JP2009060450A - Information processing apparatus, image processing method, and image processing program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To leave stripe-like noise without lacking it in image reduction processing. <P>SOLUTION: In an information processing apparatus 1, an evaluation value arithmetic processing unit 12 calculates, based on a pixel value of a target pixel and pixel values of pixels around the target pixel, an evaluation value representing a probability for the pixel value of each of pixels constituting an image captured by a scanner to contain stripe-like noise for each pixel. An image reduction processing unit 13 performs image reduction processing for preferentially leaving a pixel having an evaluation value equal to or higher than a predetermined value among the evaluation values of pixels calculated by the evaluation value arithmetic processing unit 12. <P>COPYRIGHT: (C)2009,JPO&INPIT

Description

  The present invention relates to an information processing apparatus, an image processing method, and an image processing program for processing an image.

  A task of displaying a reduced version of image data obtained by a line scanner or the like on the display, and visually confirming whether or not the image data has been obtained normally, and then passing the image data to the subsequent processing steps. is there. When an image is acquired by a line scanner or the like, vertical line noise having a width of 1 to 2 pixels is likely to occur. This linear noise may be lost during image reduction processing. In such a case, the operator cannot confirm the linear noise on the display.

There are various techniques for detecting and extracting linear features in an image. For example, Patent Document 1 describes that a streak defect is detected by a streak defect detection filter processing step and a step of detecting a streak defect based on a detection value obtained in this step. Patent Document 2 describes that a ruled line is accurately extracted from a blurred image by using both an original image and a reduced image.
JP-A-2005-346300 JP 2000-259826 A

  However, the techniques of Patent Document 1 and Patent Document 2 are techniques for detecting and extracting linear features with high accuracy, and that linear noise is lost during image reduction processing. It is not a technology to prevent. For this reason, even if the techniques of Patent Document 1 and Patent Document 2 are used, it is not possible to prevent the loss of linear noise during the image reduction process, and the operator can perform the operation from the reduced image displayed on the display. I cannot confirm linear noise.

  The present invention has been made in view of the above circumstances, and is an information processing apparatus, an image processing method, and an image processing that realize image processing capable of leaving linear noise without being lost during image reduction processing. The purpose is to provide a program.

  The information processing apparatus according to the present invention provides, for each pixel, an evaluation value that represents the probability that the pixel value of each pixel constituting the image includes linear noise, and the pixel value of the target pixel and the pixel values of surrounding pixels. And an image reduction process for preferentially leaving a pixel having an evaluation value equal to or higher than a predetermined value among the evaluation values of the pixels calculated by the evaluation value calculation means. Means.

  An image processing method according to the present invention is an image processing method applied to an information processing apparatus that processes an image, and an evaluation value that represents a probability that a pixel value of each pixel constituting the image includes linear noise, For each pixel, calculation is performed based on the pixel value of the target pixel and the pixel values of the surrounding pixels, and among the calculated evaluation values of each pixel, priority is given to a pixel having an evaluation value equal to or greater than a predetermined value. The remaining image reduction processing is performed.

  An image processing program according to the present invention is an image processing program for processing an image, and an evaluation value indicating a probability that a pixel value of each pixel constituting the image includes linear noise is determined for each pixel. A function of calculating based on the pixel value of the pixel and the pixel values of surrounding pixels, and image reduction processing that preferentially leaves pixels having an evaluation value equal to or greater than a predetermined value among the calculated evaluation values of each pixel The function to be performed is realized by a computer.

  According to the present invention, it is possible to leave the linear noise without being lost during the image reduction processing.

  Embodiments of the present invention will be described below with reference to the drawings.

  FIG. 1 is a block diagram showing an example of the configuration of an information processing system according to an embodiment of the present invention.

  The information processing system includes an information processing device 1, a line scanner 2, a display device (display) 3, a printing device (printer) 4, a communication device 5, and an input device (keyboard, mouse) 6.

  The information processing apparatus 1 is realized as a personal computer (PC), for example, and performs image reduction processing based on the image of the paper sheet S read by the line scanner 2 to display or print a reduced image. Processing such as storage and transfer can be performed. In particular, the information processing apparatus 1 performs an image reduction process so that line noise such as vertical lines generated when an image is acquired by the line scanner 2 is not lost during the image reduction process, and the linear noise remains. A reduced image can be displayed on the display device 3.

