Identification of Complex Shapes Using a Self Organizing Neural System

We present a multilayer hierarchical neural system for automatic classification of complex contour patterns. The system consists of a neocognitron-like network structure combined with self-organizing maps to automatically determine feature classes. We present results showing that multilayer hierarchical networks are able to tolerate pattern distortion considerably better than standard neural network implementations. Index Terms--Hierarchical feature extraction, self-organizing neural networks, visual pattern recognition.