JP4867564B2 - Image reading device - Google Patents

Description

  The present invention relates to a technique for detecting adhesion of dust at an image reading position for reading an image from a document and removing a noise image caused by the dust from a read image.

The image reading device reads an image of a document conveyed by the conveying device through a platen glass using a line sensor such as a CCD at a predetermined reading position. However, if dust adheres to the reading position on the platen glass, a streaky noise image resulting from the dust enters the read image. In order to solve such problems, Patent Document 1 reads a background plate before reading a document, compares the density of the document image with the density of the background plate, detects a noise image caused by dust, A technique for removing this is disclosed.
JP-A-2005-64913

  The technique described in Patent Document 1 detects a noise image for an image represented by image data composed of three color components of red (R), green (G), and blue (B), and performs subsequent image processing. However, if gamma correction is performed as a contrast correction, a noise image having a small density difference that cannot be detected as a noise image becomes conspicuous. This problem will be specifically described with reference to FIG. FIG. 11 is a diagram showing input / output characteristics in general gamma correction. The horizontal axis represents the density input value, and the vertical axis represents the density output value. The density is expressed by 256 gradations, and the density increases from 0 to 255. As shown in the figure, the input / output characteristic has a downwardly convex curve. That is, the density is corrected so that the contrast becomes larger in the region where the density is higher. When gamma correction is performed on the image data according to the input / output characteristics shown in FIG. 11, in the low density region of the image, the change in the density of the output image signal is small with respect to the density change of the input image signal. Become. On the other hand, in the high density region, the change in the density of the output image signal is larger than the change in the density of the input image signal. That is, in the image after gamma correction, the density in the high density region is stretched and the contrast is enhanced, so that a noise image that is not detected by the technique described in Patent Document 1 becomes conspicuous.

  Therefore, a method of detecting a noise image from an image after performing gamma correction is also conceivable. In this case, as described above, the change in the density of the output image signal is small with respect to the density change in the low density region. Patent Document 1 uses a method of detecting the presence of a noise image based on a difference in density from a white background board. However, the density of the background board, which is a reference for comparison, and a low density caused by paper dust, for example, are used. When the difference from the density of the noise image is relatively small, the difference is further reduced by the gamma correction, so that there is a possibility that the noise image cannot be detected.

  The present invention has been made in view of the above-described circumstances, and an object of the present invention is to accurately detect the presence of dust at a reading position of a document, and to remove a noise image resulting therefrom from the read image.

In order to achieve the above object, the present invention provides a predetermined low density existing within a predetermined range based on the density of each pixel included in image data obtained by reading an image on a document in units of scanning lines. First detection means for detecting, as a noise pixel, a predetermined number or less of pixels that have a density that deviates by more than a threshold value on the higher density side than the density of a pixel group in the area and that are continuously arranged in the scan line; The image after the gamma correction is performed by the gamma correction means for performing the gamma correction on the image data so that the change of the output density with respect to the change of the input density becomes larger than that before the correction in the predetermined high density range. based on the density of each pixel included in the image data has a density that deviates more than the threshold to a low density side than the concentration of the pixel group of the high density region existing within a predetermined range, and, in the scan line A second detection unit that detects a predetermined number of pixels arranged in succession as noise pixels, a noise pixel detected by the first detection unit, and a noise pixel detected by the second detection unit; An image reading apparatus comprising: a noise removing unit that corrects the density and outputs image data including the corrected density of the noise pixel.

  In the image reading apparatus, the first detection unit and the second detection unit have the same position on a plurality of main scanning lines including the main scanning line of interest and continuing in the sub-scanning direction. The average value of the density of the pixels at a certain position is obtained, and the average value at a certain position has a density difference equal to or greater than a threshold with respect to the average value at a position away from the position by a predetermined distance in the main scanning direction. In this case, the pixel at the position on the main scanning line of interest is detected as a noise pixel.

  Further, in this image reading apparatus, the noise removing unit pays attention when a noise pixel is detected from the focused main scanning line by the first detection unit or the second detection unit. You may make it correct | amend the density | concentration of the pixel in the same position as the said noise pixel in these main scanning lines other than a main scanning line.

  Further, in the image reading apparatus, the noise removing unit has a predetermined noise removing condition among the noise pixels detected by the first detecting unit and the noise pixels detected by the second detecting unit. You may make it correct | amend the density | concentration of the noise pixel to satisfy | fill. In a preferred aspect of the image processing apparatus, the noise removal condition may be a condition that determines whether or not to correct the density of the noise pixel according to the position of the noise pixel. Alternatively, it may be specified based on the coordinate value and color difference of each pixel in an arbitrary color space defined by a component related to lightness and a component related to hue or saturation.