  The line scanner 2 is a device that generates information described on the paper sheet S as a color or monochrome image by optically scanning the surface of the paper sheet S and performing photoelectric conversion. The light source is configured to irradiate light on the leaves S, and a self-scanning CCD image sensor that receives the reflected light and converts it into an electrical signal. An image signal generated by the line scanner 2 is supplied to the information processing apparatus 1.

  The display device 3 displays a reduced image obtained by reducing the image of the paper sheet S output from the information processing device 1.

  The printing apparatus 4 prints a reduced image obtained by reducing the image of the paper sheet S output from the information processing apparatus 1.

  The communication device 5 transmits the image of the paper sheet S output from the information processing device 1 to another information processing device in order to deliver it to the subsequent processing step.

  The input device 6 is for operating the information processing device 1, changes settings such as various threshold values and coefficients used in calculations in each processing unit, and the type of data output by the output processing unit 14 And the output destination of data can be switched.

  The information processing apparatus 1 includes an image storage unit D11, an evaluation value storage unit D12, and a reduced image storage unit D13 as functions for storing various types of information. These are realized using a storage medium such as a hard disk or a memory. In addition, the information processing apparatus 1 includes an image capturing unit 11, an evaluation value calculation processing unit (evaluation value calculation unit) 12, an image reduction processing unit (image reduction processing unit) 13, and an output processing unit 14 as various processing functions. Have These functions are realized as a computer program that can be executed by a processor such as a CPU (Central Processing Unit).

  The image storage unit D11 stores the image captured by the image capture unit 11. The image stored in the image storage unit D11 is used in the evaluation value calculation processing unit 12 and the image reduction processing unit 13.

  The evaluation value storage unit D12 stores the evaluation value calculated by the evaluation value calculation processing unit 12. The evaluation value stored in the evaluation value storage unit D12 is used in the image reduction processing unit 13.

  The reduced image storage unit D13 stores a reduced image after the image is reduced by the image reduction processing unit 13. The reduced image stored in the reduced image storage unit D13 is used in the output processing unit 14.

  The image capturing unit 11 captures an image of the paper sheet S acquired by the line scanner 2. The image capturing unit 11 stores the captured image in the image storage unit D11.

  The evaluation value calculation processing unit 12 is an evaluation value representing the probability that the pixel value of each pixel constituting the image captured by the image capturing unit 11 (that is, the image stored in the image storage unit D11) includes linear noise. Is calculated for each pixel based on the pixel value of the target pixel and the pixel values of the surrounding pixels. For example, the evaluation value of each pixel is calculated based on the degree of variation of a plurality of difference vectors representing the difference between the color of the target pixel and the surrounding pixels. The evaluation value calculation processing unit 12 stores the calculated evaluation value in the evaluation value storage unit D12.

  The image reduction processing unit 13 selects pixels having an evaluation value equal to or greater than a predetermined value from among the evaluation values of the pixels calculated by the evaluation value calculation processing unit 12 (that is, evaluation values stored in the evaluation value storage unit D12). The image reduction process to be left preferentially is performed. The image reduction processing unit 13 stores the reduced image obtained as a result of the image reduction processing in the reduced image storage unit D13.

  The output processing unit 14 displays the reduced image generated by the image reduction processing unit 13 (that is, the reduced image stored in the reduced image storage unit D13) on the display device 3, causes the printing device 4 to print, or displays the reduced image. After the operator confirms the reduced image of the paper sheet S output to the device 3 or the printing device 4, the original image before the reduction process (that is, the image stored in the image storage unit D11) is displayed as the communication device 5 (or , A removable storage device) to another information processing apparatus.

  FIG. 2 is a block diagram showing an example of the configuration of various functions included in the evaluation value calculation processing unit 12 shown in FIG.

  The evaluation value calculation processing unit 12 includes a difference vector storage unit D21 and a variation analysis result storage unit D22 as functions for storing various types of information. The evaluation value calculation processing unit 12 includes, as various processing functions, a difference vector calculation unit (difference vector calculation unit) 21, a variation analysis unit (variation analysis unit) 22, and an evaluation value calculation unit (evaluation value calculation unit) 23. Have

  The difference vector storage unit D21 stores the difference vector calculated by the difference vector calculation unit 21. The difference vector stored in the difference vector storage unit D21 is used in the variation analysis unit 22.

