touch panel.

  The display unit 54 displays information necessary for the user to operate the image processing apparatus 100, and the operation unit 55 receives inputs such as various setting inputs by user operations. In the present embodiment, the display unit 54 and the operation unit 55 are an integrated operation panel. Using this operation panel, the user can perform operations for various processes and various settings.

  An image reading unit 1 is connected to the CPU 51, and an image processing unit 4 that performs image processing on the output of the image sensor 12 is connected to the image reading unit 1. A control unit 56 and a storage unit 57 are connected to the image processing unit 4.

  The control unit 56 includes a CPU that performs calculation, a RAM that stores information associated with the calculation, a ROM that stores programs necessary for the calculation, and the like, and controls image processing in the image processing unit 4.

  The storage unit 57 is configured by a nonvolatile memory or a hard disk. The storage unit 57 stores sample data as will be described later.

  The CPU 51 is connected to a transmission unit 58 that transmits image data subjected to image processing by the image processing unit 4 to an external device such as a personal computer.

  The CPU 51 comprehensively controls the operation of each unit in the image processing apparatus 100. However, the control unit 56 controls the image processing unit 4.

  Note that the image processing apparatus 100 is an image forming apparatus such as a copying apparatus, a facsimile apparatus, or a multi-function machine that further includes an image forming section that records an image formed based on image data on a recording sheet as shown in FIG. There may be. In addition, as shown in FIG. 20, the image processing apparatus 100 may be connected to computers 102 and 103 and a digital camera 104.

(Image reading unit and image processing unit)
FIG. 1 is a block diagram showing detailed internal configurations of the image reading unit 1 and the image processing unit 4. The image reading unit 1 includes a light source 11 that irradiates a document, an image sensor 12 that converts a document image into an electrical signal, an amplifier 13 that is connected to the image sensor 12, and an A / D conversion unit 14.

  The image processing unit 4 includes a shading correction unit 413, a gamma correction unit 414, and a color conversion unit 415.

  The RGB electrical signals are input from the image sensor 12 to the amplifier 13. The amplifier 13 amplifies the RGB electrical signals with a predetermined amplification factor, and inputs the amplified RGB electrical signals to the A / D converter 14. To do. The A / D converter 14 converts RGB analog electrical signals into RGB signals that are digital signals. The RGB signal is composed of lightness values of each color of RGB in each of a plurality of pixels constituting the read image. The brightness value of each color corresponds to the reflectance of light with respect to the image recorded on the original, that is, the density of each color included in the image on the original.

  The digital RGB signal converted by the A / D conversion unit 14 is input to the shading correction unit 413, and the shading correction unit 413 corrects the RGB signal by shading and inputs the corrected RGB signal to the gamma correction unit 414.

  The gamma correction unit 414 performs gamma correction on the RGB signal input from the shading correction unit 413 and inputs the corrected RGB signal to the color conversion unit 415. The color conversion unit 415 performs color conversion correction that corrects each RGB color according to the optical characteristics so that image data of almost the same color can be obtained from the same image in any image reading apparatus. By this color conversion correction, it is possible to absorb differences in luminance and color balance between the front and back surfaces due to variations in performance between devices or differences in light sources or light receiving elements.

  The color conversion unit 415 is connected to the page memory 427 via the memory control unit 416. The color conversion unit 415 temporarily inputs the RGB signal after color conversion correction to the page memory 427 via the memory control unit 425, and the page memory 427 temporarily stores image data composed of the RGB signals. Note that the memory control unit 416 and the page memory 427 may be configured as a part of the control unit 56.

  The color conversion unit 415 and the memory control unit 425 include an image determination unit (determination unit) 40 that determines whether the read image is a copy-prohibited image, and an image represented by image data including RGB signals after color conversion correction. Is connected to an image quality improvement processing unit 47 that performs image processing for improving the image quality of the image. The color conversion unit 415 inputs the RGB signal after the color conversion correction to the image determination unit 40 and the image quality improvement processing unit 47.

  The image determination unit 40 includes a resolution conversion unit 43, a color difference calculation unit 44, a specific color extraction unit 45, and a specific pattern detection unit 46.

  The resolution conversion unit 43 performs processing for converting the resolution of an image represented by image data composed of RGB signals. For example, the resolution conversion unit 43 converts 600 dpi image data to 100 dpi.

  The color difference calculation unit 44 calculates the color difference between G and R, the color difference between G and B, and the color difference between R and B from the image data after resolution conversion.

  Based on the RGB signal and the calculated color difference, the specific color extraction unit 45 determines whether the color of each pixel in the image is a specific color that is a color of a specific pattern that characterizes the copy prohibited image, A specific color pixel that is a pixel having a specific color is extracted from the read image. Then, binary image data in which the specific color pixel is distinguished from the other pixels is input to the specific pattern detection unit 46.

  The specific pattern detection unit 46 performs a process of detecting a specific pattern from the image represented by the binary image data, thereby determining whether or not the specific pattern is included in the read image. When the specific pattern can be detected from the image represented by the binary image data, the read image is a duplication prohibited image including the specific pattern. If the specific pattern cannot be detected, the read image does not include the specific pattern, and is not a copy-prohibited image. The specific pattern detection unit 46 outputs the determination result to the CPU 51.

  The image quality improvement processing unit 47 performs a region separation unit 471 that performs region separation processing, a scaling unit 472 that performs scaling processing, an MTF correction unit 473 that performs MTF correction processing, a background processing unit 474 that performs background processing, and a rotation processing. A rotation unit 475 and a register 476 for storing various parameters are provided. The image quality improvement processing unit 47 performs image processing for improving the image quality of the image represented by the image data on the image data composed of the RGB signals after color conversion correction, and outputs the image data after the image processing to the CPU 51. To do. If the determination result that the read image includes the specific pattern is output from the specific pattern detection unit 46, the image represented by the image data output from the image quality improvement processing unit 47 is a copy-prohibited image. Executes processing for prohibiting output of image data.

  The memory control unit 425 uses the image determination unit 40 and the image quality improvement processing unit 47 to process the image data stored in the page memory 427 after the processing of the image data input from the color conversion unit 415 is completed. Input to the processing unit 47. For this reason, after the image processing of the image read from one side of the document by the first reading unit (not shown) of the image reading unit 1 is completed, the image read by the second reading unit (not shown) of the image reading unit 1 from the other side of the document. Image processing is performed. By using the same image determination unit 40 and image quality improvement processing unit 47 over time, the waste of the size and cost of the image reading apparatus that occurs when two systems of the image determination unit and image quality improvement processing unit are provided. Can do.

(Gamma correction value)
The gamma correction value in the gamma correction performed by the gamma correction unit 414 is calculated in advance by the parameter calculation unit 561 of the control unit 56 based on the result of reading the reference chart. Here, the reference chart is obtained by recording an image colored with a plurality of colors, each of which has a predetermined color and density, to be used as a reference for image processing. Correspond.