  According to the image reading apparatus of the present invention, it is possible to accurately detect the presence of dust at a reading position of a document and remove a noise image resulting from the detection from the read image.

Embodiments of the present invention will be described below with reference to the drawings.
FIG. 1 is a block diagram showing a configuration of an image reading apparatus 100 according to an embodiment of the present invention. In FIG. 1, a CCD unit 1 is means for reading a document conveyed by a conveyance device (not shown). In the present embodiment, the CCD unit 1 is driven by a drive signal from the CCD drive circuit 2 so that three reading positions from the most upstream side reading position to the most downstream side reading position on the document conveyance path are obtained. The original image is read and analog image signals R, G, and B are output.

  FIG. 2 shows the configuration of the document transport device and the configuration of the optical system from the reading position on the document transport path to the CCD unit 1. In FIG. 2, the document 13 is conveyed by the drawing roller 14 to the conveyance roller 15 one by one. The conveyance roller 15 changes the document conveyance direction and conveys the document 13 toward the contact glass 16. The document 13 conveyed in this manner is pressed against the contact glass 16 by the back platen 18 and is finally discharged from the conveying device by the discharge roller 19. The three reading positions from the upstream reading position to the downstream reading position are provided on the contact glass 16, respectively. Each original image at each reading position is changed by the first mirror 20, the second mirror 21, and the third mirror 22, and is reduced by the lens 23, and the three CCD line sensors 1 A constituting the CCD unit 1. 1B, 1C.

  Here, the CCD line sensor 1 </ b> C represents the B color components of N pixels arranged in a straight line in a direction (main scanning direction) across the document conveyance direction at the most upstream reading position C on the contact glass 16. The image signal B is output. Further, the CCD line sensor 1B is aligned in a straight line in the main scanning direction at a reading position B that has traveled downstream from the reading position on the most upstream side by a distance of four main scanning lines (hereinafter simply referred to as four lines). An image signal G representing the G color component of N pixels is output. Then, the CCD line sensor 1A has the R color of N pixels arranged in a straight line in the main scanning direction at the reading position A on the most downstream side further downstream by 4 lines from the reading position corresponding to the image signal G. An image signal R representing the component is output.

  In FIG. 1, a signal processing system A including a sample and hold circuit 3A, an output amplifier circuit 4A, an A / D conversion circuit 5A, and a shading correction circuit 6A, a sample and hold circuit 3B, and an output amplifier circuit are provided at the subsequent stage of the CCD unit 1. 4B, a signal processing system B composed of an A / D conversion circuit 5B and a shading correction circuit 6B, and a signal processing system C composed of 3C to 6C are provided. The signal processing systems A to C are signal processing systems respectively corresponding to the image signal R, the image signal G, and the image signal B obtained at the reading positions A, B, and C, respectively.

  Here, the analog image signals R, G, and B obtained from the CCD unit 1 are sampled by the sample hold circuits 3A to 3C, respectively, and then amplified to appropriate levels by the output amplifier circuits 4A to 4C. Digital image data R, G, and B are respectively converted by the D conversion circuits 5A to 5C. These digital image data R, G, and B are corrected by the shading correction circuits 6A to 6C in accordance with the sensitivity variations of the CCD line sensors 1A to 1C and the light quantity distribution characteristics of the optical system. The above is the outline of each signal processing system corresponding to the image signals R, G, and B.

  The output delay circuits 7B and 7C delay the image data G and B output from the shading correction circuits 6B and 6C by delay times corresponding to 4 lines and 8 lines, respectively, and output them as image data in phase with the image data R. . The dust detection circuit 8 detects a pixel affected by dust based on the image data output from the shading correction circuit 6A and the output delay circuits 6B and 6C, and outputs dust detection data indicating the location of the pixel. Means. Hereinafter, the pixel affected by the dust is referred to as “noise pixel”. The noise removal circuit 9 is means for removing noise pixels from the image data R, G, B based on the dust detection data from the dust detection circuit 8 and outputting them to the image processing circuit 10.