  The variation analysis result storage unit D22 stores the variation analysis result generated by the variation analysis unit 22. The variation analysis result stored in the variation analysis result storage unit D22 is used in the evaluation value calculation unit 23.

  The difference vector calculation unit 21 represents a difference between the color of the target pixel and the colors of surrounding pixels based on the image captured by the image capture unit 11 (that is, the image stored in the image storage unit D11). A plurality of difference vectors are calculated. The difference vector calculation unit 21 stores the calculated plurality of difference vectors in the difference vector storage unit D21.

  The variation analyzing unit 22 sets the plurality of difference vectors calculated by the difference vector calculating unit 21 (that is, the difference vectors stored in the difference vector storage unit D21) so that the sum of the norms of the plurality of difference vectors becomes 1. The sum of the distances between the end points of the difference vectors when the adjusted start points of the plurality of difference vectors are aligned and the center of gravity indicating the average position of these end points is calculated. The variation analysis unit 22 stores the calculated sum of distances in the analysis result storage unit D22 as a variation analysis result.

  The evaluation value calculation unit 23 calculates a value obtained by inverting the sum of the distances calculated by the variation analysis unit 22 (that is, the variation analysis result stored in the analysis result storage unit D22) as an evaluation value. . The evaluation value calculation unit 23 stores the calculated individual evaluation values in the evaluation value storage unit D12.

  FIG. 3 is a block diagram showing an example of the configuration of various functions included in the image reduction processing unit 13 shown in FIG.

  The image reduction processing unit 13 includes an image determination result storage unit D31 as a function of storing information. The image reduction processing unit 13 includes an image determination unit (pixel determination unit) 31 and a pixel selection unit (pixel selection unit) 32 as various processing functions.

  The image determination result storage unit D31 stores the pixel determination result determined by the image determination unit 31. The pixel determination result stored in the image determination result storage unit D31 is used in the pixel selection unit 32.

  The image determination unit 31 sets an evaluation value equal to or greater than a predetermined value in an area serving as a unit when the image captured by the image capture unit 11 (that is, the image stored in the image storage unit D11) is reduced. It is determined whether or not there is a pixel having. The image determination unit 31 stores the determined result in the pixel determination result storage unit D31.

  The pixel selection unit 32 includes one or more pixels having an evaluation value equal to or greater than a predetermined value based on the determination result by the image determination unit 31 (that is, the determination result of each pixel stored in the pixel determination result storage unit D31). In the case where the pixel having the highest evaluation value is selected as the pixel to be left after the image reduction process among the pixels in the region, the image is selected from the pixels in the region when none exists. A pixel present at a position closest to the position of the pixel after the reduction process is selected as a pixel to be left after the image reduction process. The pixel selection unit 32 stores a reduced image composed of the selected pixels in the reduced image storage unit D13.

  Next, the operation of the information processing apparatus 1 will be described with reference to FIG.

  The image capturing unit 11 captures an image of the paper sheet S acquired by the line scanner 2 (step 101).

  Next, the evaluation value calculation processing unit 12 calculates, for each pixel, an evaluation value representing the probability that the pixel value of each pixel constituting the image captured by the image capturing unit 11 includes linear noise such as a vertical line. Calculation is performed based on the pixel value of the target pixel and the pixel values of surrounding pixels (step 102).

  Next, the image reduction processing unit 13 performs image reduction processing that preferentially leaves pixels having an evaluation value equal to or greater than a predetermined value among the evaluation values of each pixel calculated by the evaluation value calculation processing unit 12 (step 103). ). The reduced image generated by the image reduction processing unit 13 is displayed on the display device 3, for example.

  Next, the details of the processing of step 102 (evaluation value calculation) in FIG. 4 will be described with reference to FIG.

