JP4808282B2 - Image processing apparatus, image forming apparatus, image processing method, image processing program, and recording medium for recording image processing program - Google Patents

Description

  The present invention relates to an image processing apparatus, an image forming apparatus, an image processing method, an image processing program, and a recording medium for recording an image processing program, which determine whether a document to be read is a double-sided document or a single-sided document.

  When copying a double-sided document with an automatic document feeder or other device in a copying machine or image reader, or when sending an original image to a specified email address as a scan to e-mail, multiple documents to be read If a single-sided document and a double-sided document are mixed, the user must first separate the single-sided document and the double-sided document and perform a reading operation on each. It is necessary to rearrange them in the original order.

  On the other hand, if reading is performed without separating the document as described above, unnecessary plain paper is output. In particular, when color plain paper is mixed, color toner (ink) is wasted. Also, when storing the read original image data, the storage capacity of the hard disk or the like is wasted.

In order to solve the above problems, the following methods have been proposed.
In the invention described in Patent Document 1, in a file in which a double-sided original and a single-sided original are mixed, the double-sided original and the single-sided original are distinguished depending on the presence or absence of an image. The presence or absence of an image is determined by counting the number of black pixels and checking whether or not the count value exceeds a certain reference value. Alternatively, the determination is made based on the data amount of the compressed image data.

  In the invention described in Patent Document 2, when distinguishing between double-sided originals and single-sided originals, a threshold is set to a level close to white, and the presence or absence of an image is determined by counting the number of pixels lower than this threshold. When the count number is greater than a predetermined value, it is determined that there is an image.

  The invention described in Patent Document 3 obtains a binary level of image data, compares the number of pixels of the binary level with a predetermined value, and determines whether the image data corresponds to a blank original.

JP-A-6-245003 JP-A-9-261383 JP-A-9-284490

  When the above conventional technology is applied, isolated points that are not in the image data, the influence of noise during scanning, dirt on the background of the document, and dust adhering to the background of the document are counted as black pixels. The determination accuracy of the plain image is lowered. This is the same when counting white pixels and counting black pixels.

  Further, in the prior art, since a color plain original is not considered at all, it is not possible to make a determination on a color plain image.

  An object of the present invention is to provide an image processing apparatus, an image forming apparatus, an image processing method, an image processing program, and a recording medium for recording the image processing program capable of determining a plain image with high accuracy regardless of whether it is monochrome or color. It is to be.

The present invention provides an image processing apparatus for determining whether image data is image data obtained by reading a plain original composed only of pixels having a single color density based on image data composed of a plurality of pixels.
An average value calculation unit that calculates an average value of pixel values in a pixel block including a plurality of pixels including a target pixel for each color component, and uses the calculated average value as a pixel value of the target pixel;
Based on the average value of each color component calculated by the average value calculation unit, the maximum value of the average value between each color component and the maximum difference of the average value are obtained for each pixel of interest, and each density of the maximum value and the maximum difference is obtained. A histogram creation unit that creates each histogram with the number of pixels for the classification as a frequency value;
For each color component, density information regarding density is calculated in a pixel block including a plurality of pixels including the target pixel, and whether the target pixel is an edge pixel by comparing the calculated density information with a predetermined density threshold value. A pixel determination unit that counts the number of pixels determined as edge pixels, and
Density classification in which the number of pixels determined as edge pixels by the pixel determination unit is equal to or less than a pixel number threshold, and the histogram of the maximum value and the histogram of maximum difference created by the histogram creation unit are equal to or greater than a predetermined frequency value And a determination unit that determines that the image data is obtained by reading a plain original when both of the density division numbers are equal to or less than the division threshold value.

According to another aspect of the present invention, there is provided an image processing apparatus for determining whether image data is image data obtained by reading a plain document including only pixels having a single color density, based on image data including a plurality of pixels.
An average value calculation unit that calculates an average value of pixel values in a pixel block including a plurality of pixels including a target pixel for each color component, and uses the calculated average value as a pixel value of the target pixel;
Based on the average value of each color component calculated by the average value calculation unit, the maximum value of the average value between each color component and the maximum difference of the average value are obtained for each pixel of interest, and each density of the maximum value and the maximum difference is obtained. A histogram creation unit that creates each histogram with the number of pixels for the classification as a frequency value;
In the histogram of the maximum value and the histogram of the maximum difference created by the histogram creation unit, the number of density categories that are equal to or greater than a predetermined frequency value is obtained, both of these density categories are equal to or less than the threshold value, A determination unit that determines that the image data is obtained by reading a plain original when the number of maximum difference histogram original density widths representing the entire number of sections equal to or greater than a predetermined frequency value satisfies a predetermined value. An image processing apparatus is characterized.

