Machine vision methods and systems for boundary feature comparison of patterns and images
First Claim
1. In a machine vision method for comparing a pattern and an image, the improvement comprising:
- A. finding points on a boundary in the image, B. identifying a boundary feature in the image, the boundary feature being defined by a plurality of the points on the boundary in the image, C. determining one or more point-to-point relationships, if any, between each point defining the boundary feature and a corresponding point, if any, on a boundary in the pattern, and C1. step (c) including assigning a numerical score that is a function of differences in any of location, angle or contrast of the point on the boundary feature in the image and the corresponding point, if any, on the boundary in the boundary in the pattern, D. determining a relationship between the boundary feature in the image and the pattern as a function of the relationship determined in step (C), D1. step (D) includes determining whether the boundary feature in the image is extra with respect to the pattern as a function of whether the numerical score determined in step (C1) falls below either a first threshold or a second threshold.
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Abstract
The invention provides boundary-based machine vision methods and systems for comparing a pattern to an image. These contemplate the steps of finding points on a boundary in the image; identifying one or more boundary features, at least one of which is made up of multiple such points; determining point-by-point relationships, if any, between each point defining the boundary feature in the image and points on a boundary in the pattern; and determining a relationship between the boundary feature in the image and the pattern (e.g., whether the boundary feature in the image matches a corresponding feature in the pattern) as a function of the point-by-point relationships.
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Citations
32 Claims
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1. In a machine vision method for comparing a pattern and an image, the improvement comprising:
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A. finding points on a boundary in the image, B. identifying a boundary feature in the image, the boundary feature being defined by a plurality of the points on the boundary in the image, C. determining one or more point-to-point relationships, if any, between each point defining the boundary feature and a corresponding point, if any, on a boundary in the pattern, and C1. step (c) including assigning a numerical score that is a function of differences in any of location, angle or contrast of the point on the boundary feature in the image and the corresponding point, if any, on the boundary in the boundary in the pattern, D. determining a relationship between the boundary feature in the image and the pattern as a function of the relationship determined in step (C), D1. step (D) includes determining whether the boundary feature in the image is extra with respect to the pattern as a function of whether the numerical score determined in step (C1) falls below either a first threshold or a second threshold. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
E. identifying a boundary feature in the pattern, the boundary feature being defined by a plurality of the points in the pattern;
F. determining one or more point-to-point relationships, if any, between each point defining the boundary in the pattern and a corresponding point on the boundary in the image, and G. determining a relationship between the boundary feature in the pattern and the boundary in the image as a function of the relationships determined in step (F).
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7. In a machine vision method according to claim 6, the further improvement wherein step (F) includes determining whether a point on the boundary feature in the pattern is missing from the boundary in the image.
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8. In a machine vision method according to claim 7, the further improvement wherein step (G) includes determining whether the boundary feature in the pattern is missing from the image based on a count of a number of the points on the boundary feature in the pattern that are missing from the boundary in the image.
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9. In a machine vision method for comparing a pattern and an image, the improvement comprising:
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A. finding points on a boundary in the image, B. identifying a boundary feature in the image, the boundary feature being defined by a plurality of the points on the boundary in the image, C. determining a quantitative point-to-point relationships, if any, between each point defining the boundary feature and a corresponding point, if any, on a boundary in the pattern, and C1. step (C) includes assigning a numerical score that is a function of differences in any of the location, angle or contrast of the point on the boundary feature in the image and the corresponding point, if any, on the boundary in the boundary in the pattern, D. determining a relationship between the boundary feature in the image and the patterns a function of the quantitative relationships determined in step (C), D1. step (D) includes determining whether the boundary feature in the image is extra with respect to the pattern as a function of whether the score determined in step (C1) falls below either a first threshold or a second threshold. - View Dependent Claims (10, 11, 12, 13, 14, 15)
E. identifying a boundary feature in the pattern, the boundary feature being defined by a plurality of the points on the boundary in the pattern, F. determining a quantitative point-to-point relationship between each point defining the boundary feature in the pattern and a corresponding point, if any, on a boundary in the image, and G. determining a relationship between the boundary feature in the pattern and the image as a function of the quantitative relationships determined in step (F).
