Automated defect classification system
First Claim
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1. A digital computer for automatically classifying defects in an object comprising:
- means for forming a defect image from a digital input image of an object;
means for forming an adaptively labeled defect image from said digital input image and a reference label image of aid object;
means for creating a plurality of defect feature measurements of a defect from at least said defect image, and said adaptively labeled image;
fuzzy logic inference engine means having a plurality of if-then defect class rules each based on a plurality of fuzzy sets of fuzzy logic parameters, means for converting said defect feature measurements into fuzzy logic parameters and applying said converted parameters to said if-then rules to compute a delete class fuzzy set for each defect; and
means lot deriving output data from each said defect class fuzzy set which classifies each defect.
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Abstract
An integrated visual defect detection and classification system. The invention includes adaptive defect detection and image labeling, defect feature measures, and a knowledge based inference shell/engine for classification based on fuzzy logic. The combination of these elements comprises a method and system for providing detection and analysis of product defects in many application domains, such as semiconductor and electronic packaging manufacturing.
418 Citations
52 Claims
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1. A digital computer for automatically classifying defects in an object comprising:
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means for forming a defect image from a digital input image of an object; means for forming an adaptively labeled defect image from said digital input image and a reference label image of aid object; means for creating a plurality of defect feature measurements of a defect from at least said defect image, and said adaptively labeled image; fuzzy logic inference engine means having a plurality of if-then defect class rules each based on a plurality of fuzzy sets of fuzzy logic parameters, means for converting said defect feature measurements into fuzzy logic parameters and applying said converted parameters to said if-then rules to compute a delete class fuzzy set for each defect; and means lot deriving output data from each said defect class fuzzy set which classifies each defect. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 51)
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26. A method for automatically classifying defects in an object comprising the steps of:
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forming a defect image from a digital input image of the object; forming an adaptively labeled defect image from said digital input image and a reference label image; creating a plurality of defect feature measurements of a defect from at least said defect image, and said adaptively labeled image; converting said defect feature measurements into fuzzy logic parameters; applying said converted parameters to a plurality of if-then rules each based on a plurality of fuzzy sets of fuzzy logic parameters; computing a defect class fuzzy set for each defect; and deriving output data from each of said defect class fuzzy sets for classifying each defect. - View Dependent Claims (27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 52)
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Specification