  First, the difference vector calculation unit 21 calculates a difference vector between a target pixel to be evaluated and surrounding pixels. For example, nine pixel values p (i-2, j-2), p (i, j-2), p (i + 2, j-2), p (i-2, j), p (i, j), p (i + 2, j), p (i-2, j + 2), p (i, j + 2), p (i-2, j + 2) Using these, the six difference vectors v0, v1, v2, v3, v4, v5 shown in FIG. 7 are calculated (step 201). This difference vector may be defined in any manner as long as it is a vector representing a color difference between a pixel at a position assumed to be a vertical line and a pixel assumed not to be a surrounding vertical line.

  Next, the variation analysis unit 22 adjusts each difference vector so that the sum of the norms (lengths) of the six difference vectors is 1. Then, the center of gravity of each adjusted difference vector (the average position of the end points of each difference vector when the start points of the respective difference vectors are aligned) is obtained, and the total distance between each adjusted difference vector and the center of gravity is calculated. Obtain (step 202). The smaller the total distance calculated here, the smaller the variation of the difference vector, that is, the target pixel has a strong property as a vertical line.

  Next, the evaluation value calculation unit 23 sets the distance sum as an evaluation value obtained by reversing the positive and negative values (step 203). It can be said that a pixel whose evaluation value is equal to or greater than a certain threshold value has a strong property as a vertical line.

  When a monochrome image is handled instead of a color image, the difference between the pixels in the vertical line portion and the surrounding pixels is a scalar instead of a vector, but the evaluation value can be calculated by a similar process.

  Next, the details of the processing in step 103 (image reduction) in FIG. 4 will be described with reference to FIGS.

  In the image reduction process, for example, as shown in FIG. 9, one pixel is selected from several candidates (9 in the illustrated example) of the original image, and this is displayed as a pixel of the reduced image. The evaluation value is used for pixel selection at this time.

  First, the pixel determination unit 31 determines whether there is a pixel whose evaluation value is equal to or greater than a certain threshold among the candidate pixels (step 501).

  Next, when there is no pixel whose evaluation value is equal to or greater than the threshold value, the pixel selection unit 32 selects a pixel whose position after the reduction conversion is closest to the pixel position of the reduced image (step 502). On the other hand, if there is one or more pixels whose evaluation value is equal to or greater than the threshold value, the pixel having the highest evaluation value is selected (step 503). As a result, a reduced image is formed by the selected pixels.

  As described above in detail, according to the present embodiment, even if an image is reduced and displayed, it is possible to display without missing linear noise, so that there is no oversight in visual confirmation by an operator. Is obtained.

  In addition, according to the present embodiment, since pixels for reduction display are selected using an evaluation value for determining the presence or absence of linear noise in the image, lines with a desired threshold value or more are included in the reduced image. Can be displayed.

  Further, according to the present embodiment, in the evaluation value calculation process, a variation degree of a plurality of difference vectors representing a color difference between a pixel assumed to be a line and a pixel assumed not to be a surrounding line is used. Therefore, it is not necessary to perform separate processing for the line pixel value and the background pixel value, and the evaluation value can be obtained by one type of processing.

  Further, according to the present embodiment, in the evaluation value calculation process, the plurality of difference vectors are adjusted so that the sum of the norms of the plurality of difference vectors is 1, so that it is not affected by the brightness, A highly accurate evaluation value can be obtained.

  Further, according to the present embodiment, in the image reduction process, the pixel selection method is changed depending on whether or not there is a pixel whose evaluation value is equal to or greater than the threshold among the candidate pixels to be displayed. A line can be reliably displayed in a portion where pixels like lines are present, and can be displayed in other portions without causing deterioration in image quality such as jagged edges.

  The various processing procedures according to the present invention described in the above-described embodiments are stored in a storage medium (for example, a magnetic disk, an optical disk, or a semiconductor memory) that can be read by a computer (information processing apparatus) as a computer program. If necessary, it may be read and executed by the processor. Such a computer program can also be distributed by transmitting from one computer to another computer via a communication medium.

  The present invention is not limited to the above-described embodiments as they are, and can be embodied by modifying the constituent elements without departing from the scope of the invention in the implementation stage. In addition, various inventions can be formed by appropriately combining a plurality of components disclosed in the embodiment. For example, some components may be deleted from all the components shown in the embodiment. Furthermore, constituent elements over different embodiments may be appropriately combined.