  FIG. 2 is a schematic diagram illustrating an example of a reference chart. The reference chart is formed of a plurality of color patches arranged vertically and horizontally, and each color patch is colored with one color having a predetermined color and density. In the figure, an example is shown in which a color patch is recorded in which colors of B, G, R, BK1, BK2, C, M, and Y are colored with colors determined in 12 stages of density. In the figure, the density is indicated by a number from 1 to 12, and the larger the number, the higher the density. One of BK1 and BK2 is black in a color image, and the other is black in a monochrome image. Although each color patch is shown in monochrome in FIG. 2, each color patch is colored with each color in an actual reference chart. The reference chart shown in FIG. 2 is an example, and the configuration of the reference chart such as a configuration with a reduced number of colors may be other configurations.

  The storage unit 57 stores in advance sample data 571 generated as ideal read data, which is a sample of image data generated by actually reading the reference chart by the image reading unit 1. The sample data 571 is configured to include target values of RGB signals generated by reading each color patch in the reference data. The target value is an intensity value of the RGB signal generated for each color patch when the reference chart is read by an ideal image reading device, and is a value indicating an ideal color of each color patch included in the reference chart. is there. The sample data 571 is generated, for example, by reading the reference chart with a specific image reading apparatus as a standard. For example, the sample data 571 may be theoretically generated by a method such as simulating an ideal optical system state.

  The image reading unit 1 actually reads the reference chart, and the control unit 56 obtains a gamma correction value by comparing the image data generated by the reading with the sample data. The image sensor 12 of the image reading unit 1 receives reflected light from each color patch in the reference chart, and outputs electrical signals of RGB colors for each color patch. The shading correction unit 413 is an RGB signal for each color patch. To correct shading.

  The control unit 56 includes a parameter calculation unit 561, and calculates the read value of the RGB signal corresponding to each color patch by averaging the read value of the RGB signal in each color patch subjected to the shading correction. This read value is the intensity value of the EGB signal obtained by reading the image with the image reading unit 1, and the read value corresponding to the color patch is obtained by actually reading each color patch included in the reference chart with the image reading device. A value indicating the color. The control unit 56 reads the sample data 571 from the storage unit 57 and compares the target value of the RGB signal corresponding to each color patch with the read value of the RGB signal subjected to the shading correction by the shading correction unit 413, thereby obtaining the gamma. Calculate the correction value.

4A and 4B are conceptual diagrams showing an outline of a method for calculating a gamma correction value. Here, the target values of the RGB signals are R _target , G _target and B _target, and the read values of the RGB signals corresponding to the color patches are R _in , G _in and B _in . As shown in FIG. 4A, the control unit 56 associates the target values and read values of the R signals corresponding to the same color patch with each other, and arranges them in order of signal intensity. In the example shown in FIG. 4A, R _in (i) and R _target (i) are R signals corresponding to the same color patch. 4 (b) is a corresponding curve showing the correspondence between the read value R _in the target value R _target of the R signal, the corresponding curve is gamma for converting the read value R _in the target value R _target It is a curve.

Next, the control unit 56 linearly interpolates the reading value R _in and the target value R _target to correspond one-to-one with the arbitrary reading value of the R signal and the reading value according to the gamma curve shown in FIG. The correspondence relationship with the gamma correction value to be obtained is obtained, and a table representing the correspondence relationship between the obtained read value and the gamma correction value is generated. The read value included in this table is a value obtained by linear interpolation of the read value R _in generated for each color patch, and the gamma correction value is a value obtained by linear interpolation of the target value R _target for each color patch. In the generated table, the read value of the R signal and the gamma correction value are associated one-to-one, and by reading the gamma correction value associated with the read value from the table, an arbitrary read value is obtained. The target value can be converted into a gamma correction value obtained by linear interpolation.

Similarly, the control unit 56 generates a table representing a correspondence relationship between the read value of the G signal and the gamma correction value from the read value G _in of the G signal and the target value G _target , and reads the read value B of the B signal. _{From the in} and target value B _target , a process for generating a table representing the correspondence between the read value of the B signal and the gamma correction value is performed. The control unit 56 inputs the generated table for each of RGB to the gamma correction unit 414. The gamma correction unit 414 stores the input table in a non-volatile memory, and thereafter uses the stored table as an LUT (look-up table) to convert the read value of the RGB signal into a gamma correction value. By doing so, the gamma correction of the RGB signal is executed.

(Correction coefficient for color conversion correction)
Further, the control unit 56 causes the parameter calculation unit 561 to calculate a correction coefficient used for processing performed by the color conversion unit 415 based on the result of reading the reference chart. The control unit 56 compares the read value of the RGB signal gamma corrected by the gamma correction unit 414 with the target value of the RGB signal corresponding to each color patch of the reference chart, thereby performing color conversion executed by the color conversion unit 415. A correction coefficient for correction is calculated.

The color conversion correction process performed by the color conversion unit 415 is a process for converting the read value of the RGB signal to a value close to the target value so that the color of the read image is substantially the same as the color of the image indicated by the sample data. It is. The color conversion unit 415 converts RGB signals by matrix calculation. The ideal relationship between the RGB signal read values R _in , G _in and B _in and the RGB signal target values R _target , G _target and B _target is expressed by the following equation (1). In the formula (1), R ₁₁ , R ₁₂ , R ₁₃ , G ₁₁ , G ₁₂ , G ₁₃ , B ₁₁ , B ₁₂ , and B ₁₃ are correction coefficients for color conversion correction.

5A and 5B are conceptual diagrams showing an outline of a method for calculating a correction coefficient for color conversion correction. As shown in FIG. 5A, the control unit 56 associates the target value of the R signal corresponding to the same color patch with the read value of the RGB signal. Next, the control unit 56 substitutes the corresponding target value of the R signal and the read value of the RGB signal into the equation (1), thereby obtaining a relational expression between the target value of the R signal and the read value of the RGB signal. create. That is, the relational expression R _target (i) = R ₁₁ R _in (i) + R ₁₂ G _in (i) + R ₁₃ B _in (i) is created. When the number of color patches read from the reference chart is N, a relational expression of i = 1 to N is created. The control unit 56 calculates the coefficients R ₁₁ , R ₁₂ and R ₁₃ in the relational expression by executing the least square method using the created N relational expressions.

Similarly, as shown in FIG. 5B, the control unit 56 associates the target value of the G signal corresponding to the same color patch with the read value of the RGB signal so that i = 1 to N. By creating the formula G _target (i) = G ₁₁ R _in (i) + G ₁₂ G _in (i) + G ₁₃ B _in (i) and executing the least squares method using the created N relational expressions The coefficients G ₁₁ , G ₁₂ and G ₁₃ in the relational expression are calculated.