In addition, the present invention is an image forming apparatus including the image processing apparatus.
According to another aspect of the present invention, there is provided an image processing method for determining whether image data is image data obtained by reading a plain original composed only of pixels having a single color density, based on image data composed of a plurality of pixels.
For each color component, an average value calculation step of calculating an average value of pixel values in a pixel block including a plurality of pixels including the target pixel, and using the calculated average value as a pixel value of the target pixel;
For each color component, density information regarding density is calculated in a pixel block including a plurality of pixels including the target pixel, and whether the target pixel is an edge pixel by comparing the calculated density information with a predetermined density threshold value. And a pixel determination step for counting the number of pixels determined to be edge pixels,
Based on the average value for each color component calculated in the average value calculation step, the maximum value of the average value between each color component and the maximum difference of the average value are obtained for each pixel of interest, and each density of the maximum value and the maximum difference is obtained. A histogram creation step of creating each histogram with the number of pixels for the classification as a frequency value;
Density classification in which the number of pixels determined as edge pixels in the pixel determination step is equal to or less than a pixel number threshold, and the histogram of the maximum value and the histogram of maximum difference created in the histogram creation step are equal to or greater than a predetermined frequency value The image processing method includes a determination step of determining the image data obtained by reading a plain original when both the number of density categories are equal to or less than the threshold value.

According to another aspect of the present invention, there is provided an image processing method for determining whether image data is image data obtained by reading a plain original composed only of pixels having a single color density, based on image data composed of a plurality of pixels.
For each color component, an average value calculation step of calculating an average value of pixel values in a pixel block including a plurality of pixels including the target pixel, and using the calculated average value as a pixel value of the target pixel;
Based on the average value for each color component calculated in the average value calculation step, the maximum value of the average value between each color component and the maximum difference of the average value are obtained for each pixel of interest, and each density of the maximum value and the maximum difference is obtained. A histogram creation step of creating each histogram with the number of pixels for the classification as a frequency value;
In the histogram creation step, the maximum value histogram and the maximum difference histogram are used to determine the number of density categories that are equal to or greater than a predetermined frequency value, and both the number of density categories are equal to or less than the threshold value, A determination step of determining that the image data is obtained by reading a plain original when the number of maximum difference histogram document density widths representing the entire number of sections equal to or greater than a predetermined power value satisfies a predetermined value. This is an image processing method.

  The present invention is also an image processing program for causing a computer to execute the image processing method.

  The present invention is also a computer-readable recording medium that records an image processing program for causing a computer to execute the image processing method.

  According to the present invention, the average value calculation unit calculates, for each color component, an average value of pixel values in a pixel block including a plurality of pixels including the target pixel, and the calculated average value is used as the pixel value of the target pixel. To do. In the histogram creation unit, based on the average value for each color component calculated by the average value calculation unit, the maximum value of the average value between each color component and the maximum difference of the average value are obtained for each pixel of interest, and the maximum value and Each histogram is created with the number of pixels for each density category having the maximum difference as a frequency value.

  The pixel determination unit calculates density information related to density (pixel value) in a pixel block including a plurality of pixels including the target pixel for each color component, and compares the calculated density information with a predetermined density threshold value. It is determined whether or not the target pixel is an edge pixel, and the number of pixels determined to be an edge pixel is counted.

  The determination unit is such that the number of pixels determined to be edge pixels by the pixel determination unit is equal to or less than a pixel number threshold, and the maximum value histogram and the maximum difference histogram created by the histogram creation unit are equal to or greater than a predetermined frequency value. The number of density classifications to be obtained is obtained, and when both of these density classifications are equal to or less than the classification threshold value, it is determined that the image data is obtained by reading a plain original.

  As a result, it is possible to suppress the effects of isolated points, noise during scanning, dirt on the background of the document, and dust attached to the background of the document. Can be determined with high accuracy.

  According to the present invention, the average value calculation unit calculates an average value of pixel values in a pixel block including a plurality of pixels including the target pixel for each color component, and calculates the calculated average value as a pixel value of the target pixel. And In the histogram creation unit, based on the average value for each color component calculated by the average value calculation unit, the maximum value of the average value between each color component and the maximum difference of the average value are obtained for each pixel of interest, and the maximum value and Each histogram is created with the number of pixels for each density category having the maximum difference as a frequency value.

  The determination unit obtains the number of density categories that are equal to or greater than a predetermined frequency value from the maximum value histogram and the maximum difference histogram created by the histogram creation unit, and both the number of density categories are equal to or less than the threshold value. When the maximum difference histogram document density width number representing the entire number of sections equal to or greater than the predetermined power value satisfies a predetermined value, it is determined that the image data is obtained by reading a plain document.

  As a result, it is possible to suppress the effects of isolated points, noise during scanning, dirt on the background of the document, and dust attached to the background of the document. Can be determined with high accuracy.

  Further, according to the present invention, since the image forming apparatus includes the above-described image processing apparatus, it is possible to determine a plain original with high accuracy, and to suppress the use amount of color materials such as toner and ink. An easy-to-use image forming apparatus that saves labor can be provided.

  According to the present invention, in the average value calculating step, an average value of pixel values is calculated for each color component in a pixel block including a plurality of pixels including the target pixel, and the calculated average value is used as the pixel value of the target pixel. And In the histogram creation step, based on the average value for each color component calculated in the average value calculation step, the maximum value of the average value between each color component and the maximum difference between the average values are obtained for each pixel of interest, and the maximum value and Each histogram is created with the number of pixels for each density category having the maximum difference as a frequency value.

