The model of a neural network visual preprocessor

Abstract The model of a neural network visual preprocessor and a system architecture for visual information processing are proposed. The model of the preprocessor is based on the model of a visual cortex iso-orientation domain which is considered as a neural network with retinotopically organized afferent inputs and anisotropic lateral inhibition formed by feedback connections via inhibitory interneurons. The high-level system uses the preprocessor to process image fragments with different resolutions and to represent the image as a set of contour segments of different sizes.

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