The image processing circuit 10 performs image processing required for a device (digital copying machine, scanner, etc.) in which the image reading device 100 is mounted on the image data output from the noise removal circuit 9, such as enlargement / reduction processing, background It is means for performing removal processing, binarization processing, and the like. The CPU 11 is means for controlling each part of the image reading apparatus 100. Specifically, the CPU 11 sets the drive period of the CCD unit 1 performed by the CCD drive circuit 2, controls the gain of the output amplifier circuits 4A to 4C, the shading correction circuits 6A to 6C, the dust detection circuit 8, the noise. The removal circuit 9 and the image processing circuit 10 are controlled.
The overall configuration of the image reading apparatus 100 has been described above.

Next, the dust detection circuit 8 will be described with reference to FIG. The dust detection circuit 8 includes an averaging circuit 80, a gamma correction circuit 81, a first dust detection circuit 82, a second dust detection circuit 83, and a dust determination circuit 84.
The averaging circuit 80 has a memory for storing the image data R output from the shading correction circuit 6A and the image data G and B output from the output delay circuits 7B and 7C for a predetermined number of lines, respectively. An average value of the densities of the pixels at the same position in the image data is calculated. FIG. 4 is a diagram for explaining processing performed on the image data by the averaging circuit 80, taking the case of the image data R as an example. In the following description, one line includes N pixels, and image data for one pixel is referred to as pixel data.

  In this image reading apparatus 100, image data R representing R components of N pixels read for each main scanning line by the CCD line sensor 1A is sequentially output from the shading correction circuit 6A and supplied to the averaging circuit 80. . When the pixel data R of one pixel k is supplied to the averaging circuit 80, the averaging circuit 80 outputs the pixel data of the pixel k and the pixel k− one line (that is, N pixels) before the pixel k. N pixel data, pixel data of pixel k-2N that is two lines (ie, 2N pixels) before pixel k, and pixel data of pixel k-3N that is three lines (ie, 3N pixels) before pixel k Read the pair. That is, the averaging circuit 80 has the density of the pixel k of the target line L shown in FIG. 4 and the pixels k-N, k at the same position on the main scanning line as the pixel k in the three lines immediately before it. An average value of a total of four concentrations of -2N and k-3N is obtained. A pixel indicating the average value of the density is referred to as an “averaged pixel”, and FIG. 4 illustrates an averaged pixel k1 as an example. The pixel data for one averaged pixel is referred to as “averaged pixel data”. As shown in the lowermost stage of FIG. 4, one line can be formed by arranging N averaged pixels. Similarly, the averaging circuit 80 obtains averaged pixel data for the image data G and B. The averaging circuit 80 outputs the set of R, G, and B averaged pixel data obtained in this way to the gamma correction circuit 81 and the first dust detection circuit 82 as “first image data”.

  The gamma correction circuit 81 performs gamma correction on the first image data output from the averaging circuit 80 according to the input / output characteristics as shown in FIG. Then, the gamma correction circuit 81 supplies the image data after the gamma correction to the second dust detection circuit 83 as “second image data”.

  The first dust detection circuit 82 performs dust detection processing on the first image data output from the averaging circuit 80. Specifically, the first dust detection circuit 82 pays attention to one of the averaged pixels in FIG. 4 (for example, the averaged pixel k1 in FIG. 4), and the density of the averaged pixel is 8 pixels before that. It is determined whether or not the density of the averaged pixel k2 has a density difference equal to or greater than a predetermined threshold value (threshold value T1). If the density difference is equal to or greater than the threshold T1, the first dust detection circuit 82 detects the pixel (pixel k1 in the example of FIG. 4) located on the target line as a noise pixel, and “1” as dust detection data. Is smaller than the threshold value T1, “0” is output as dust detection data. The dust detection data “1” means that it is affected by dust, and the dust detection data “0” means that it is not affected by dust. Hereinafter, the dust detection data output from the first dust detection circuit 82 is referred to as “first dust detection data”.

  The second dust detection circuit 83 performs dust detection processing on the second image data output from the gamma correction circuit 81. Similar to the above-described first dust detection circuit 82, the second dust detection circuit 83 has a predetermined density of the averaged pixel subjected to gamma correction with respect to the density of the averaged pixel k2 eight pixels before that. It is determined whether or not there is a density difference equal to or greater than a threshold (referred to as threshold T2). If the density difference is equal to or greater than the threshold value T2, the second dust detection circuit 83 detects the pixel (pixel k in the example of FIG. 4) located on the target line as a noise pixel, and “1” as dust detection data. Is smaller than the threshold value T1, “0” is output as dust detection data. Here again, the dust detection data “1” means that it is affected by dust, and the dust detection data “0” means that it is not affected by dust. Hereinafter, the dust detection data output by the second dust detection circuit 83 is referred to as “second dust detection data”.