  In the pixel determination step, for each color component, density information related to density is calculated in a pixel block including a plurality of pixels including the target pixel, and the calculated density information is compared with a predetermined density threshold to determine whether the target pixel is an edge. It is determined whether or not the pixel is a pixel, and the number of pixels determined to be an edge pixel is counted.

  In the determination step, the number of pixels determined as the edge pixel in the pixel determination step is equal to or less than a pixel number threshold value, and the maximum value histogram and the maximum difference histogram created in the histogram creation step are equal to or greater than a predetermined frequency value. The number of density classifications to be obtained is obtained, and when both of these density classifications are equal to or less than the classification threshold value, it is determined that the image data is obtained by reading a plain original.

  As a result, it is possible to suppress the effects of isolated points, noise during scanning, dirt on the background of the document, and dust attached to the background of the document. Can be determined with high accuracy.

  According to the present invention, in the average value calculating step, an average value of pixel values is calculated for each color component in a pixel block including a plurality of pixels including the target pixel, and the calculated average value is used as the pixel value of the target pixel. And In the histogram creation step, based on the average value for each color component calculated in the average value calculation step, the maximum value of the average value between each color component and the maximum difference between the average values are obtained for each pixel of interest, and the maximum value and Each histogram is created with the number of pixels for each density category having the maximum difference as a frequency value.

  In the determination step, the number of density divisions that are equal to or greater than a predetermined frequency value is obtained from the maximum value histogram and the maximum difference histogram created in the histogram creation step, and both of these density division numbers are less than or equal to the division threshold value. When the maximum difference histogram document density width number representing the entire number of sections equal to or greater than the predetermined power value satisfies a predetermined value, it is determined that the image data is obtained by reading a plain document.

  As a result, it is possible to suppress the effects of isolated points, noise during scanning, dirt on the background of the document, and dust attached to the background of the document. Can be determined with high accuracy.

  In addition, according to the present invention, it is possible to provide an image processing program for causing a computer to execute the above-described image processing method, and a computer-readable recording medium on which the image processing program is recorded.

1 is a block diagram illustrating a configuration of an image forming apparatus 1 according to an embodiment of the present invention. 3 is a block diagram illustrating a configuration of an original document type automatic determination unit 13. FIG. 5 is a flowchart illustrating a determination process performed by an automatic document type determination unit 13; It is a figure which shows the example of a maximum value histogram. It is a figure which shows the example of a maximum difference histogram. It is a block diagram showing a configuration of a document type automatic determination unit 13a that determines a plain document and another document type. It is a flowchart which shows the discrimination | determination process of the original classification automatic discrimination | determination part 13a. 6 is a flowchart illustrating document determination processing. It is a flowchart of a determination process. It is a block diagram which shows the structure of the image reading apparatus 6 which is other embodiment of this invention.

  FIG. 1 is a block diagram showing a configuration of an image forming apparatus 1 according to an embodiment of the present invention. In the present embodiment, the image forming apparatus 1 is applied to an electrophotographic digital color copying machine.

  The image forming apparatus 1 includes a color image input device 2, a color image processing device 3, a color image output device 4, and an operation panel 5. The color image processing apparatus 3 includes an A / D (analog / digital) conversion unit 11, a shading correction unit 12, a document type automatic discrimination unit 13, an input tone correction unit 14, a region separation processing unit 15, a color correction unit 16, and a black color. The generated under color removal unit 17, the spatial filter processing unit 18, the output tone correction unit 19, and the tone reproduction processing unit 20 are configured.

  The color image input device 2 serving as an image reading unit includes a scanner unit (not shown) having a CCD (Charge Coupled Device), for example, and converts a reflected light image from a document into RGB (R: red, G : Green, B: blue), and the image data is read by a CCD as image data composed of analog signals representing the reflectance of reflected light from a recording medium such as paper on which an original image is recorded. Input to the processing device 3. Image data of analog signals given from the color image input device 2 to the color image processing device 3 is rasterized.

  The image data read by the color image input device 2 includes an A / D conversion unit 11, a shading correction unit 12, a document type automatic discrimination unit 13, an input tone correction unit 14, an area separation process included in the color image processing device 3. 15, the color correction unit 16, the black generation and under color removal unit 17, the spatial filter processing unit 18, the output gradation correction unit 19, and the gradation reproduction processing unit 20 are sent in this order, and CMYK (C: cyan, M: Magenta, Y: yellow, K: black) are output to the color image output device 4 as image data represented by digital color signals.

  The A / D (analog / digital) converter 11 converts analog signal image data corresponding to RGB into image data of digital signals. The shading correction unit 12 applies various types of image data generated in the illumination system, the imaging system, and the imaging system of the color image input apparatus 2 to the image data of digital signals respectively corresponding to RGB sent from the A / D conversion unit 11. Apply processing to remove distortion. The shading correction unit 12 adjusts the color balance.

  The automatic document type discrimination unit 13 uses an RGB signal (RGB reflectance signal) whose color balance has been adjusted by removing various distortions by the shading correction unit, such as a density signal, and is used in a color image processing apparatus. The signal is converted into a signal that can be easily handled by the system, and a determination is made as to whether or not the document is a blank document (non-image document or plain document). If it is determined that the document is a blank document, the subsequent processing is canceled. If it is determined that the document is not a blank document, the subsequent processing is continued.

