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

fYear

1990

fDate

5-7 Sep 1990

Firstpage

61

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control, 1990. Proceedings., 5th IEEE International Symposium on

Conference_Location

Philadelphia, PA

ISSN

2158-9860

Print_ISBN

0-8186-2108-7

Type

conf

DOI

10.1109/ISIC.1990.128440

Filename

128440