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Adaptive edge-only matching model for pattern recognition in humans and machines

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Abstract

A procedure for the classification of patterns in terms of their critical edge features is considered. The learning phase involves: (i) an initial multiscaled edge extractor for each sample within a class; (ii) developing multiscaled prototypes within each class; and (iii) emphasizing the unique features of each class.

© 1986 Optical Society of America

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