  The automatic document type discrimination unit 13 determines not only the blank document but also the document type such as a character document, a printed photo document, or a character printed photo document in which characters and a printed photo are mixed. You may comprise so that discrimination may be performed.

  The document type determination signal representing the document type generated by the automatic document type determination unit 13 is input gradation correction unit 14, color correction unit 16, black generation and under color removal unit 17, spatial filter processing unit 18, gradation reproduction. It is output to the processing unit 20. Details of the automatic document type discrimination unit 13 will be described later.

  The input tone correction unit 14 performs image quality adjustment processing such as removal of background density and contrast. The background color of the document (paper on which characters are printed) varies, and yellowish items such as straw paper do not treat the background color as white. Extra recording agent is used. Therefore, the input tone correction unit 14 removes the background density, that is, sets the background density to a white density and simultaneously adjusts the contrast. The input tone correction unit 14 gives image data composed of density signals corresponding to RGB to the region separation processing unit 15.

  The region separation processing unit 15 converts each pixel in the image data input to the color image processing device 3 into a background region, a photo (photographic paper photo) region, a character region, and a halftone dot region by using density signals corresponding to RGB. And whether these are color or monochrome. In this embodiment, region separation refers to whether a region is a character region, a photographic region (continuous tone region) or a halftone dot region, and whether they are color or monochrome. , Etc. The character area represents a character including characters and symbols. The background area represents the background portion (background) of the document. Based on the separation result, the region separation processing unit 15 outputs a region identification signal indicating which region each pixel belongs to, a color correction unit 16, a black generation and under color removal unit 17, a spatial filter processing unit 18, and a gradation. In addition to outputting to the reproduction processing unit 20, the density signal corresponding to each of RGB output from the input tone correction unit 14 is output to the subsequent color correction unit 16 as it is.

  In response to the region identification signal provided from the region separation processing unit 15, the color correction unit 16 converts density signals (input signals) corresponding to RGB supplied from the region separation processing unit 15 and density signals (input signals) corresponding to CMY respectively. (Hereinafter referred to as CMY signal). The color correction unit 16 performs conversion from density signals corresponding to RGB to signals corresponding to CMY. The color correction unit 16 performs a process of removing color turbidity based on the spectral characteristics of the CMY color material including unnecessary absorption components in order to realize faithful color reproduction. The color correction unit 16 performs color conversion based on a document type determination signal provided from the document type automatic determination unit 13.

  The black generation / under color removal unit 17 obtains black generation for generating a black signal corresponding to black (K) from the CMY signal corresponding to CMY after color correction by the color correction unit 16 and black generation from the original CMY signal. A process of generating a new CMY signal by subtracting the K signal is performed. As a result, the CMY signals are converted into CMYK four-color signals (hereinafter referred to as CMYK signals).

  The black generation and under color removal unit 17 performs black generation using skeleton black as an example of black generation processing. In the black generation by the skeleton black, the input / output characteristics of the skeleton curve are y = f (x), the densities corresponding to the input C, M, and Y are respectively C, M, and Y, and the output C, If the densities corresponding to M, Y, and K are C ′, M ′, Y ′, and K ′, respectively, and the UCR (Under Color Removal) rate is α (0 <α <1), black generation and undercolor removal is performed. In the processing, the CMY three-color density signals are converted into CMYK four-color density signals by the following equation (1).

  The spatial filter processing unit 18 uses a digital filter that is set in advance for each region in the image data of the CMYK signal provided from the black generation and under color removal unit 17 in accordance with the region identification signal provided from the region separation processing unit 15. Filter processing is performed to correct the spatial frequency characteristics so as to prevent blurring of the output image and deterioration of graininess.

  Similar to the spatial filter processing unit 18, the gradation reproduction processing unit 20 performs predetermined processing on the image data of the CMYK signal provided from the output gradation correction unit 19 in accordance with the region identification signal provided from the region separation processing unit 15. Apply. For example, with respect to the region separated into the character region by the region separation processing unit 15, in order to improve the reproducibility of black characters or color characters in particular, the sharpness enhancement processing in the spatial filter processing by the spatial filter processing unit 18 increases the high frequency enhancement amount. In the gradation reproduction processing unit 20, binarization or multi-value processing is performed on a high-resolution screen suitable for high-frequency reproduction. Further, for the region separated into halftone dot regions by the region separation processing unit 15, the spatial filter processing unit 18 performs low-pass filter processing for removing the input halftone component. The output tone correction unit 19 performs an output tone correction process for converting a signal such as a density signal into a halftone dot area ratio that is a characteristic value of the color image output device 4. Then, gradation reproduction processing (halftone generation) is performed so that the image is finally separated into pixels and each gradation is reproduced. For the region separated into photographs by the region separation processing unit 15, binarization or multi-value processing is performed on the screen with an emphasis on gradation reproducibility.

