Feature recognition using loose gray scale template matching
First Claim
1. A method for feature recognition using a method for matching a plurality of templates with a received image comprising:
- (a) receiving an image comprised of gray-scale image data;
(b) generating a two-dimensional window of the received gray-scale image data, the two-dimensional window having a target gray-scale pixel and a plurality of surrounding gray-scale pixels, each gray-scale pixel being associated with a pixel of received gray-scale image data in the two-dimensional window;
(c) determining a plurality of looseness intervals for one template of a plurality of templates, each looseness interval being a difference between a gray-scale pixel associated with the two-dimensional window and a template gray scale pixel from the template and corresponding to the pixel location in the two-dimensional window;
(d) determining a template looseness interval value for the template based upon the determined plurality of looseness intervals;
(e) comparing the determined template looseness interval value to a threshold looseness interval value, the threshold looseness interval value being a maximum allowable value for the determined template looseness interval value that indicates a loosely matched template;
(f) determining, based upon the comparison between the determined template looseness interval value and the threshold looseness interval, which template of the plurality of templates loosely matches the two-dimensional window of received gray-scale image data, the loosely matched template being a template wherein the determined template looseness interval value associated therewith is equal to a non-zero value and the threshold looseness interval value is equal to a non-zero value, an exactly matched template being a template wherein the associated determined looseness interval value is equal to a zero value and the threshold looseness interval value is equal to a zero value; and
(g) outputting an identifier associated with the loosely matched template such that the identifier indicates a recognized image feature.
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Abstract
What is presented is a method for feature recognition using loose-gray-scale template matching including at least an initial point for locating within the received image a plurality of pixel points in gray-scale surrounding an initial point. The method has the steps of first locating the initial point and the plurality of pixel points to define feature boundaries and then generating a looseness interval about the located initial point with template information being associated therewith. The next step involves determining which one of a plurality of templates for fitting fits within a threshold looseness interval, and then outputting a signal associated with that recognized feature.
55 Citations
20 Claims
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1. A method for feature recognition using a method for matching a plurality of templates with a received image comprising:
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(a) receiving an image comprised of gray-scale image data;
(b) generating a two-dimensional window of the received gray-scale image data, the two-dimensional window having a target gray-scale pixel and a plurality of surrounding gray-scale pixels, each gray-scale pixel being associated with a pixel of received gray-scale image data in the two-dimensional window;
(c) determining a plurality of looseness intervals for one template of a plurality of templates, each looseness interval being a difference between a gray-scale pixel associated with the two-dimensional window and a template gray scale pixel from the template and corresponding to the pixel location in the two-dimensional window;
(d) determining a template looseness interval value for the template based upon the determined plurality of looseness intervals;
(e) comparing the determined template looseness interval value to a threshold looseness interval value, the threshold looseness interval value being a maximum allowable value for the determined template looseness interval value that indicates a loosely matched template;
(f) determining, based upon the comparison between the determined template looseness interval value and the threshold looseness interval, which template of the plurality of templates loosely matches the two-dimensional window of received gray-scale image data, the loosely matched template being a template wherein the determined template looseness interval value associated therewith is equal to a non-zero value and the threshold looseness interval value is equal to a non-zero value, an exactly matched template being a template wherein the associated determined looseness interval value is equal to a zero value and the threshold looseness interval value is equal to a zero value; and
(g) outputting an identifier associated with the loosely matched template such that the identifier indicates a recognized image feature. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
(h) determining from a plurality of identifiers a recognized global image feature.
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4. The method as in claim 3, wherein the recognized global image feature may a global feature from a group of global features including financial documents, secure documents, bonds, stamps, or passports.
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5. The method as in claim 1, further comprising:
(h) increasing the contrast of the recognized feature based upon the outputted identifier.
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6. The method as in claim 1, further comprising:
(h) darkening the recognized feature based upon the outputted identifier.
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7. The method as in claim 1, further comprising:
(h) thinning the recognized feature based upon the outputted identifier.
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8. The method as in claim 1, wherein the recognized image feature is an adjacent colored edged.
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9. The method as in claim 1, wherein the determined plurality of looseness intervals are determined from various color separations.
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10. The method as claimed in claim 1, wherein the determined looseness interval value for the template is the average looseness interval value determined from the plurality of determined looseness intervals.
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11. The method as in claim 1, further comprising:
(h) using, when more than one template loosely matches the two-dimensional window of received gray-scale image data, an arbitration process to select the most preferred loosely matched template.
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12. The method as in claim 1, further comprising:
(h) creating an image plane being composed of the outputted identifiers.
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13. A method for feature recognition using a method for matching a plurality of templates with a received image comprising:
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(a) receiving an image comprised of gray-scale image data;
(b) generating a two-dimensional window of the received gray-scale image data, the two-dimensional window having a target gray-scale pixel and a plurality of surrounding gray-scale pixels, each gray-scale pixel being associated with a pixel of received gray-scale image data in the two-dimensional window;
(c) determining a plurality of looseness intervals for one template from a plurality of templates, each looseness interval being a difference between a gray-scale pixel associated with the two-dimensional window and a template gray scale pixel from the template and corresponding to the pixel location in the two-dimensional window;
(d) comparing each non-zero looseness interval of the plurality of looseness intervals with a threshold looseness interval to determine a looseness interval number for the template, the looseness interval number being equal to how many non-zero looseness intervals within the set of looseness intervals are less than the threshold looseness interval;
(e) selecting the template of the plurality of templates having a greatest associated looseness interval number as the template that loosely matches the two-dimensional window of received gray-scale image data; and
(f) outputting an identifier associated with the loosely matched template such that the identifier indicates a recognized image feature. - View Dependent Claims (14, 15, 16, 17, 18, 19, 20)
(g) increasing the contrast of the recognized feature based upon the outputted identifier.
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16. The method as in claim 13, further comprising:
(g) darkening the recognized feature based upon the outputted identifier.
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17. The method as in claim 13, further comprising:
(g) thinning the recognized feature based upon the outputted identifier.
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18. The method as in claim 13, wherein the recognized image feature is an adjacent colored edged.
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19. The method as in claim 13, further comprising:
(g) using, when more than one template loosely matches the two-dimensional window of received gray-scale image data, an arbitration process to select the most preferred loosely matched template.
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20. The method as in claim 13, further comprising:
(g) creating an image plane being composed of the outputted identifiers.
Specification