Title :
A hierarchical machine vision system based on a model of the primate visual system
Author :
Gochin, Paul M. ; Lubin, Joseph M.
Author_Institution :
Dept. of Psychol., Princeton Univ., NJ, USA
Abstract :
The problem of advancing machine visual pattern recognition capabilities is approached by examining the visual system of the primate. A model of biological vision is suggested, and an analogous machine vision simulation is developed. The modeling is limited to luminance information (color, motion, and depth are not considered), and biological systems are considered at the network level (biochemical and biophysical details are not simulated). The system architecture consists of a set of invariance transforms (luminance, spatial, and scale) followed by storage using an adaptive resonance theory network
Keywords :
computer vision; hierarchical systems; neural nets; pattern recognition; visual perception; ART model; ART-1; adaptive resonance theory network; biological vision; categorical storage; hierarchical machine vision system; invariance transforms; luminance contrast enhancement; luminance information; machine vision simulation; machine visual pattern recognition; primate visual system; spatial invariance; Anatomy; Biological system modeling; Biological systems; Brain modeling; Filters; Machine vision; Neural networks; Resonance; Retina; Visual system;
Conference_Titel :
Intelligent Control, 1990. Proceedings., 5th IEEE International Symposium on
Conference_Location :
Philadelphia, PA
Print_ISBN :
0-8186-2108-7
DOI :
10.1109/ISIC.1990.128440