  The operation panel 5 includes, for example, a display unit such as a liquid crystal display and operation keys. Information input from the operation panel 5 is given to a control unit (not shown). The control unit controls operations of the color image input device 2, the color image processing device 3, and the color image output device 4 in accordance with information input from the operation panel 5.

  The image data output from the gradation reproduction processing unit 20, that is, the image data on which the above-described processes are performed, is temporarily stored in the storage unit, read at a predetermined timing, and input to the color image output device 4. .

  The color image output device 4 is image forming means and outputs image data as an image on a recording medium (for example, a sheet body such as paper). The color image output device 4 can form an image on a recording medium using recording agents of two or more colors. In the present embodiment, the recording agents of each color of C, M, Y, and K are used. An image can be formed on a recording medium. The color image output device 4 forms an image using the C recording agent for the image data corresponding to C, forms an image using the M recording agent for the image data corresponding to M, and Y For image data corresponding to, an image is formed using a Y recording agent, and for image data corresponding to K, an image is formed using a K recording agent. The color image output device 4 is realized by an electrophotographic printer device in the present embodiment. However, in another embodiment of the present invention, the color image output device 4 is realized by an ink jet printer device. Also good. Each unit of the color image processing apparatus 3 is controlled by a control unit (not shown). The control unit includes a CPU (Central Processing Unit) and a storage medium in which a control program executed by the CPU is stored. The CPU controls the color image input device 2, the color image processing device 3, and the color image output device 4 by executing the control program.

  FIG. 2 is a block diagram showing a configuration of the document type automatic discrimination unit 13. FIG. 3 is a flowchart showing the determination processing by the document type automatic determination unit 13.

  As shown in FIG. 2, the document type automatic discrimination unit 13 includes an average value calculation unit 21, a pixel determination unit 22, a calculation unit 23, a histogram creation unit 24, an edge pixel count unit 25, a determination unit 26, and an edge determination threshold setting unit. 27, a first determination threshold setting unit 28, a second determination threshold setting unit 29, and a third determination threshold setting unit 30.

  The average value calculation unit 21 calculates an average value of density values of blocks (for example, 7 × 7 pixels) including a plurality of pixels including the target pixel for each RGB plane (for each color component), and calculates the pixel value of the target pixel. (Step S1). The pixel determination unit 22 calculates a maximum density difference in a block (for example, 7 × 7 pixels) that includes a plurality of pixels and includes the target pixel for each RGB plane (each color component) (step S2), and determines an edge determination threshold value. It is compared with an edge determination threshold value (for example, 30) given from the setting unit 27, and it is determined whether the target pixel of the block belongs to the edge pixel (step S3). That is, when any one of the plurality of color components has a maximum density difference equal to or greater than the threshold, it is determined that the target pixel is an edge pixel (step S8). As a method for determining an edge, in addition to such a maximum density difference, a dispersion value may be obtained, and when the dispersion value is equal to or greater than a threshold value, it may be determined that the pixel is an edge pixel.

  The pixel determined by the pixel determination unit 22 as an edge pixel is counted by the edge pixel counting unit 25.

  Next, the calculation unit 23 compares the average value calculated for each plane (for each color component) of the target pixel calculated by the average value calculation unit 21, and determines the maximum average value between the color components for each target pixel. The maximum difference is calculated (steps S4 and S6), and the histogram creation unit 24 generates a histogram of each of the maximum value and the maximum difference (steps S5 and S7). The number of density categories is, for example, 16 categories.

  It is determined whether or not the processing of all pixels has been completed (step S9). If not completed, the process proceeds to the next pixel block and the above process is repeated. If completed, the determination unit 26 compares the number of edge pixels counted by the edge pixel count unit 25 with a first determination threshold value (for example, 5000) given from the first determination threshold value setting unit 28 (step S10). If the number of edge pixels is larger than the first determination threshold value, a character area or a dot area exists, and it is determined that the document is not a plain original (step S15). Further, when the number of edge pixels counted by the edge pixel counting unit 25 is compared with a first determination threshold value (for example, 5000) given from the first determination threshold value setting unit, and the number of edge pixels is equal to or less than the first determination threshold value, It is determined that the document is a plain document or a photographic paper photograph document. When it is determined that the document is a plain document or a photographic paper photograph document, each histogram of the maximum value and the maximum difference created by the histogram creation unit 24 and the second determination threshold value (for example, the second determination threshold value setting unit 29) , 500) to calculate the total value of the number of divisions whose power value is larger than the second determination threshold value, and set each as the maximum value histogram document density width and the maximum difference histogram document density width (step S11, step S12). ).

  Each of the calculated maximum value histogram document density width and maximum difference histogram document density width is compared with a third determination threshold value (for example, 3) given from the third determination threshold value setting unit 30 (step S13). If it is smaller than the determination threshold, it is determined as a plain original (step S14).

  Although the configuration in which the pixel determination unit 22 is provided has been described above, the maximum value and the maximum value of the average value for each color component using the average value calculated by the average value calculation unit 21 without the pixel determination unit 22 being provided. The difference may be calculated, and histograms of the maximum value and the maximum difference may be generated to determine whether the document is a plain document. In this case, in addition to the determination of the maximum histogram original density width and the maximum difference histogram original density width, the number of maximum difference histogram original density widths is detected, and each of the maximum histogram original density width and the maximum difference histogram original density width is If it is smaller than the third determination threshold (for example, 3) and the number of maximum difference histogram document density widths is 1, it may be determined that the document is a plain document.