Next, the processing of the first dust detection circuit 82 and the second dust detection circuit 83 will be described more specifically.
FIG. 5 shows the first image data supplied to the first dust detection circuit 82 as a solid line, and the second image data supplied to the second dust detection circuit 83 as a broken line. FIG. 9A shows a case where the density of the averaged pixel groups p1 and p2 continuous in the main scanning direction is higher than that of the neighboring pixels in a relatively low density region. On the other hand, FIG. 7B shows a case where the density of the continuous averaging pixel groups p1 and p2 is lower than that of the neighboring pixels in a relatively high density region. In FIG. 5, it is assumed that the density is represented by 256 bits.

  As shown by the solid line in FIG. 5A, in the first image data supplied to the first dust detection circuit 82, the density of the averaged pixel group p1 is greatly changed to the higher density side than the surroundings. . On the other hand, as indicated by a broken line, in the second image data supplied to the second dust detection circuit 83, the density of the averaged pixel group p1 is greatly changed to a higher density side than the surroundings. The degree is smaller than that of the first image data.

  When the average pixel group p1 is affected by dust having a higher density than the surrounding density (for example, black dust), as shown in FIG. 5A, the density appearing in the first image data. The change (solid line) is larger than the density change (broken line) appearing in the second image data. This is because the change in the output density of the first image data before the gamma correction is made with respect to the change of the input density in the low density region, compared with the second image data after the gamma correction is made. This is because it is large. In other words, according to the first dust detection circuit 82, the density difference due to the averaging pixel that is the dust detection condition described above easily exceeds the threshold T1, and the dust detection accuracy in the low density region is high. On the other hand, according to the second dust detection circuit 83, the density difference does not easily exceed the threshold value T2, and the dust detection accuracy in the low density region is low. Therefore, the first dust detection circuit 82 is suitable for detecting light-colored dust such as paper dust from a relatively low density (bright color) region.

  Next, as shown by a broken line in FIG. 5B, in the second image data supplied to the second dust detection circuit 83, the density of the average pixel group p2 is lower than the surrounding density. It has changed greatly. On the other hand, as shown by the solid line, in the first image data supplied to the first dust detection circuit 82, the density of the averaged pixel group p1 is greatly changed to the lower density side than the surrounding density. The degree of change is smaller than that of the second image data.

  When the average pixel group p2 is affected by dust having a lower density than the surrounding density (for example, white dust), as shown in FIG. 5B, the density appearing in the second image data. The change (broken line) is larger than the density change (solid line) appearing in the first image data. This is because the change in the output density of the second image data after the gamma correction is changed with respect to the change of the input density in the high density region, compared to the first image data before the gamma correction is performed. This is because it is large. In other words, according to the second dust detection circuit 83, the density difference due to the averaged pixel that is the dust detection condition described above easily exceeds the threshold value T2, and the detection accuracy of the noise pixel in the high density region is high. On the other hand, according to the first dust detection circuit 82, the density difference is unlikely to exceed the threshold value T1, and the noise pixel detection accuracy in the high density region is low. Therefore, the second dust detection circuit 83 is suitable for detecting noise pixels from a relatively high density (dark color) region.

  However, the maximum number of pixels in which noise pixels detected in this way are continuous is two pixels. The reason for this will be explained. The line image may be included in the image on the document, but the thinnest line segment image is only about 3 pixels thick. To do. The dust determination circuit 84 has less than two pixels of dust detection data “1” in the main scanning direction so that it is not erroneously determined that such a very thin line segment image is affected by dust. It is determined that the pixel is a noise pixel only when it is continuous, and is not determined as a noise pixel when three or more pixels of dust detection data “1” continue in the main scanning direction. However, the condition of “2 pixels” as the number of continuous pixels that is a criterion for determining this noise pixel is merely an example, and the number of continuous pixels depends on the resolution at the time of image reading, the size of paper dust generated from the paper, and the like. It is desirable to set it appropriately in consideration.

3 uses the first dust detection data output from the first dust detection circuit 82 and the second dust detection data output from the second dust detection circuit 83. The dust determination circuit 84 shown in FIG. The noise pixel is determined. Specifically, the dust determination circuit 84 is one of first dust detection data output from the first dust detection circuit 82 and second dust detection data output from the second dust detection circuit 83. A pixel having a value of “1” is determined as a noise pixel. As described above, this may occur when the dust in the low concentration range is detected by the first dust detection circuit 82 even if the dust is not detected by the second dust detection circuit 83. This is because the reverse is also possible for dust in the concentration range.
In the dust determination circuit 84, such processing is performed in units of R, G, and B colors.