Similarly, as shown in FIG. 5C, the control unit 56 associates the target value of the B signal corresponding to the same color patch with the read value of the RGB signal so that i = 1 to N. B _target (i) = B ₁₁ R _in (i) + B ₁₂ G _in (i) + B ₁₃ B _in (i) is created, and the least squares method using the created N relational expressions is executed. Thus, the coefficients B ₁₁ , B ₁₂ and B ₁₃ in the relational expression are calculated.

Through the above processing, the control unit 56 calculates the correction coefficients R ₁₁ , R ₁₂ , R ₁₃ , G ₁₁ , G ₁₂ , G ₁₃ , B ₁₁ , B _12, and B ₁₃ for color conversion correction, and the calculated correction coefficients. Is input to the color conversion unit 415. The color conversion unit 415 stores the input correction coefficient, and thereafter uses the stored correction coefficient to perform a matrix operation represented by the following equation (2), thereby inputting the correction coefficient from the gamma correction unit 414. The color conversion correction is performed to convert the read values R _in , G _in and B _in of the RGB signals into R, G and B _{in the} equation (2).

  As described above, the correction coefficient (correction parameter) for the gamma correction value and the color conversion correction is a sample which is a sample of image data generated by reading the reference chart from the RGB signal obtained by actually reading the reference chart. Calculated to get as close to the data as possible. Characteristics such as optical characteristics when the image reading apparatus reads an image vary depending on the individual image reading apparatus. Therefore, even if the same image is read, the obtained RGB signals differ depending on the image reading device. However, the gamma correction value and the color conversion correction correction coefficient are calculated so that the read value read from the reference chart is as close as possible to the sample data, and the obtained RGB signal is subjected to gamma correction and color conversion correction. Therefore, it becomes as follows. That is, the corrected RGB signals are roughly the same value in any image reading apparatus if there is no change in design, such as a CCD that is an image sensor for reading or a xenon lamp that is a light source, in the same model. The corrected RGB signal obtained is almost equivalent to the RGB signal that can be generated by an ideal image reading apparatus.

  When the components such as CCD, xenon lamp, and lens change due to cost reduction, or when the optical system mounting accuracy or component lot changes, the value of the corrected RGB signal changes (reference chart) The corrected value of the read data of the color patch may not be substantially equal to the value of the sample data). In this case, if the specific color range for detecting the specific pattern is fixed, the detection rate of the specific pattern may decrease. However, according to the present invention, as will be described later, each value (R, G, B, G) of a plurality of color parameters included in a specific color that is a color of a specific pattern is determined from the RGB signal values of the corrected color patch. For each value of -R, GB, and RB, a specific color range that defines a range that can be recognized as a color parameter included in the specific color is calculated. Therefore, even if the adjustment is made for some reason, the detection rate can be kept from dropping even when the color balance is out of the reference.

  When the gamma correction value and the correction coefficient (correction parameter) for color conversion correction are stored in the storage unit 57, after adjusting the color balance and calculating the specific color range once at the time of production of the image processing apparatus 100, You don't have to do it every time.

(Specific color extraction unit)
The specific color extraction unit 45 will be described in detail. FIG. 6 is a block diagram showing an internal configuration of the specific color extraction unit 45 and input / output in the image determination unit 40.

  The RGB value after the color conversion correction is input from the color conversion unit 415 or the memory control unit 425 to the resolution conversion unit 43. The resolution conversion unit 43 performs processing for converting the resolution of an image represented by image data composed of RGB signal values. Specifically, the resolution conversion unit 43 reduces the pixels in the image by averaging the RGB signal values between adjacent pixels, or interpolates the RGB signal values between adjacent pixels. Process to increase. For example, if the resolution of the read image is too large, the amount of data becomes too large and it takes time for the image determination unit 40 to process. Therefore, the image determination unit 40 converts 600 dpi image data into 100 dpi. The resolution is converted to an appropriate resolution for processing.

  As shown in FIG. 18, the resolution conversion unit 43 includes a main scanning conversion unit 31, a sub-scanning conversion unit 32, a setting register 34, and a memory unit 33. The main scanning direction resolution conversion unit 31 converts the resolution in the scanning direction of the image data to a predetermined resolution. For example, 600 dpi RGB 8-bit (256 gradations) image data is converted to 100 dpi by taking an average value of 6 pixels.

  Similarly, the sub-scanning direction resolution conversion unit 32 converts the resolution of the image data in the sub-scanning direction to a predetermined resolution. Similar to the main scanning direction, for example, 600 dpi RGB 8-bit image data is converted to 100 dpi by taking an average value of 6 pixels. However, in the sub-scanning direction, the image may be scaled by setting the moving speed of the optical system, and the resolution conversion magnification is not constant. Therefore, in the sub-scanning direction, the resolution is scaled according to the magnification set in advance in the setting register 34 in order to set the resolution to 100 dpi. The memory unit 33 is a storage unit that temporarily stores data of a plurality of lines in the sub-scanning direction when the sub-scanning direction resolution conversion unit 32 performs the resolution conversion operation in the sub-scanning direction.

  The resolution conversion unit 43 inputs the RGB signal after the resolution conversion to the color difference calculation unit 462.

  The color difference calculation unit 44 receives the RGB signal value input from the resolution conversion unit 43, the (G−R) value obtained by subtracting the R signal value from the G signal value, and the B signal value from the G signal value. A value (GB) obtained by subtracting the value and a value (RB) obtained by subtracting the value of the B signal from the value of the R signal are calculated. If the RGB signal values are each represented by 8 bits (256 gradations), the values of (GR), (GB), and (RB) may be negative values. Therefore, it is represented by 9 bits. Each value of R, G, B, (GR), (GB), and (RB) corresponds to a color parameter value for specific color extraction in the present invention. The color difference calculation unit 44 inputs R, G, B, (GR), (GB), and (RB) values to the specific color extraction unit 45. In the present embodiment, R, G, B, (GR), (GB), and (RB) are color parameters. However, the color parameter is not limited to these.

  The specific color extraction unit 45 detects the color of the pixel from the image read by the image reading unit 4 in order to easily detect a specific image pattern included in the copy prohibited image and specifying the copy prohibited image. Performs a process of extracting a specific color pixel within a specific color range of the specific pattern.

  The specific color extraction unit 45 includes a comparator 451 and a setting register 452, and R, G, B, (GR), (GB), (R−) from the color difference calculation unit 44. B) Each signal is input to the comparator 451. The setting register 452 stores a specific color range in which the R, G, B, G-R, G-B, and R-B signal ranges are defined as ranges that express the color of a specific pattern.