  Hereinafter, the histogram generated by the histogram creation unit 24 will be described in detail.

  FIG. 4 is a diagram illustrating an example of the maximum value histogram, and FIG. 5 is a diagram illustrating an example of the maximum difference histogram.

Examples of histograms for plain originals are shown in FIGS. 4 (a) and 5 (a).
Since a plain document has only pixels of a single color density, both the maximum value histogram and the maximum difference histogram have a shape in which the frequency exists only in a limited density section (for example, 1-2 sections) as shown in the figure. Further, it can be considered that a document having a higher density value (pixel value) where the frequency of the maximum value histogram is larger is a bright document, and a document having a smaller value is a dark document. Further, regarding the maximum difference histogram, it can be considered that the larger the density value where the frequency is, the more chromatic original, and the smaller the density value, the achromatic original. For example, if the maximum value histogram has a frequency at one density value 255 and the maximum difference histogram has a frequency at one density value 0, it is determined that the document is a blank document.

Examples of histograms for a photographic paper photo original are shown in FIGS. 4B and 5B.
Since the photographic paper photographic document is expressed in various densities, both the maximum value histogram and the maximum difference histogram have shapes having frequencies in a wide range of density categories. In addition, regarding the maximum difference histogram, it is possible to consider a chromatic color document with a frequency in a wide range of density categories, and a monochromatic photographic paper photo document with a frequency in a limited density category. In particular, those having a frequency in a low density section can be regarded as an achromatic photographic paper photographic original. For example, if the maximum value histogram and the maximum difference histogram have frequencies in a wide density range, it is determined that the document is a color photographic paper photographic document.

Examples of histograms for character originals are shown in FIGS. 4 (c) and 5 (c).
Since the text document has a large background density, both the maximum value histogram and the maximum difference histogram have a shape similar to that of the plain document. However, in the maximum difference histogram, the frequency exists in the density division of the character part, and above all, the number of edge pixels due to the character exists, so that the distinction from the plain original can be clearly determined.

  Since halftone originals also have frequencies in various density categories, the maximum value histogram and the maximum difference histogram both have frequencies in a wide density range. However, since a halftone dot is counted as an edge in a halftone original, it can be distinguished from a photographic paper photo original.

  A case where the document type automatic determination unit 13 determines a plain document from another document type will be described.

  FIG. 6 is a block diagram showing the configuration of the document type automatic discrimination unit 13a that discriminates between a plain document and other document types. FIG. 7 is a flowchart showing the discrimination processing of the document type automatic discrimination unit 13a. FIG. 8 is a flowchart showing the document determination process.

  Parts that perform the same operations as those constituting the document type automatic discrimination unit 13 shown in FIG.

  First, a flag F used in the determination process described later is initialized, and F = 0 is set (step S20).

  Steps S21 to S34 are the same as steps S1 to S14 in the flowchart shown in FIG.

  The RGB signals input to the document type automatic determination unit 13a are processed in parallel with the processing in the average value calculation unit 21, pixel determination unit 22, calculation unit 23, and histogram creation unit 24, and the maximum density calculation unit 31 and the minimum The data is input to the density calculator 32 and the total density busyness calculator 33.

  The pixels determined by the pixel determination unit 22 as edge pixels are counted by the edge pixel counting unit 25, and the count value is output to the determination unit 26. The character / halftone pixel determination unit 35 performs a character / halftone pixel determination process for determining whether the pixel is a character pixel or a halftone pixel (step S35).

  Referring to FIG. 8, in the character / halftone pixel determination process, first, in the maximum density calculation unit 31 and the minimum density calculation unit 32, for example, the maximum density value in the 7 × 7 pixel block including the target pixel, and A minimum density value is calculated (steps S39 and S40). The maximum density difference calculator 34 calculates the maximum density difference using the calculated minimum density value and maximum density value (step S41).

  The total density busyness calculation unit 33 calculates a total density busyness that is the sum of absolute values of density differences between adjacent pixels in the 7 × 7 pixel block (step S42). The total density busyness is obtained, for example, in the main scanning direction and the sub-scanning direction, and these sums are used. Further, the calculated total density busyness is compared with the product of the character / halftone dot determination threshold given from the character / halftone pixel determination threshold setting unit 36 and the calculated maximum density difference, and the character area and the halftone dot are compared. The region / region is determined (step S43). Note that the character / halftone pixel determination can be executed, for example, according to the procedure described in Japanese Patent Application Laid-Open No. 2002-232708.

  Pixels determined to be character pixels are counted by the character pixel counting unit 37 (step S44), and pixels determined to be halftone pixels are counted by the halftone pixel counting unit 38 (step S45).

  Returning to FIG. 7, when the determination unit 26 determines that the document is not a blank document (step S36), the determination result that the document is a photographic paper photograph document (flag F = a, step S37) and the character count The document determination process is comprehensively performed using the number and the halftone dot count (step S38).