  The noise removal circuit 9 corrects the density based on the noise pixels represented by the first dust detection data and the second dust detection data output from the dust detection circuit 8, and reads the noise pixels from the document. Remove from image. Here, the process of the noise removal process performed by the noise removal circuit 9 will be described with reference to FIG. FIG. 6 shows the contents of the process for removing pixels including noise performed by the noise removal circuit 9.

  The noise removing circuit 9 extends the image data R output from the shading correction circuit 6A and the image data G and B output from the output delay circuits 7B and 7C over the three lines immediately before the target line. An image data buffer for temporary storage and a dust detection data buffer for temporarily storing each dust detection data output from the dust detection circuit 8 over the three lines described above are provided. In FIG. 6, only the stored contents of the image data buffer 91A corresponding to the R color and the image data buffer 91C corresponding to the B color are shown in order to prevent the drawing from becoming complicated. Illustration is omitted.

  The noise removal circuit 9 determines a pixel to be subjected to noise removal processing based on the position of the noise pixel detected by the dust detection circuit 8. Specifically, the noise removal circuit 9 detects the dust detection data of the target pixel (for example, the pixel k in FIG. 4) read from the dust detection data buffer and the main scanning lines for three lines immediately before the target pixel. One of the dust detection data of the pixels at the same position (that is, the pixels k-N, k-2N, and k-3N in the three main scanning lines continuous in the sub-scanning direction) is “1”. If there is, the noise removal processing is performed on the pixel at the same position as the noise pixel in the target line and the three lines immediately before the target line. That is, when a pixel including noise is detected from the target line, the noise removal circuit 9 performs noise removal processing retroactively to the pixels in the previous three lines, and any of the pixels in the previous three lines. If noise is detected, it is determined that the noise pixel also reaches the target line, and noise removal processing is performed. This is based on the fact that the dust detection circuit 8 performs dust detection processing on the averaged pixel data obtained from the four lines of pixel data. That is, if noise is detected from any pixel, it is relatively likely that streak-like noise pixels are generated in the sub-scanning direction of these four lines.

Next, a method of noise removal processing performed by the noise removal circuit 9 will be specifically described.
In the embodiment, the noise removal circuit 9 pays attention to a pixel on which noise removal processing is performed, and specifies a pixel to be replaced with the pixel of interest for the pixel data B, G, and R. Then, pixel replacement is performed by placing the identified pixel at the position of the target pixel. For example, it is assumed that the noise removal circuit 9 determines to perform noise removal processing on, for example, the i-th pixel Bij in the main scanning direction and the j-th pixel Bij in the sub-scanning direction based on the dust detection data corresponding to the B color. In this case, the noise removal circuit 9 replaces the pixel data of the pixel Bij with pixel data of an appropriate B color pixel around it. For this purpose, since it is necessary to search for pixel data suitable for use in the replacement, the noise removal circuit 9 obtains the replacement pixel data as follows.

  First, the noise removal circuit 9 includes a noise pixel and a pixel adjacent to the pixel out of pixels in a range of 17 pixels in the main scanning direction centered on the pixel and 3 lines in the sub-scanning direction. An area excluding two pixels in the main scanning direction is defined as a “substitution pixel selection target area”. Next, the noise removal circuit 9 refers to the pixel Rij at the same position as the pixel Bij in the image data buffer corresponding to a color different from the color of the pixel Bij, for example, the image data buffer 91A, and is closest to this pixel. A pixel is selected from R color pixels in the same area as the replacement pixel selection target area. Next, the noise removal circuit 9 reads out the pixel data of the B color pixel located at the same position as the R color pixel selected in this way from the image data buffer 91C, and uses this pixel data for the pixel Bij in the image data buffer 91C. Replace pixel data.

  Such processing is performed on all the pixels that the noise removal circuit 9 determines to perform noise removal processing, so that noise pixels caused by dust are removed from the image data in the image data buffer. Then, the image data on which the noise removal processing has been performed is sent to the image processing circuit 10.