The specific color range is determined by setting a threshold value that defines an upper limit and a lower limit of each value of R, G, B, GR, GB, and RB. Specifically, the specific color range includes a lower limit value R _min and an upper limit value R _{max of} the value of the R signal, and a lower limit value G of the value of the G signal for determining that the pixel color is the color of the specific pattern. _min and upper limit value G _max , lower limit value B _min and upper limit value B _max of the value of the B signal, lower limit value (GR) _min and upper limit value (GR) _{max of} the value of (G−R), (G From the lower limit (GB) _min and upper limit (GB) _max of the value of -B), the lower limit (RB) _min and upper limit (RB) _{max of the} value of (RB) Become. When 255 indicates the lightest color, 0 indicates the darkest color, and the color of the specific pattern is vermilion, the setting register 452 may include, for example, R _min = 40, R _max = 160, G _min = 0, G _max = 95, B _min = 0, B _max = 75, (G−R) _min = −95, (G−R) _max = −5, (G−B) _min = −15, (G−B) _A specific color range in which _max = 35, (R−B) _min = 5 and (R−B) _max = 105 is stored. In this case, only the color pixels whose values of R, G, B, GR, GB, and RB are all included in the specific range are extracted. The extracted color pixel is binarized to 1, and the other color pixels are binarized to 0. The binarized image data (binary image data) is sent to a specific pattern detection unit in order to determine whether the shape is a specific pattern shape. In the present invention, the value of the setting register is calculated at the time of color balance adjustment in which the values of gamma correction and color correction are adjusted using the reference chart.

  By setting the specific color range using not only the RGB signal value but also the color difference values (GR), (GB) and (RB), only the RGB signal value is used. Compared to the method of defining the specific color range, the specific color range of the specific pattern can be set more finely. The image processing apparatus 100 according to the present embodiment may be configured to set the specific color range using other color parameters.

The comparator 451 outputs R, G, B, (G−R), (G−B), and (R−) input from the color difference calculation unit 44 for each pixel (determination target) included in the read image data. B) Each value and the specific color range stored in the setting register 452 are compared to determine whether each value (each signal) is included in the specific color range. That is, the comparator 451 has an R value (R signal) of R _min or more and R _max or less, a G value (G signal) of G _min or more and G _max or less, and a B value (B signal) of B _min. and a _min or more B _max or less, the value of (G-R) of the value ((G-R) signal) is (G-R) _min or more (G-R) and a _max or less, (G-B) (( (GB) signal) is (GB) _min or more and (GB) _max or less and (RB) value ((RB) signal) is (RB) _min or more (R- B) It is determined whether it is below _max . The comparator 451 determines that the pixel color is a specific color when all the values of R, G, B, (GR), (GB), and (RB) are included in the specific color range. The pixel value, which is a value corresponding to the pixel, is determined to be 1 (hereinafter also referred to as black). Further, the comparator 451 determines the pixel to be determined when any value of R, G, B, (GR), (GB), and (RB) is out of the specific color range. The color is determined not to be a specific color, and the pixel value corresponding to the pixel is determined to be 0 (hereinafter also referred to as white). The comparator 451 determines a pixel value for each pixel included in the read image data, and outputs the binary image data representing the pixel value of each pixel as a binary value of 1 or 0 to the specific pattern detection unit 46. input.

  When the values of the RGB signals are 8 bits, the pixel value corresponding to each pixel is represented by 1 bit of 0 or 1 by the processing of the comparator 451, so the data amount for each pixel is 1/24. . When the resolution conversion unit 43 sets the respective resolutions in the main scanning direction and the sub-scanning direction to 1/6, the data amount representing the read image is 1/6 × 1/6 × 1/24 = 1/864. It becomes. As described above, since the amount of data to be handled by the specific pattern detection unit 46 is reduced, high-speed processing by the specific pattern detection unit 46 is facilitated.

  The setting register 452 stores a specific color range for each of a plurality of types of specific patterns related to a plurality of types of copy-prohibited images. The comparator 451 repeats the process for the number of specific color ranges stored in the setting register 452, and outputs binary image data for each of a plurality of types of specific patterns. Note that a plurality of specific color extraction units 45 corresponding to the number of types of specific patterns may be provided in parallel, and each specific color extraction unit 45 may output binary image data for each specific pattern.

  When a plurality of types of specific patterns share a specific color, the setting register 452 stores a specific color range common to the plurality of types of specific patterns, and the comparator 451 is common to the plurality of types of specific patterns. Value image data may be output.

  The binarized binary image data is input to the specific pattern detection unit 46. Before describing the specific pattern detection unit 46, a method for calculating a specific color range at the time of color balance adjustment will be described with reference to FIG. explain. Hereinafter, a case where the specific color is vermilion and the specific pattern is vermillion on a gift certificate will be described as an example.

First, as described above, the RGB value (read value) of the color patch of the reference chart 23 read by the image reading unit 1 at the time of color balance adjustment approaches the RGB value (target value) of the sample data 571. Correction is performed by the gamma correction unit 414 and the color conversion unit 415. The R patch, the G signal, and the B signal of the red twelfth patch after correcting the read data of the color patch of the reference chart 23 are R _r12 , G _r12 , and B _r12 , respectively. The values of the R signal, G signal, and B signal of the red No. 6 patch after correcting the data are R _r6 , G _r6 , and B _r6 , respectively.

  For color balance adjustment, black, red, blue, green, cyan, magenta, and yellow color patches are used. When the specific color is vermilion, the red color patch is used to define the specific color range. The threshold value is calculated. Similarly, the yellow specific color is calculated using a yellow patch, and the black specific color is calculated using a black patch.

The upper limit (bright for RGB) values R _max , G _max , B _max , (G−) of R, G, B, (G−R), (G−B), and (R−B) in the specific color region R) _max , (GB) _max , (RB) _max , and lower limit (dark for RGB) values R _min , G _min , B _min , (GR) _min , (GB) _min , (R−B) _min is expressed as shown in FIG. This equation is actually read by the image reading unit 1 even if the characteristics of the image reading unit 1 vary with various light sources (xenon lamps, LEDs, cold cathode tubes, etc.) and various light receiving sensors (CCDs and CISs of various manufacturers). This is obtained in advance by experiments so that the change in the above characteristics can be absorbed by using the reading value of the color chart. In FIG. 21, for example, “(GR) _min” is simply described as “GRmin”.

For example, the values of R _r12 , G _r12 , B _r12 after adjusting the cover balance of a certain reading device are 149, 58, 23, respectively, and the values of R _r6 , G _r6 , B _r6 are 203, 161, respectively. Suppose that it was 135. Assume that the RGB values of the sample data for the red 12th patch are 150, 52, and 23, and the RGB values of the sample data for the red 6th patch are 199, 164, and 135, respectively. The reading device is a reading device that can only be adjusted so that the value of R is slightly increased and the value of G is decreased when a red image in the middle density portion is read. When used as a color scanner or a color copier, Since the difference from the sample data is small, it is hardly a problem.