FIG. 9 is a flowchart showing the determination process.
First, the determination unit 26 compares the halftone dot count with the print photo original determination threshold (for example, 20% of the total number of pixels) set by the print photo original determination threshold setting unit 40 (step S51). If the halftone dot count is smaller than the print photo original determination threshold value, it is determined whether or not flag F = a (step S52).

If F = a, the determination unit 26 compares the character count number with the character document determination threshold value set by the character document determination threshold value setting unit 39 (for example, 10% of the total number of pixels) (step S53). If the character count is smaller than the character document determination threshold, it is determined that the document is a photographic paper photographic document (step S55). If the character count is greater than or equal to the character document determination threshold, it is determined that the document is a character photographic paper photographic document. (Step S56). If F = a, it is determined that the document is a character document (step S57).

  Further, even when the halftone dot count is equal to or greater than the print photo original determination threshold, the character count and the character original determination threshold set by the character original determination threshold setting unit 39 (for example, 10% of the total number of pixels) are set. A comparison is made (step S54). If the character count is smaller than the character document determination threshold, it is determined that the document is a printed photo document (step S58). If the character count is greater than or equal to the character document determination threshold, the character print photo document is determined. (Step S59).

  FIG. 10 is a block diagram showing a configuration of an image reading apparatus 6 according to another embodiment of the present invention.

  The image reading device 6 includes a color image input device 2 and a color image processing device 3a. The color image processing apparatus 3 a includes an A / D conversion unit 11, a shading correction unit 12, and a document type automatic determination unit 13.

  The color image input device (image reading means) 2 is composed of, for example, a scanner unit provided with a CCD, reads a reflected light image from an original as an RGB analog signal with the CCD, and inputs it to the color image processing device 3a. Is.

  The analog signal read by the color image input device 2 is sent through the color image processing device 3a in the order of the A / D conversion unit 11, the shading correction unit 12, and the document type automatic discrimination unit 13.

  The A / D converter 11 converts RGB analog signals into digital signals, and the shading correction unit 12 applies a color image input device to the digital RGB signals sent from the A / D converter 11. 2 performs processing for removing various distortions generated in the illumination system, the imaging system, and the imaging system. The shading correction unit 12 adjusts the color balance.

  In the automatic document type discrimination unit 13, the RGB signal (RGB reflectance signal) from which various distortions have been removed by the shading correction unit 12 and the color balance has been adjusted is employed in the color image processing apparatus 3 a such as a density signal. The signal is converted into a signal that can be easily handled by the image processing system, and it is determined whether the document is a plain original. The automatic document type discrimination unit 13 determines not only the plain original, but also the original type such as a character original, a printed photo original, or a character printed photo original in which characters and a printed photo are mixed. You may comprise so that discrimination may be performed.

  The image data and the document type determination signal output from the image reading device 6 are transmitted to a printer, a multifunction device, or a computer via a network.

  As another embodiment of the present invention, the above-described plain image discrimination processing is performed on a computer-readable recording medium in which program code (execution format program, intermediate code program, source program) of a program to be executed by a computer is recorded. It is also possible to record an image processing method to be performed.

  As a result, a recording medium on which a program code for performing the image processing method for determining the plain image is recorded can be provided in a portable manner.

  In the present embodiment, the recording medium may be a program medium such as a memory (not shown) such as a ROM itself because processing is performed by a microcomputer. However, it may be a program medium provided with a program code reading device as an external storage device and readable by inserting a recording medium therein.

  In any case, the stored program may be configured to be accessed and executed by the microprocessor, or in any case, the program code is read and the read program code is stored in the microcomputer. The program code may be downloaded to a program storage area (not shown) and the program code is executed. It is assumed that this download program is stored in the main device in advance.

  Here, 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, a CD-ROM / MO / MD / DVD, or the like. Semiconductors such as optical discs, IC cards (including memory cards) / optical cards, etc., or mask ROM, EPROM (Erasable Programmable Read Only Memory), EEPROM (Electrically Erasable Programmable Read Only Memory), flash ROM, etc. It may be a medium that carries a fixed program including a memory.

  In the present embodiment, since the system configuration is such that a communication network including the Internet can be connected, it may be a medium that fluidly carries a program so as to download a program code from the communication network. When the program code is downloaded from the communication network in this way, the download program may be stored in the main device in advance, or may be installed from another recording medium. The present invention can also be realized in the form of a computer data signal embedded in a carrier wave in which the program code is embodied by electronic transmission.

  The recording medium is read by a program reading device provided in a digital color image forming apparatus or a computer system, whereby the above-described image processing method is executed.

  The computer system includes an image input device such as a flatbed scanner, a film scanner, and a digital camera, a computer that performs various processes such as the above image processing method by loading a predetermined program, and a CRT display that displays the processing results of the computer. An image display device such as a liquid crystal display and a printer that outputs the processing results of the computer to paper or the like. Furthermore, a network card, a modem, and the like are provided as communication means for connecting to a server or the like via a network.