  In this process, two pixels in the main scanning direction adjacent to the target pixel are excluded from the replacement pixel selection target area. If the target pixel is a noise pixel, the pixel adjacent to the target pixel includes noise. This is because even if the pixel is not detected, it may be slightly affected by the noise pixel. Even when the pixel of interest is not a noise pixel, it is desirable to exclude adjacent pixels in the same manner because the noise pixels are close and are subject to noise removal processing.

  According to the above-described embodiment, the image reading apparatus according to the present invention performs the process of detecting the noise pixels for the image data before and after the gamma correction is performed, so that the dust at the reading position is accurately detected. Therefore, dust can be detected with high accuracy regardless of the density of the surrounding image area.

  The present invention can be implemented in various forms. For example, the above-described embodiment may be modified as follows. Note that, among the configurations of the image reading apparatuses, the same components as those shown in FIG.

  In the above-described embodiment, the image reading apparatus 100 includes the averaging circuit 80. However, a configuration without the averaging circuit may be employed. FIG. 7 is an example of a block diagram illustrating a configuration of an image reading apparatus 100a that does not include an averaging circuit. FIG. 8 is an example of a block diagram illustrating a configuration of a dust detection circuit 8a included in the image reading apparatus 100a. is there. In this case, as shown in FIGS. 7 and 8, the pixel data group for one line output from the shading correction circuit 6A and the output delay circuits 7B and 7C is supplied to the first dust detection circuit 82 of the dust detection circuit 8a. And supplied to the gamma correction circuit 81. Then, the pixel data group subjected to gamma correction by the gamma correction circuit 81 is supplied to the second dust detection circuit 83. Then, for each line of pixel data, dust detection processing is performed by the first dust detection circuit 82 and the second dust detection circuit 83, and the subsequent processing is continued. As described above, the averaging circuit 80 is provided in order to accurately detect streak-like noise pixels. Therefore, since it is determined whether or not the pixel is a noise pixel by adopting a configuration without this averaging circuit, for example, a noise removal process is performed only on a pixel in which noise is detected. In such a case, it is suitable.

  Further, although the dust detection circuit 8a of the image reading apparatus 100a described above has the gamma correction circuit 81, an image forming apparatus such as a general digital copying machine or a scanner on which the image reading apparatus is mounted, or the image processing apparatus itself. Has a gamma correction function, the gamma correction circuit may not be provided inside the dust detection circuit, which is a feature of the embodiment and the modification. FIG. 9 is an example of a block diagram illustrating a configuration of the image reading apparatus 100 in which the gamma correction circuit 12 is mounted outside the dust detection circuit. The configuration of the dust detection circuit 8b in this case is the same as that in the case where the gamma correction circuit 81 shown in FIG. 8 is located outside the dust detection circuit 8a. As shown in FIG. 9, the pixel data group for one line output from the shading correction circuit 6A and the output delay circuits 7B and 7C is supplied to the first dust detection circuit 82 of the dust detection circuit 8b, and gamma correction is performed. It is supplied to the circuit 12. On the other hand, the pixel data group that has been supplied to the gamma correction circuit 12 and subjected to gamma correction is supplied to the second dust detection circuit 83 of the dust detection circuit 8b and also to the noise removal circuit 9. Then, noise removal processing is performed on the pixel data group that has been subjected to gamma correction and is supplied to the noise removal circuit 9, and the subsequent processing is continued. In this way, even if the dust detection circuit 8b does not have a gamma correction circuit as a contrast correction means for performing dust detection, dust detection processing is performed using the gamma correction function of the installed device. be able to.

In the above-described embodiment, the noise image is detected from the image data (first and second image data) based on the image on the document. However, the image data generated by reading the background plate is further detected. May also be used.
Specifically, the document is not conveyed, the image is read in a state where there is no document at the reading position corresponding to each of the R, G, and B colors, and the third image data obtained as a result is given to the dust detection circuit 8. It is done. The dust detection circuit 8 generates dust detection data (referred to as third dust detection data) based on the averaged pixels of the third image data. At this time, the detection of noise pixels based on the third image data may be performed by the first dust detection circuit 82 of the dust detection circuit 8 or the second dust detection circuit 83.
Also in the third dust detection data, the dust detection data of the noise pixel is “1”, and the dust detection data of the pixel that is not the noise pixel is “0”. Then, the dust determination circuit 84 determines whether a pixel in which either the first dust detection data or the second dust detection data is “1” and the third dust detection data is also “1”. judge. Then, the dust determination circuit 84 may determine pixels that are continuous within 2 pixels in the main scanning direction as noise pixels among the pixels for which the third dust detection data is also “1”. In this way, since the presence of a noise image can be detected based on the difference in density from the background plate, the accuracy of noise pixel detection is further improved.

