Method for image binarization
First Claim
Patent Images
1. A method for image binarization, comprising:
- receiving a gray-level input image comprising a plurality of pixels having respective gray-level values;
analyzing variations among the gray-level values of the pixels in the input image so as to determine image statistics with respect to gaps between the gray-level values of neighboring pixels;
responsive to the image statistics, determining a lower threshold and an upper threshold, which is greater than the lower threshold by a selected difference;
assigning a first binary value to the pixels in the gray-level image having gray-level values above the upper threshold and a second binary value to the pixels in the gray-level image having gray-level values below the lower threshold; and
processing the pixels in an intermediate group having gray-level values between the lower and upper thresholds so as to determine optimal assignments of the pixels in the intermediate group to the first and second binary values.
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Abstract
A method for binarizing a gray-level input image including a plurality of pixels having respective gray-level values. A lower threshold and an upper threshold are determined. A first binary value is assigned to the pixels in the gray-level image having gray-level values above the upper threshold, and a second binary value is assigned to the pixels in the gray-level image having gray-level values below the lower threshold. The pixels in an intermediate group having gray-level values between the lower and upper thresholds are processed so as to determine optimal assignments of the pixels in the intermediate group to the first and second binary values.
50 Citations
27 Claims
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1. A method for image binarization, comprising:
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receiving a gray-level input image comprising a plurality of pixels having respective gray-level values;
analyzing variations among the gray-level values of the pixels in the input image so as to determine image statistics with respect to gaps between the gray-level values of neighboring pixels;
responsive to the image statistics, determining a lower threshold and an upper threshold, which is greater than the lower threshold by a selected difference;
assigning a first binary value to the pixels in the gray-level image having gray-level values above the upper threshold and a second binary value to the pixels in the gray-level image having gray-level values below the lower threshold; and
processing the pixels in an intermediate group having gray-level values between the lower and upper thresholds so as to determine optimal assignments of the pixels in the intermediate group to the first and second binary values. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. A method for image binarization, comprising:
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receiving a gray-level input image comprising a plurality of pixels having respective gray-level values;
analyzing variations among the gray-level values of the pixels in the input image so as to find gaps between the gray-level values of neighboring pixels;
responsive to the gaps that are found, determining a lower threshold and an upper threshold, which is greater than the lower threshold by a selected difference;
assigning a first binary value to the pixels in the gray-level image having gray-level values above the upper threshold and a second binary value to the pixels in the gray-level image having gray-level values below the lower threshold; and
processing the pixels in an intermediate group having gray-level values between the lower and upper thresholds so as to determine optimal assignments of the pixels in the intermediate group to the first and second binary values, wherein the thresholds are selected so as to preserve the gaps that are significant in preference to the gaps that are not significant in an output image made up of the assigned binary values, wherein the significant gaps are defined as those whose absolute magnitude is greater than the selected difference between the upper and lower threshold, and wherein the thresholds are selected so as to maximize a merit score computed for multiple different pairs of upper and lower thresholds, wherein the score correlates positively with the number of significant gaps preserved in the output image by the selected thresholds, and correlates negatively with the number of gaps that are not significant that are preserved and the number of significant gaps that are not preserved in the output image by the selected thresholds.
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13. A method for processing a gray-level input image, which includes a plurality of pixels having respective gray-level values, the method comprising:
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analyzing variations among the gray-level values of the pixels in the input image;
responsive to the analyzed variations, determining a lower threshold and an upper threshold, which is greater than the lower threshold by a selected gap size;
assigning a first binary value to the pixels in the gray-level image having gray-level values above the upper threshold and a second binary value to the pixels in the gray-level image having gray-level values below the lower threshold; and
generating an output image, in which the pixels assigned the first and second binary values are represented by their respective binary values, and the pixels in an intermediate group having gray-level values between the lower and upper thresholds are represented by their respective gray-level values. - View Dependent Claims (14, 15, 16)
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- 17. Apparatus for image binarization, comprising an image processor, which is coupled to receive a gray-level input image comprising a plurality of pixels having respective gray-level values, and which is adapted to analyze variations among the gray-level values of the pixels in the input image so as to determine image statistics with respect to gaps between the gray-level values of neighboring pixels, and responsive to the statistics, to determine a lower threshold and an upper threshold, which is greater than the lower threshold by a selected difference, to assign a first binary value to the pixels in the gray-level image having gray-level values above the upper threshold and a second binary value to the pixels in the gray-level image having gray-level values below the lower threshold, and to process the pixels in an intermediate group having gray-level values between the lower and upper thresholds so as to determine optimal assignments of the pixels in the intermediate group to the first and second binary values.
- 22. Apparatus for processing a gray-level input image, which includes a plurality of pixels having respective gray-level values, the apparatus comprising an image processor, which is adapted to analyze variations among the gray-level values of the pixels in the input image and, responsive to the analyzed variations, to determine a lower threshold and an upper threshold, which is greater than the lower threshold by a selected gap size, and to assign a first binary value to the pixels in the gray-level image having gray-level values above the upper threshold and a second binary value to the pixels in the gray-level image having gray-level values below the lower threshold, thus to generate an output image, in which the pixels assigned the first and second binary values are represented by their respective binary values, and the pixels in an intermediate group having gray-level values between the lower and upper thresholds are represented by their respective gray-level values.
- 25. A computer software product for processing an input image, comprising a computer-readable medium having program instructions stored therein, which instructions, when read by a computer, cause the computer to receive a gray-level input image comprising a plurality of pixels having respective gray-level values, to analyze variations among the gray-level values of the pixels in the input image so as to determine image statistics with respect to gaps between the gray-level values of neighboring pixels, and responsive to the statistics, to determine a lower threshold and an upper threshold, which is greater than the lower threshold by a selected difference, to assign a first binary value to the pixels in the gray-level image having gray-level values above the upper threshold and a second binary value to the pixels in the gray-level image having gray-level values below the lower threshold, and to process the pixels in an intermediate group having gray-level values between the lower and upper thresholds so as to determine optimal assignments of the pixels in the intermediate group to the first and second binary values.
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27. A computer software product for processing a gray-level input image, which includes a plurality of pixels having respective gray-level values, the product comprising a computer-readable medium having program instructions stored therein, which instructions, when read by a computer, cause the computer to analyze variations among the gray-level values of the pixels in the input image and, responsive to the analyzed variations, to determine a lower threshold and an upper threshold, which is greater than the lower threshold by a selected gap size, to assign a first binary value to the pixels in the gray-level image having gray-level values above the upper threshold and a second binary value to the pixels in the gray-level image having gray-level values below the lower threshold, and to generate an output image, in which the pixels assigned the first and second binary values are represented by their respective binary values, and the pixels in an intermediate group having gray-level values between the lower and upper thresholds are represented by their respective gray-level values.
Specification