DESCRIPTION OF SYMBOLS 1 Image forming apparatus 2 Color image input device 3 Color image processing device 4 Color image output device 5 Operation panel 11 A / D conversion part 12 Shading correction part 13 Document type automatic discrimination part 14 Input gradation correction part 15 Area separation processing part 16 Color correction unit 17 Black generation and under color removal unit 18 Spatial filter processing unit 19 Output tone correction unit 20 Tone reproduction processing unit

Claims (7)

In an image processing apparatus for determining whether image data is image data obtained by reading a plain original composed only of pixels having a single color density based on image data composed of a plurality of pixels,
An average value calculation unit that calculates an average value of pixel values in a pixel block including a plurality of pixels including a target pixel for each color component, and uses the calculated average value as a pixel value of the target pixel;
Based on the average value of each color component calculated by the average value calculation unit, the maximum value of the average value between each color component and the maximum difference of the average value are obtained for each pixel of interest, and each density of the maximum value and the maximum difference is obtained. A histogram creation unit that creates each histogram with the number of pixels for the classification as a frequency value;
For each color component, density information regarding density is calculated in a pixel block including a plurality of pixels including the target pixel, and whether the target pixel is an edge pixel by comparing the calculated density information with a predetermined density threshold value. A pixel determination unit that counts the number of pixels determined as edge pixels, and
Density classification in which the number of pixels determined as edge pixels by the pixel determination unit is equal to or less than a pixel number threshold, and the histogram of the maximum value and the histogram of maximum difference created by the histogram creation unit are equal to or greater than a predetermined frequency value And a determination unit that determines that the image data is obtained by reading a plain original when both of the density division numbers are equal to or less than the division threshold value.
In an image processing apparatus for determining whether image data is image data obtained by reading a plain original composed only of pixels having a single color density based on image data composed of a plurality of pixels,
An average value calculation unit that calculates an average value of pixel values in a pixel block including a plurality of pixels including a target pixel for each color component, and uses the calculated average value as a pixel value of the target pixel;
Based on the average value of each color component calculated by the average value calculation unit, the maximum value of the average value between each color component and the maximum difference of the average value are obtained for each pixel of interest, and each density of the maximum value and the maximum difference is obtained. A histogram creation unit that creates each histogram with the number of pixels for the classification as a frequency value;
In the histogram of the maximum value and the histogram of the maximum difference created by the histogram creation unit, the number of density categories that are equal to or greater than a predetermined frequency value is obtained, both of these density categories are equal to or less than the threshold value, A determination unit that determines that the image data is obtained by reading a plain original when the number of maximum difference histogram original density widths representing the entire number of sections equal to or greater than a predetermined frequency value satisfies a predetermined value. A featured image processing apparatus.   An image forming apparatus comprising the image processing apparatus according to claim 1. In an image processing method for determining whether image data is image data obtained by reading a plain original composed only of pixels of a single color density based on image data composed of a plurality of pixels,
For each color component, an average value calculation step of calculating an average value of pixel values in a pixel block including a plurality of pixels including the target pixel, and using the calculated average value as a pixel value of the target pixel;
For each color component, density information regarding density is calculated in a pixel block including a plurality of pixels including the target pixel, and whether the target pixel is an edge pixel by comparing the calculated density information with a predetermined density threshold value. And a pixel determination step for counting the number of pixels determined to be edge pixels,
Based on the average value for each color component calculated in the average value calculation step, the maximum value of the average value between each color component and the maximum difference of the average value are obtained for each pixel of interest, and each density of the maximum value and the maximum difference is obtained. A histogram creation step of creating each histogram with the number of pixels for the classification as a frequency value;
Density classification in which the number of pixels determined as edge pixels in the pixel determination step is equal to or less than a pixel number threshold, and the histogram of the maximum value and the histogram of maximum difference created in the histogram creation step are equal to or greater than a predetermined frequency value An image processing method, comprising: a determination step of determining the image data obtained by reading a plain original when both of the number of density categories are equal to or less than a threshold value. In an image processing method for determining whether image data is image data obtained by reading a plain original composed only of pixels of a single color density based on image data composed of a plurality of pixels,
For each color component, an average value calculation step of calculating an average value of pixel values in a pixel block including a plurality of pixels including the target pixel, and using the calculated average value as a pixel value of the target pixel;
Based on the average value for each color component calculated in the average value calculation step, the maximum value of the average value between each color component and the maximum difference of the average value are obtained for each pixel of interest, and each density of the maximum value and the maximum difference is obtained. A histogram creation step of creating each histogram with the number of pixels for the classification as a frequency value;
In the histogram creation step, the maximum value histogram and the maximum difference histogram are used to determine the number of density categories that are equal to or greater than a predetermined frequency value, and both the number of density categories are equal to or less than the threshold value, A determination step of determining that the image data is obtained by reading a plain original when the number of maximum difference histogram document density widths representing the entire number of sections equal to or greater than a predetermined power value satisfies a predetermined value. An image processing method.   An image processing program for causing a computer to execute the image processing method according to claim 4 or 5.   A computer-readable recording medium on which an image processing program for causing a computer to execute the image processing method according to claim 4 or 5 is recorded.

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