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14. In a machine vision method according to claim 13, further improvement wherein step (F) comprises assigning a numerical score to each point on the boundary feature in the pattern based on a difference in any of a location, angle and contrast of that point and a corresponding point, if any, on the boundary in the image.
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15. In a machine vision method according to claim 14, the further improvement wherein step (G) includes determining whether the boundary feature in the image is missing with respect to to the pattern as a function of whether a statistical measure of the numerical score determined in step (F) falls below a threshold.
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16. In a machine vision method for comparing a pattern and an image, the improvement comprising:
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A. finding points on a boundary in the image, B. identifying a boundary feature in the image, the boundary feature being defined by a plurality of the points on the boundary in the image, C. determining one or more point-to-point relationships, if any, between each point defining the boundary feature and a corresponding point, if any, on a boundary in the pattern, and C1. step (c) including assigning a numerical score that is a function of differences in any of location, angle or contrast of the point on the boundary feature in the image and the corresponding point, if any, on the boundary in the boundary in the pattern, D. determining a relationship between the boundary feature in the image and the pattern as a function of the relationship determined in step (C), D1. step (D) includes determining whether the boundary feature in the image is extra with respect to the pattern as a function of whether the score determined in step (C1) falls below either a first threshold or a second threshold. - View Dependent Claims (17, 18, 19, 20, 21, 22, 23)
E. identifying a boundary feature in the pattern, the boundary feature being defined by a plurality of the points in the pattern;
F. determining one or more point-to-point relationships, if any, between each point defining the boundary in the pattern and a corresponding point, if any, on the boundary feature in the image, and G. determining a relationship between the boundary feature in the pattern and the boundary in the image as a function of the relationships determined in step (F).
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22. In a machine vision system according to claim 21, the further improvement wherein step (F) includes determining whether the points on the boundary feature in the pattern are missing from the boundary in the image.
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23. In a machine vision system according to claim 22, the further improvement wherein step (G) includes determining whether the boundary feature in the pattern is missing from the image as a function of a number of the points on the boundary feature in the pattern that are missing from the boundary in the image.
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24. In a machine vision method for comparing a pattern and an image, the improvement comprising:
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A. finding points on a boundary in the image, B. identifying a boundary feature in the image, the boundary feature being defined by a plurality of the points on the boundary in the image, C. determining a quantitative point-to-point relationships, if any, between each point defining the boundary feature and a corresponding point, if any, on a boundary in the pattern, and C1. step (C) includes assigning a numerical score that is a function of differences in any of the location, angle or contrast of the point on the boundary feature in the image and the corresponding point, if any, on the boundary in the boundary in the pattern, D. determining a relationship between the boundary feature in the image and the patterns a function of the quantitative relationships determined in step (C), D1. step (D) includes determining whether the boundary feature in the image is extra with respect to the pattern as a function of whether the score determined in step (C1) falls below either a first threshold or a second threshold. - View Dependent Claims (25, 26, 27, 28, 29, 30, 31, 32)
E. identifying a boundary feature in the pattern, the boundary feature being defined by a plurality of the points on the boundary in pattern, F. determining a quantitative point-to-point relationship between each point defining the boundary feature in the pattern and points on a boundary in the image, and G. determining a relationship between the boundary feature in the pattern and the image as a function of the quantitative relationships determined in step (F).
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31. In a machine vision system according to claim 30, the further improvement wherein step (F) comprises assigning a numerical score to each point on the boundary feature in the pattern as a function of a difference in any of a location, angle and contrast of that point and a corresponding point, if any, on the boundary in the image.
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32. In a machine vision system according to claim 31, the further improvement wherein step (G) includes determining whether the boundary feature in the image is missing with respect to to the pattern as a function of whether a statistical measure of the quantitative relationships determined in step (F) falls below a threshold.
Specification