1 is a block diagram showing an example of the configuration of an information processing system according to an embodiment of the present invention. The block diagram which shows an example of a structure of the various functions contained in the evaluation value calculation process part 12 shown in FIG. The block diagram which shows an example of a structure of the various functions contained in the image reduction process part 13 shown in FIG. The flowchart which shows operation | movement of the information processing apparatus 1 shown in FIG. The flowchart which shows the detail of a process of step 102 (evaluation value calculation) in FIG. The figure for demonstrating the method of calculating the difference vector of the object pixel used as evaluation object, and the surrounding pixel. The figure which shows the example of the six difference vectors calculated. 5 is a flowchart showing details of processing in step 103 (image reduction) in FIG. 4. The figure which shows the example which selects 1 pixel from the 9 pixel candidates of an original image in an image reduction process.

Explanation of symbols

  DESCRIPTION OF SYMBOLS 1 ... Information processing apparatus, 2 ... Line scanner, 3 ... Display apparatus, 4 ... Printing apparatus, 5 ... Communication apparatus, 6 ... Input device, 11 ... Image capture part, 12 ... Evaluation value calculation process part, 13 ... Image reduction Processing unit, 14 ... Output processing unit, 21 ... Difference vector calculation unit, 22 ... Variation analysis unit, 23 ... Evaluation value calculation unit, 31 ... Image determination unit, 32 ... Pixel selection unit, D11 ... Image storage unit, D12 ... Evaluation Value storage unit, D13 ... reduced image storage unit, D21 ... difference vector storage unit, D22 ... variation analysis result storage unit, D31 ... image determination result storage unit.

Claims (6)

Evaluation value calculation means for calculating, for each pixel, an evaluation value representing the probability that the pixel value of each pixel constituting the image includes linear noise based on the pixel value of the target pixel and the pixel values of surrounding pixels. When,
Image reduction processing means for performing image reduction processing that preferentially leaves pixels having evaluation values greater than or equal to a predetermined value among the evaluation values of each pixel calculated by the evaluation value calculation means. Processing equipment.   The evaluation value calculation means calculates an evaluation value of each pixel based on a degree of variation of a plurality of difference vectors representing a difference between a target pixel color and a surrounding pixel color. Item 4. The information processing apparatus according to Item 1. The evaluation value calculation means includes:
Difference vector calculation means for calculating a plurality of difference vectors representing the difference between the color of the target pixel and the colors of the surrounding pixels;
The plurality of difference vectors calculated by the difference vector calculating means are adjusted so that the sum of norms of the plurality of difference vectors is 1, and the difference vectors obtained when the start points of the adjusted plurality of difference vectors are aligned. Variation analysis means for calculating the sum of the distance between the end point and the center of gravity indicating the average position of these end points;
The information processing apparatus according to claim 1, further comprising: an evaluation value calculation unit that calculates a value obtained by inverting the sum of the distances calculated by the variation analysis unit as the evaluation value. The image reduction processing means includes
Pixel determining means for determining the presence or absence of a pixel having an evaluation value equal to or greater than a predetermined value in a region serving as a unit when the image is reduced;
As a result of the determination by the pixel determination means, if there is one or more pixels having an evaluation value equal to or greater than a predetermined value, the pixel having the highest evaluation value among the pixels in the area is left after the image reduction process If no pixel is selected, a pixel that is selected as a pixel to be left after the image reduction process is selected from the pixels in the area that are closest to the pixel position after the image reduction process. The information processing apparatus according to claim 1, further comprising: means. An image processing method applied to an information processing apparatus for processing an image,
An evaluation value representing the probability that the pixel value of each pixel constituting the image includes linear noise is calculated for each pixel based on the pixel value of the target pixel and the pixel values of surrounding pixels.
An image processing method comprising: preferentially leaving a pixel having an evaluation value equal to or greater than a predetermined value among the calculated evaluation values of each pixel. An image processing program for processing an image,
A function of calculating, for each pixel, an evaluation value representing the probability that the pixel value of each pixel constituting the image includes linear noise based on the pixel value of the target pixel and the pixel values of surrounding pixels;
An image processing method that causes a computer to realize a function of performing image reduction processing that preferentially leaves pixels having an evaluation value equal to or greater than a predetermined value among the calculated evaluation values of each pixel.

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