  However, when extraction of a specific color is considered, the color difference value obtained by subtracting the R value from the G value (G−R) becomes smaller than the actual value as R increases and G decreases. For this reason, for example, even if the general pattern 16 shown in FIG. 16 (not the gift certificate, the red mark of the Faculty of Commerce) is slightly different in hue from the specific pattern, the thickness and diameter of the general pattern circle 162 are different from the specific pattern. In the same way, when the quotient character 163 of the general pattern is similar to the quotient character of the specific pattern of the gift certificate, the value of (G−R) becomes smaller than the value of the standard reader, so that the specific color May be mis-detected.

  FIG. 19 shows a specific pattern included in the shareholder special coupon as an example of the specific pattern. In addition to the circle 262 and the excellent character 263, the base pattern 264 is printed in a color similar to the specific color. . In the reading device in which the value of the intermediate density R data is increased and the G value is decreased, the color of the base pattern 264 is extracted, and the arc cannot be detected depending on the angle at which the shareholder coupon is placed on the reading device. May not be detected, and a counterfeit coupon may be printed.

  As described above, since there are many originals including a specific pattern and originals that do not include a specific pattern, the image processing apparatus 1 including a reading device 1 can be used to reliably detect a specific pattern and not reliably detect a specific pattern. It is necessary to optimize the setting of the color space of the specific color extraction pattern for each table. Therefore, it is very expensive to completely adjust the color balance of all the reading devices. However, in the present invention, by using the color patch data value after adjustment at the time of color balance adjustment, a specific color range that is optimal for each apparatus can be defined (color extraction register) without using extra work and parts. ) Can be set.

  The expression for calculating the specific color range is an expression set in the image processing apparatus 100 at the time of shipment. FIG. 21 shows an example in which the color of the specific pattern is vermilion. However, if the color of the specific pattern is changed, the formula and the color of the color patch to be used are changed.

  In this way, by using the values that are actually corrected for each image processing device, it is possible to absorb all variations from device to device, device to device model, and slight image changes due to cost reductions in device parts. can do.

  However, if there is a case where the adjustment cannot be performed correctly due to intention or negligence, an incorrect specific color range is set. For example, the specific color range can be distorted by crafting the chart. Therefore, when correct adjustment cannot be made due to intention or negligence, the following measures are taken.

First, a difference between a target value that is an RGB value of the sample data 571 and a correction value that is a corrected value is obtained. For example, if the difference between the target value and the correction value is (G−R) _min , the difference is obtained by subtracting (G _r12 −R _r12 ) from (g _r12 −r _r12 ). Note that (g _r12 -r _r12 ) may be subtracted from (G _r12 -R _r12 ). Here, the correction value is a gamma value so that the RGB value (read value) of the color patch of the reference chart 23 read by the image reading unit 1 approaches the RGB value (target value) of the sample data 571. The values are corrected by the correction unit 414 and the color conversion unit 415.

  Then, the formula for calculating the specific color range is changed according to the obtained difference as shown in FIG.

In FIG. 22, after correcting the color patch of the reference chart 23 read at the time of color balance adjustment, the values (correction values) of the R signal, the G signal, and the B signal of the red twelfth patch are respectively R _r12 , G _r12 , It is assumed that B _r12 and the values (correction values) of the R signal, the G signal, and the B signal of the red No. 6 patch are R _r6 , G _r6 , and B _r6 , respectively. Further, the target values of the R signal, G signal, and B signal of the red 12th patch of the sample data 571 are set to r _r12 , g _r12 , and b _r12 , respectively, and the R signal and G signal of the red 6th patch of the sample data 571 are used. The target values of the B signal are r _r6 , g _r6 , and b _r6 , respectively. In FIG. 22, for example, “(GR) _min” is simply described as “GRmin”.

  The difference between the target value and the correction value is smaller (less than −5 in FIG. 22) or larger (greater than 5 in FIG. 22) when it is smaller than the allowable range (−5 to 5 (absolute value within 5) in FIG. 22). In some cases, the target value is used in the formula for calculating the specific color range.

  When the difference between the target value and the correction value is within the allowable range (from −5 to 5 in FIG. 22), the correction value is used in the formula for calculating the specific color range.

  By dividing the formula as described above, when the reference chart 23 cannot be read correctly by the image reading unit 1, that is, there is a difference between the color data value of the corrected reference chart and the color value of the sample data. Even in this case, the specific color can be detected correctly.

  An allowable range (−5 or more and 5 or less in FIG. 22) of the difference between the target value for changing the equation of FIG. 22 and the adjusted value is a value determined in advance at the time of shipment of the image processing apparatus 100. This permissible range can prevent counterfeiting of banknotes, etc., based on whether or not there is a sense of incongruity when banknotes having a specific color are actually printed. The criterion for whether or not there is a sense of incongruity may be determined by, for example, copying a document including a specific pattern by changing the difference and judging by a plurality of people.

  Note that the equation for calculating the specific color range shown in FIG. 22 is also an equation set in the image processing apparatus 100 at the time of shipment, as in FIG. In the present embodiment, an example of an expression for extracting a vermilion specific pattern has been described. However, in another specific color, the expression shown in FIG. 22 and the color patch used are changed.

  The specific color range is calculated by the specific range determining unit 562 of the control unit 56.

  Further, a reference chart used for adjusting the inclination of the document feeder and the color balance of the image processing apparatus as shown in FIG. 17 is used during production, and the gamma adjustment chart as shown in FIG. Man may use. With this configuration, it is possible to adjust the inclination of the document feeder, the color balance, and the specific color range in a short time during production. On the other hand, the service person of the apparatus can adjust the color balance even if there is no special equipment or the environment is not prepared.

(Specific pattern detector)
Next, the processing content in the specific pattern detection unit 46 will be described. Since the data is binarized, there is no color, but for convenience of explanation, 1 is written as black and 0 is written as white. The specific pattern detection unit 46 performs a process for detecting a partial pattern constituting a part of the specific pattern from the image, and performs a process for detecting the specific pattern from the image when the partial pattern is detected.

  FIG. 7 is a schematic diagram illustrating an example of a copy prohibition image, and FIG. 8 is a schematic diagram illustrating an example of a specific pattern. FIG. 7 shows a gift certificate as an example of a copy prohibited image, and a specific pattern 61 is included in the copy prohibited image.

