Visual Cortex Inspired Intelligent Contour Detection

Abstract

The present paper proposes a model for intelligent image contour detection. The model is strongly based on the architecture and functionality of the mammalian visual cortex. A pixel-to-feature transformation is performed on the input image, the result of which is a set of abstract image features, instead of another set of pixels. The contouring task is performed by a vast and complex network of simple units of computation that work together in a parallel way. The use of a large number of such simple units allows a clear structure that can be implemented on a special hardware to allow constant time computation.

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“…The advantages are derived from the biological structure of human brain. As shown in the results of neuroscience studies Resko et al (2006); Born and Bradley (2005); Moran and Desimone (1985), a large portion of the primary neocortex appears to be directly devoted to and specialized in visual processing. In other words, human can rapidly process visual information.…”

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“…Due to the special weighting of inputs [6][7], a neuron produces increased responses when a line segment of the preferred orientation appears in the neurons receptive field.…”

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