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Proceedings Paper

Fuzzy Logic, Neural Networks And Computer Vision
Author(s): Madan M. Gupta
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Paper Abstract

The emulation of human-like vision on a computer is often the desired goal of robot vision and medical image processing. Human vision possesses some important attributes such as "perception" and "cognition". It is imperative that some aspects of these attributes are captured when emulating the human visual system. The processes of perception, mentation, and cognition imply that objects and images are not crisply perceived and, therefore, the more common forms of logic such as binary cannot be used. The recently developed calculus of fuzzy logic along with neuron-like computational units appear to be very powerful tools for the emulation of human-like vision fields on a computer. In this paper, we describe the connection between fuzzy logic and neural networks for the area of computer vision.

Paper Details

Date Published: 27 March 1989
PDF: 3 pages
Proc. SPIE 1002, Intelligent Robots and Computer Vision VII, (27 March 1989); doi: 10.1117/12.960296
Show Author Affiliations
Madan M. Gupta, University of Saskatchewan (Canada)

Published in SPIE Proceedings Vol. 1002:
Intelligent Robots and Computer Vision VII
David P. Casasent, Editor(s)

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