  As shown in FIG. 8, the specific pattern 61 is a pattern having a shape in which a quotient character is written in a circle. A plurality of types of copy-prohibited images may include a common specific pattern, and a plurality of types of copy-prohibited images may include individual specific patterns. If the specific pattern 61 as shown in FIG. 8 is included in the image, it can be determined that the image is a copy-prohibited image. On the other hand, when the specific pattern is not included in the image, it can be determined that the image is not a copy prohibited image. Note that the specific pattern is not limited to the example illustrated in FIG. 8, and a plurality of types of figures such as red marks included in the banknote are set as the specific pattern.

  FIG. 9 is a schematic diagram illustrating an example of a partial pattern constituting a part of the specific pattern. 9 shows an example in which the solid line portion is a partial pattern 62, and the partial pattern 62 is an arc that forms part of the specific pattern 61 shown in FIG. In FIG. 9, portions other than the partial pattern 62 in the specific pattern 61 are indicated by dotted lines. When the partial pattern 62 that is an arc is detected in the image, a specific pattern candidate image that may be the specific pattern 61 can be extracted.

  FIG. 10 is a schematic diagram illustrating an example of a specific pattern candidate image. When the partial pattern 62 is detected in the image, the radius of the arc of the partial pattern 62 is n (mm), and the portion surrounded by the circle of the radius n including the partial pattern 62 may be the specific pattern 61. . Therefore, a portion surrounded by a circle with a radius n including the partial pattern 62 in the image is the specific pattern candidate image 63. In FIG. 10, portions other than the partial pattern 62 of the circle including the partial pattern 62 are indicated by broken lines, and the range of the specific pattern candidate image 63 is indicated by hatching. A partial pattern is set for each of the other types of specific patterns.

  Although the shape of the partial pattern is not limited, it may be a shape that can be easily detected as shown in FIG. 9, and the shape of the specific pattern candidate image 63 can be easily determined as shown in FIG. 10. is necessary.

  The specific pattern detection unit 46 sets a determination window having a size capable of including the partial pattern in the image, and moves the determination window in the image to determine whether or not the partial pattern is included in the determination window. Then, a process of detecting a partial pattern from the image is performed.

  FIG. 11 is a schematic diagram illustrating an example of the determination window. In the example shown in FIG. 11, the determination window 64 has a rectangular shape in which each side is parallel to the main scanning direction and the sub-scanning direction when the image is read using the image reading unit 1. The size 62 is included. FIG. 11 shows a state in which the partial pattern 62 is included in the determination window 64 in order to show the relationship between the size of the determination window 64 and the partial pattern 62.

  When a partial pattern is included in the determination window 64 on the image represented by the binary image data input from the specific color extraction unit 45, a specific color that is an image of a specific color among the pixels in the determination window 64 The pixels are concentrated on the partial pattern, and other pixels that are not specific color pixels should be distributed in other portions. The specific pattern detection unit 46 sets the size of the determination window 64 as information for setting the shape of the partial pattern, and sets each area obtained by dividing the inside of the determination window 64 in order to examine the distribution of specific color pixels. Remembered templates.

  FIG. 12 is a schematic diagram showing an example of the template. FIG. 12A shows a pixel distribution when the partial pattern 62 is included in the determination window 64. In the example shown in FIG. 12, the determination window 64 includes six line data 641, 642, 643, 644, 645, and 646 arranged in the sub-scanning direction, and each line data is arranged in the main scanning direction 42. Pixels are included. A black cell shown in FIG. 12A represents a specific color pixel having a pixel value of 1, and a white cell represents a pixel having a pixel value of 0. For example, in the line data 641, the pixel values of the pixels corresponding to the coordinates (0,0) to (15,0) and the coordinates (26,0) to (41,0) are 0, and the coordinates (16,0) The pixels corresponding to .about. (25,0) are specific color pixels having a pixel value of 1.

  FIG. 12B shows the template 70 compared with the determination window 64 including the partial pattern 62. The template 70 includes a first line 71, a second line 72, a third line 73, a fourth line 74, a fifth line 75, and a sixth line 76 corresponding to the line data 641 to 646 in the determination window 64, respectively. Has been. Each of the first line 71 to the sixth line 76 has 42 pixels in the main scanning direction and is divided into three regions in the main scanning direction.

  The first line 71 includes a first area 71a from coordinates (15,0) to (26,0), coordinates (11,0) to (14,0), and coordinates (27,0) to (30,0). The second regions 71b and 71b are divided into coordinates (0, 0) to (10, 0) and third regions 71c and 71c from coordinates (31, 0) to (41, 0). The second line 72 includes a first area 72a from coordinates (17,1) to (24,1), coordinates (11,1) to (16,1), and coordinates (25,1) to (30,1). The second regions 72b and 72b, the coordinates (0, 1) to (10, 1), and the coordinates (31, 1) to (41, 1) are divided into third regions 72c and 72c. The third line 73 includes a first area 73a from coordinates (13, 2) to (28, 2), coordinates (8, 2) to (12, 2), and coordinates (29, 2) to (33, 2). The second regions 73b and 73b, the coordinates (0, 2) to (7, 2), and the coordinates (34, 2) to (41, 2) are divided into third regions 73c and 73c. The fourth line 74 includes a first area 74a from coordinates (11, 3) to (30, 3), coordinates (7, 3) to (10, 3), and coordinates (31, 3) to (34, 3). The second regions 74b and 74b, the coordinates (0, 3) to (6, 3), and the coordinates (33, 3) to (41, 3) are divided into third regions 74c and 74c. The fifth line 75 includes a first region 75a from coordinates (10, 4) to (31, 4), coordinates (5, 4) to (9, 4), and coordinates (32, 4) to (36, 4). The second areas 75b and 75b, the coordinates (0, 4) to (4, 4), and the coordinates (37, 4) to (41, 4) are divided into third areas 75c and 75c. The sixth line 76 includes a first area 76a from coordinates (7,5) to (34,5), coordinates (4,5) to (6,5), and coordinates (35,5) to (37,5). The second regions 76b and 76b, the coordinates (0, 5) to (4, 5) and the third regions 76c and 76c to the coordinates (38, 5) to (41, 5) are divided.

  As shown in FIG. 12B, the shape of the determination window 64 is set according to the overall shape of the template 70. Each region in the template 70 is set according to the distribution of specific color pixels when the partial pattern 62 is included in the determination window 64. That is, the first area 71a and the second areas 72b to 76b are areas where specific color pixels concentrate when the partial pattern 62 is included in the determination window 64, and the other areas hardly include specific color pixels. It is an area.

  The specific pattern detection unit 46 further stores a pixel number range that defines a range of the number of specific color pixels included in each region when the partial pattern 62 is included in the determination window 64.