  In the above-described embodiment, average pixel data is obtained from pixels at the same position on a certain pixel on the target line and three main scanning lines immediately preceding in the sub-scanning direction, and this average is obtained. The noise pixel on the target line is detected based on the normalized pixel data. However, the positional relationship between the target line and the main scanning line for obtaining the averaged pixel data and the number of the main scanning lines are not limited to the contents described in the embodiment. For example, when obtaining averaged pixel data, a target line and a plurality of main scanning lines immediately after the target line may be used, or a target line and a plurality of main scan lines immediately before and after the target line may be used. Scan lines may be used. Further, in the embodiment, the number of main scanning lines when obtaining the averaged pixel data is 4 lines including the attention line, but this may be 3 lines or less including the attention line, or 5 lines or more. It is good. In short, if averaged pixel data is obtained from a target line and a plurality of main scanning lines that are continuous in the sub-scanning direction when viewed from the target line, and noise pixels on the target line are detected based on the averaged pixel data. Good.

Further, in the above-described embodiment, when a noise pixel is detected from the pixel of interest or any one of the three immediately preceding lines, the noise removal circuit 9 performs noise removal processing on all of these pixels. However, the pixels for which noise removal processing is performed may be limited to the following cases. For example, in the image area, information with relatively high importance is often included near the center, but such frequency is relatively low at the edge. In addition, the frequency of the end portion is less than that in the vicinity of the center in the degree to which the viewer gazes. Therefore, the noise removal condition based on the pixel position of the noise pixel is specified, and for the noise pixel detected at the predetermined pixel position, the density of the noise pixel is corrected, and other noise pixels remain. The noise removal process may not be performed on a noise pixel at a position that does not cause much problem.
Alternatively, noise removal processing may be performed only on noise pixels that are relatively conspicuous. For example, image data lightness L, hue a, and saturation b obtained by converting R, G, and B into a CIELAB color space defined by components related to lightness and components related to hue or saturation are used. . Specifically, when the coordinate values L, a, and b in the CIELAB color space of the noise pixel and surrounding pixels take predetermined values and the color difference is equal to or greater than a threshold value, it is determined that the noise pixel is easily noticeable. Then, noise removal processing may be performed. Therefore, a noise removal condition based on the coordinate value and color difference of the CIELAB color space may be designated to remove only noise pixels that are determined to be conspicuous.
Thus, if the density of only noise pixels satisfying a predetermined noise removal condition is corrected, a process of performing noise removal processing by storing necessary data in the image data buffer or dust detection data buffer of the noise removal circuit 9 Therefore, the time required for the noise removal process can be shortened.

Further, the method of dust detection processing performed by the first dust detection circuit 82 and the second dust detection circuit 83 is not limited to the method described in the embodiment, and any method may be used. For example, the following method may be used in order for the first dust detection circuit 82 and the second dust detection circuit 83 (hereinafter referred to as dust detection circuit) to detect noise pixels on the low density region side.
When detecting the density of each pixel, the dust detection circuit pays attention to a certain pixel p1 on the main scanning line as shown in FIG. 10, and is located within a predetermined range on the front side in the scanning direction from the position of the target pixel p1. The average value a1 of the density of the group (here, 16 pixel groups Pf located on the front side in the scanning direction) is calculated. If the calculated density average value a1 of the pixel group Pf is equal to or greater than a predetermined threshold, the dust detection circuit compares the density average value a1 of the pixel group Pf with the density z1 of the target pixel p1. When the density z1 of the target pixel p1 deviates from the density average value a1 of the pixel group Pf by the threshold value s1 or more on the low density side, the dust detection circuit indicates that there is a density step on the low density side. judge. The reason for confirming whether the average density value a1 of the pixel group Pf is equal to or greater than a predetermined threshold is to confirm whether the density is such that a pixel group that changes significantly can be extracted. It is.
Next, the dust detection circuit calculates an average value a2 of the densities of the four pixel groups Pb that are continuous from pixels that are two pixels behind in the scanning direction from the target pixel p1. The dust detection circuit compares the density z1 of the pixel of interest p1 with the average density a2 of the pixel group Pb, and the density z1 of the pixel of interest p1 is lower than the density average value a2 of the pixel group Pb by the threshold s2. If there is a deviation, it is determined that “there is a density step on the high density side”. The dust detection circuit determines the pixel of interest p1 determined to have a step on the low density side and the high density side as a noise pixel. Further, the dust detection circuit uses the density z2 of the adjacent pixel p2 existing one pixel behind the target pixel p1 determined to be a noise pixel as the density average value a1 of the pixel group Pf and the density average value a2 of the pixel group Pb. Compare. As a result of this comparison, the density z2 of the pixel of interest p2 deviates from the density average value a1 of the pixel group Pf by a threshold value s1 or more to the low density side, and the threshold value s2 or more from the density average value a2 of the pixel group Pf to the low density side. If there is a divergence, the dust detection circuit determines that the pixel of interest p2 is also a noise pixel. If the density z2 of the target pixel p2 does not satisfy these density conditions, only the target pixel p1 is determined as a noise pixel.
In this way, it is possible to more accurately detect noise pixels that are affected by white dust such as paper dust.

