Patent ID: 6148099
Filing Date: 2000-11-14
Classification: G06T

Abstract:
A method for incremental concurrent learning in automatic defect classification comprising the steps of:(a) providing defect images with truth labels;(b) performing a context sensitive segmentation to produce a segmented image output;(c) extracting a set of comprehensive features from a segmented image output to provide a feature output;(d) performing automatic feature selection and transformation of the feature output having an application feature set output;(e) automatic classification rule generation to provide classification rules for automatic feature selection and transformation and to provide initial classification rules;(f) providing new potential defects;(g) performing a context sensitive segmentation of the new potential defects;(h) performing feature extraction of potential defects to provide extracted potential defects;(i) performing feature classification of the extracted potential defects using the initial classification rules to provide defect classification;(j) providing potential defects and fabrication information;(k) providing a primary classification rule and secondary classification rule selection from a defect knowledge database from multiple products with different process cycles;(l) performing primary defect classification having a classification output;(m) checking a confidence of the classification output to decide whether to perform a secondary defect classification;(n) if the confidence is not high, performing a secondary defect classification;(o) checking the confidence of a secondary defect classification and if the confidence of the secondary defect classification is high, defining a classification outcome and providing the classification outcome to the primary classification rule and secondary classification rule selection step;(p) if the confidence of the secondary defect classification is not high, questioning the classification outcome and sending potential defects to a novelty defect detection step;(q) performing the novelty defect detection step to define artifacts or potential new defect types to provide information for a truth inquiry; and(r) performing a truth inquiry to update a classification rule database for use by the primary classification rule and secondary classification rule selection.