Feature classification using supervised statistical pattern...

G - Physics – 06 – K

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G06K 9/46 (2006.01) G06K 9/62 (2006.01) G06K 9/68 (2006.01) G06F 15/401 (1990.01)

Patent

CA 2094212

FEATURE CLASSIFICATION USING SUPERVISED STATISTICAL PATTERN RECOGNITION Abstract of the Disclosure Feature classification using a novel supervised statistical pattern recognition approach is described. A tree-like hierarchical decomposition of n-dimensional feature space is created off-line from an image processing system. The hierarchical tree is created through a minimax-type decompositional segregation of n-dimensional feature vectors of different feature classifications within the corresponding feature space. Each cell preferably contains feature vectors of only one feature classification, or is empty, or is of a predefined minimum cell size. Once created, the hierarchical tree is made available to the image processing system for real-time defect classification of features in a static or moving pattern. Each feature is indexed to the classification tree by locating its corresponding feature vector in the appropriate feature space cell as determined by a depth-first search of the hierarchical tree. The smallest leaf node which includes that feature vector provides the statistical information on the vector's classification.

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