Visual Feature Extraction by a Multilayered Network of Analog Threshold Elements

Abstract

A new type of visual feature extracting network has been synthesized, and the response of the network has been simulated on a digital computer. This research has been done as a first step towards the realization of a recognizer of handwritten characters. The design of the network was suggested by biological systems, especially, the visual systems of cat and monkey. The network is composed of analog threshold elements connected in layers. Each analog threshold element receives inputs from a large number of elements in the neighbouring layers and performs its own special functions. It takes care of one restricted part of the photoreceptor layer, on which an input pattem is presented, and it responds to one particular feature of the input pattem, such as brightness contrast, a dot in the pattern, a line segment of a particular orientation, or an end of the line. This means that the network performs parallel processing of the information. With the propagation of the information through the layered network, the input pattern is successively decomposed into dots, groups of line segments of the same orientation, and the ends of these line segments.