  FIG. 13 is a chart showing an example of the pixel number range. Here, “black” in FIG. 13 represents “specific color pixels”, and “9 ≦ black” represents that there are nine or more specific color pixels. As described above, the specific color pixel is treated as 1 (black) by binarization. Since the first region 71a of the first line 71 and the second regions 72b to 76b of the second line 72 to the sixth line 77 have specific color pixels concentrated when the partial pattern 62 is included in the determination window 64, The pixel number range is set so as to include many specific color pixels. In the other areas, when the partial pattern 62 is included in the determination window 64, the specific color pixels are hardly included. Therefore, the pixel number range is set so that the specific color pixels are hardly included.

  When the number of specific color pixels is included in the pixel number range in all the regions defined by the template 70, it is determined that the partial pattern is included in the determination window 64. The specific pattern detection unit 46 stores a template and a pixel number range for each of a plurality of types of specific patterns.

  The specific pattern detection unit 46 determines the positions of the determination window 64 in the main scanning direction and the sub scanning direction in the image represented by the binary image data input from the specific color extraction unit 45, and determines among the pixels in the image. From the pixels included in the window 64, the number of specific color pixels included in each region defined by the template 70 is measured. Specifically, the number of pixels having a pixel value of 1 among the pixels included in each region is measured.

  Next, the specific pattern detection unit 46 compares the measured number of specific color pixels in each area with the pixel number range stored for each area, and the number of specific color pixels in all areas is the number of pixels. If it is included in the range, it is determined that the partial pattern 62 has been detected. The specific pattern detection unit 46 determines that the partial pattern 62 cannot be detected when there is a region where the number of specific color pixels is not included in the pixel number range, and sets the determination window 64 in the image in the main scanning direction. Similarly, the process of detecting the partial pattern 62 is performed by moving the pixel.

  When scanning in the main scanning direction is completed when the partial pattern 62 cannot be detected, the specific pattern detection unit 46 moves the determination window 64 by one pixel in the sub-scanning direction within the image, and similarly scans in the main scanning direction. I do. When scanning of the entire image is completed in a state where the partial pattern 62 cannot be detected, the specific pattern detection unit 46 determines that the specific pattern is not included in the read image.

  Further, when detecting the partial pattern 62, the specific pattern detection unit 46 extracts a specific pattern candidate image 63 including the partial pattern 62 included in the determination window 64 from the image represented by the binary image data. Next, the specific pattern detection unit 46 determines whether or not the specific pattern candidate image 63 is a specific pattern based on the distribution of specific color pixels included in the extracted specific pattern candidate image 63. Specifically, the specific pattern detection unit 46 divides the specific pattern candidate image 63 into a plurality of regions, and when the number of specific color pixels included in each region is within a predetermined range, the specific pattern detection unit 46 It is determined that the candidate image 63 is the specific pattern 61.

  The specific pattern candidate image 63 is divided into a plurality of areas in accordance with area setting data that defines the divided areas. FIG. 14 is a schematic diagram in which the specific pattern candidate image 63 is divided into a plurality of regions in accordance with the region setting data. In the example shown in FIG. 14, the circular specific pattern candidate image 63 is divided into concentric circles. In FIG. 14, the region surrounded by the circumference having the smallest radius is the first divided region 631, the region surrounded by the circumference and the circle having the second smallest radius is the second divided region 632, and the circumference thereof. And a region surrounded by a circle having the third smallest radius is a third divided region 633, and a region surrounded by the circle and the outer periphery is a fourth divided region 634.

  The specific pattern detection unit 46 stores area setting data that defines the divided areas. The specific pattern detection unit 46 further stores a specific color pixel number range that defines a range of the number of specific color pixels included in each region obtained by dividing the specific pattern according to the region setting data. When the specific pattern is divided according to the area setting data, it is divided into a first divided area, a second divided area, a third divided area, and a fourth divided area as described above.

  FIG. 15 is a conceptual diagram illustrating an example of a specific color pixel number range. In FIG. 15, the range of the number of specific color pixels in the first divided region is 246 or more and 300 or less, the range of the number of specific color pixels in the second divided region is 250 or more and 302 or less, and in the third divided region In the example, the range of the number of specific color pixels is 266 or more and 310 or less, and the range of the number of specific color pixels in the fourth divided region is 480 or more. Therefore, although details will be described later, for example, the range of the number of specific color pixels in the first divided region 631 of the specific pattern candidate image 63 and the number of specific color pixels in the first divided region shown in FIG. Is compared.

  The example shown in FIG. 15 is an example in the case where the specific pattern is the specific pattern 61 shown in FIGS. 7 and 8, and the specific color pixel included in each area obtained by dividing the specific pattern 61 as shown in FIG. It is determined according to the number.

  As described above, the area setting data and the specific color pixel number range are determined to reflect the distribution of the specific color pixels included in the specific pattern. The specific pattern detection unit 46 stores region setting data and a specific color pixel number range for each of a plurality of types of specific patterns.

  The specific pattern detection unit 46 divides the specific pattern candidate image 63 into a plurality of divided areas defined by the area setting data, and measures the number of specific color pixels included in each divided area. Specifically, the number of pixels having a pixel value of 1 among the pixels included in each divided region is measured. Next, the specific pattern detection unit 46 compares the measured number of specific color pixels in each divided region with the pixel number range in each divided region defined by the specific color pixel number range, and the specific color in all the divided regions. When it is determined that the specific pattern 61 is detected when the number of pixels is included in the pixel number range, it is determined that the specific pattern is included in the read image. On the contrary, the specific pattern detection unit 46 determines that the specific pattern 61 is not detected when there is a divided region where the number of specific color pixels is not included in the pixel number range, and the specific pattern is included in the read image. Is determined not to be included. The specific pattern detection unit 46 finally outputs the determination result to the CPU 51.

  In the case of detecting a plurality of specific patterns with which the partial pattern 62 is common, such as specific patterns with different characters written in a circle, the specific pattern detection unit 46 determines the number of specific patterns with which the detected partial pattern 62 is common. Only the specific pattern detection process is repeated. The specific pattern detection unit 46 repeats the specific pattern detection process for each of a plurality of types of specific patterns. A specific pattern detection unit 46 is connected to each of the plurality of specific color extraction units 45 provided in parallel, and each specific pattern detection unit 46 detects specific patterns for binary image data output from each specific color extraction unit 45. The form which performs this process may be sufficient.

  The CPU 51 controls the processing of the image data according to the determination result output from the specific pattern detection unit 46. That is, when the determination result that the specific pattern is not included in the image read by the image reading unit 1 is output, the CPU 51 stores the image data output by the image quality improvement processing unit 47 in the RAM 53 and stores the image data. Processing to transmit from the transmission unit 58 to the outside is performed. On the contrary, when the determination result that the image read by the image reading unit 1 includes the specific pattern is output, the CPU 51 outputs the image data output by the image quality improvement processing unit 47 from the transmission unit 58 to the outside. The process which prohibits doing is performed. At this time, the CPU 51 performs a process of displaying information for notifying the output of the image data on the display unit 54.