1 is a block diagram illustrating a configuration of an image reading apparatus according to an embodiment of the present invention. FIG. 2 is a diagram illustrating a configuration of an optical system from a document conveying device and a document reading position to a CCD unit. It is a block diagram which shows the structure of a dust detection circuit. It is a figure explaining the process which the averaging circuit of the dust detection circuit performs. It is a figure explaining a mode that the density change of the pixel group for 1 line is detected by the dust detection circuit. It is a figure explaining the process which a noise removal circuit performs. It is a block diagram which shows the structure of an image reading apparatus. It is a block diagram which shows the structure of a dust detection circuit. It is a block diagram which shows the structure of an image reading apparatus. It is a figure explaining the mechanism which determines an abnormal pixel based on the density change of the pixel group for 1 line. It is a figure which shows the input / output characteristic in a gamma correction.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 ... CCD part, 2 ... CCD drive circuit, 7B, 7C ... Output delay circuit, 8, 8a, 8b ... Dust detection circuit, 9 ... Noise removal circuit, 10 ... Image processing circuit, 80 ... Averaging circuit, 12, 81 ... Gamma correction circuit, 82 ... First dust detection circuit, 83 ... Second dust detection circuit, 84 ... Dust determination circuit, 100, 100a, 100b ... Image reading device.

Claims (6)

Based on the density of each pixel included in the image data obtained by scanning the image on the original in units of scanning lines, the density is higher than the density of a pixel group in a predetermined low density area existing within a predetermined range. First detection means for detecting, as noise pixels, a predetermined number or less of pixels that have a density that deviates more than a threshold and that are continuously arranged in the scan line;
As the change in output density with respect to a change in input density in advance high concentration range that is determined is greater than before the correction, images after the gamma correction has been performed by the gamma correction means for performing gamma correction to the image data Based on the density of each pixel included in the data, it has a density that deviates by more than a threshold to the lower density side than the density of the pixel group in the high density area existing within a predetermined range, and continuously in the scan line Second detection means for detecting a predetermined number or less of pixels arranged as noise pixels;
Noise removing means for correcting the density of the noise pixel detected by the first detecting means and the noise pixel detected by the second detecting means and outputting image data including the corrected density of the noise pixel; An image reading apparatus comprising: The first detection unit and the second detection unit are configured to detect the density of pixels at the same position on a plurality of main scanning lines including the main scanning line of interest and continuing in the sub-scanning direction. An average value is obtained, and when the average value at a certain position has a density difference equal to or greater than a threshold with respect to the average value at a position away from the position by a predetermined distance in the main scanning direction, The image reading apparatus according to claim 1, wherein a pixel at the position on the main scanning line is detected as a noise pixel.   When a noise pixel is detected from the main scanning line of interest by the first detecting unit or the second detecting unit, the noise removing unit is configured to detect the plurality of pixels other than the main scanning line of interest. The image reading apparatus according to claim 2, wherein the density of a pixel located at the same position as the noise pixel is corrected in the main scanning line. The noise removing unit corrects the density of a noise pixel that satisfies a predetermined noise removing condition among the noise pixels detected by the first detecting unit and the noise pixels detected by the second detecting unit. The image reading apparatus according to claim 1, wherein the image reading apparatus is an image reading apparatus. The image reading apparatus according to claim 4, wherein the noise removal condition is a condition that determines whether or not to correct a density of the noise pixel according to a position of the noise pixel. The noise removal condition is specified based on a coordinate value and a color difference of each pixel in an arbitrary color space defined by a component related to lightness and a component related to hue or saturation. Item 5. The image reading apparatus according to Item 4.

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