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Design for optoelectronic implementation of visual recognition system

The visual recognition system in animals is an inherently parallel system. Existing very large scale integrated circuit implementations have serious limitations on power consumption and computational speed. We propose a highly parallel optoelectronic system combining elements of the Grossberg and Dobbin vision models and Fukushima's Neocognitron model. This high performance machine vision hardware is capable of distortion invariant recognition. Modeling and implementation of such systems provides insight into the visual recognition function, and also is useful for designing optoelectronic hardware that can be used for many applications.