  As described above, the image processing apparatus 100 configured as described above actually reads a reference chart and performs a process of calculating a gamma correction value and a color conversion correction correction coefficient based on the read reference chart. At the same time, the image processing apparatus 100 compares the read value obtained by actually reading the reference chart with the target value included in the sample data stored in the storage unit 57, thereby determining the specific color range stored in the setting register 452. Perform the decision process.

(Program etc.)
In the image processing apparatus 100 of the present embodiment, in particular, each unit and each processing step of the image processing unit 4 and the control unit 56 is a program stored in a storage unit such as a ROM (Read Only Memory) or a RAM by a calculation unit such as a CPU. This is realized by controlling the input means such as the keyboard, the output means such as the display, or the communication means such as the interface circuit. Therefore, the computer having these means can realize various functions and various processes of the image processing unit 4 and the control unit 56 of the present embodiment simply by reading the recording medium storing the program and executing the program. Can do. In addition, by recording the program on a removable recording medium, the various functions and various processes described above can be realized on an arbitrary computer.

  As this recording medium, a program medium such as a memory (not shown) such as a ROM may be used for processing by the microcomputer, or a program reader is provided as an external storage device (not shown). It may be a program medium that can be read by inserting a recording medium therein.

  In any case, the stored program is preferably configured to be accessed and executed by the microprocessor. Furthermore, it is preferable that the program is read out, and the read program is downloaded to a program storage area of the microcomputer and the program is executed. It is assumed that this download program is stored in advance in the main unit.

  The program medium is a recording medium configured to be separable from the main body, such as a tape system such as a magnetic tape or a cassette tape, a magnetic disk such as a flexible disk or a hard disk, or a disk such as a CD / MO / MD / DVD. Fixed disk, IC card (including memory card), etc., or semiconductor ROM such as mask ROM, EPROM (Erasable Programmable Read Only Memory), EEPROM (Electrically Erasable Programmable Read Only Memory), flash ROM, etc. In particular, there are recording media that carry programs.

  In addition, if the system configuration is capable of connecting to a communication network including the Internet, the recording medium is preferably a recording medium that fluidly carries the program so as to download the program from the communication network.

  Further, when the program is downloaded from the communication network as described above, it is preferable that the download program is stored in the main device in advance or installed from another recording medium.

  The present invention is not limited to the above-described embodiments, and various modifications can be made. In other words, embodiments obtained by combining technical means appropriately changed are also included in the technical scope of the present invention.

  According to the present invention, a specific pattern for specifying a print prohibited image can be reliably detected from the read image data by non-special adjustment. Therefore, the image processing for detecting the specific pattern for specifying the print prohibited image from the read image. Applicable to the device.

1 Image reading unit (reading means)
4 Image processing unit 16 General pattern 23 Reference chart 40 Image determination unit (determination means)
43 Resolution Conversion Unit 44 Color Difference Calculation Unit 45 Specific Color Extraction Unit 46 Specific Pattern Detection Unit 47 Image Quality Improvement Processing Unit 51 CPU
56 control unit 57 storage unit (sample data storage unit, parameter storage unit)
61 Specific Pattern 414 Gamma Correction Unit 415 Color Conversion Unit 425 Memory Control Unit 427 Page Memory 451 Comparator 452 Setting Register 561 Parameter Calculation Unit (Correction Parameter Calculation Unit)
562 Specific range determination unit (specific color range determination means)
571 Sample data

Claims (9)

A reading unit that reads an original image in color and converts it into image data, and a determination as to whether or not the image data includes a specific pattern that specifies copy prohibition is performed by using a specific color that is the color of the specific pattern and the specific pattern Based on the shape of the
The determination means includes a plurality of color parameters included in the determination target color in a specific color range that defines a range that can be recognized as a color parameter included in the specific color for each value of the plurality of color parameters included in the specific color. An image processing apparatus for determining whether or not a color parameter value is included,
A sample data storage unit storing sample data generated as ideal read data of a reference chart including a plurality of color patches whose density is known in advance;
Correction parameter calculation means for calculating a correction parameter for correcting the color parameter value of the reference image data, which is the image data of the reference chart actually read by the reading means, to approach the value of the color parameter of the sample data; ,
A parameter storage unit for storing the calculated correction parameter;
Correction means for correcting the value of the color parameter of the image data based on the calculated correction parameter;
A specific color range determination unit that calculates the specific color range using a value of a color parameter after the reference image data is corrected by the correction unit based on the calculated correction parameter;
An image processing apparatus comprising:   The specific range determination unit calculates a difference between a color parameter value after the reference image data is corrected by the correction unit based on the calculated correction parameter, and a color parameter value of the sample data; The image processing apparatus according to claim 1, wherein the specific color range is calculated using different calculation formulas depending on whether the difference is within a predetermined allowable range or not.   The reading unit reads an image obtained by adding another function to the function of adjusting the color balance of the image processing apparatus as the reference image when the image processing apparatus is produced. An image processing apparatus according to 1.   The image processing apparatus according to claim 2, wherein the allowable range is determined in advance in consideration of an influence on image quality when the image data is printed.   When the calculated difference is within the allowable range, the specific color range determination unit uses a color parameter value after correcting the reference image data by the correction unit, using the calculation formula 5. The image according to claim 2, wherein when the calculated difference is outside the allowable range, the specific color range is calculated by a calculation formula using a color parameter value of the sample data. Processing equipment.   An image forming apparatus comprising: the image processing apparatus according to claim 1; and a printing apparatus that performs printing based on the image data. A reading unit that reads an original image in color and converts it into image data, and a determination as to whether or not the image data includes a specific pattern that specifies copy prohibition is performed by using a specific color that is the color of the specific pattern and the specific pattern A determination unit configured to perform determination based on the shape of the color, and the determination unit specifies a range that can be recognized as a color parameter included in the specific color for each value of the plurality of color parameters included in the specific color A method for determining the specific color range of an image processing apparatus for determining whether a color range includes a plurality of color parameter values included in a color to be determined,
A sample data storage step for storing sample data generated as ideal read data of a reference chart including a plurality of color patches whose density is known in advance;
A correction parameter calculating step for calculating a correction parameter for correcting the color parameter value of the reference image data, which is the image data of the reference chart actually read by the reading unit, to approach the color parameter value of the sample data; ,
A parameter storage step for storing the calculated correction parameter;
A correction step of correcting the value of the color parameter of the image data based on the calculated correction parameter;
A specific color range determination step for calculating the specific color range using a color parameter value after correcting the color parameter value of the reference image data based on the calculated correction parameter;
A determination method characterized by comprising:   A program for causing a computer to function as each means of the image processing apparatus according to any one of claims 1 to 5.   A computer-readable recording medium on which the program according to claim 8 is recorded.

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