Image segmentation method with enhanced noise elimination function
First Claim
1. A method for segmenting an image formed of a plurality of pixels, comprising the steps of:
- detecting edges of the image, the edge-detected image including real edges and noise;
scanning rows of the image to discriminate between the real edges and the noise, eliminating the noise of the image;
projecting the image; and
segmenting the image, wherein the scanning step includes the steps of;
discriminating between real spaces and discontinuous edges;
connecting the discontinuous edges between two adjacent edges;
generating a first value by counting pixels corresponding to the real edges and the noise;
generating a second value by counting pixels corresponding to the real spaces and the discontinuous edges; and
comparing the first value and the second value with predetermined first threshold and second threshold, respectively, to verify the counted pixels according to the results of the comparison.
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Abstract
Segmentation of a character-containing image, made by placing a dark mark against a light background, is accomplished by establishing a vertical pixel projection for each pixel column in the image. For more exact segmentation, the image is horizontally scanned in each row of the image after detecting edges of characters. The scanned results and thresholds are compared to verify whether edges and spaces of the scanned row are noise or discontinuous edges. The thresholds correlate with neighboring row data of the image. According to the results of the comparison, the discontinuous edges are connected and the noise is eliminated. Thereby, the character-containing image can be segmented into each character without segmentation errors.
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Citations
14 Claims
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1. A method for segmenting an image formed of a plurality of pixels, comprising the steps of:
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detecting edges of the image, the edge-detected image including real edges and noise;
scanning rows of the image to discriminate between the real edges and the noise, eliminating the noise of the image;
projecting the image; and
segmenting the image, wherein the scanning step includes the steps of;
discriminating between real spaces and discontinuous edges;
connecting the discontinuous edges between two adjacent edges;
generating a first value by counting pixels corresponding to the real edges and the noise;
generating a second value by counting pixels corresponding to the real spaces and the discontinuous edges; and
comparing the first value and the second value with predetermined first threshold and second threshold, respectively, to verify the counted pixels according to the results of the comparison. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A method for segmenting an image formed of a plurality of pixels, comprising the steps of:
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detecting edges and noise of each row of the image;
discriminating between the edges and the noise detected;
detecting spaces and discontinuous edges of each row of the image;
discriminating between the spaces and the discontinuous edges detected;
eliminating the noise discriminated from the edges;
connecting the discontinuous edges discriminated from the spaces;
projecting the image; and
segmenting the image, wherein the step of discriminating includes the steps of;
generating a first value by counting pixels corresponding to the edges;
generating a second value by counting pixels corresponding to the spaces;
comparing the first value and the second value with predetermined first threshold and second threshold generated by summing up a threshold of a previous row, and an average number of pixels verified to edges and spaces in the previous row, respectively, to verify the counted pixels according to the results of the comparison. - View Dependent Claims (11, 12, 13, 14)
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Specification