A Theory of Pattern Perception Based on Human Physiology

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Abstract
The gross connectivity, patterns of information pathways in the primate and human visual systems, when examined by an information processing engineer, bear a curious resemblance to the two-dimensional-pattern optical computers which he builds himself in an attempt to achieve pattern recognition. The portions of the visual system inferior to the primary visual cortex are essentially a topologically accurate homeo-morphic mapping of the retinal image, at least in the vicinity of the fovea. Analysis of the topological aspects of the visual scene and hence ‘ Pattern Recognition ’ must therefore take place in the primary visual cortex and successive cortical areas We have previously reported how intra- and inter-cortical connectivity could support a combined memory and computation scheme capable of performing pattern recognition by a variation of two-dimensional cross correlation. This paper is a report of an extension of the previous model enabling it to perform pattern recognition by computing the two-dimensional Fourier transform of input images in a manner isomorphic to computation of the Fraunhofer diffraction pattern in optical computers. It is shown that the use of the Fourier transform of an unknown pattern in a subsequent correlation scheme results in a pattern recognition system which is not easily faulted by the small local mutilations of input patterns which badly compromise straight correlation pattern recognition schemes