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GA-based learning for a model-based object recognition system

โœ Scribed by R. Soodamani; Z.Q. Liu

Publisher
Elsevier Science
Year
2000
Tongue
English
Weight
714 KB
Volume
23
Category
Article
ISSN
0888-613X

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โœฆ Synopsis

This paper proposes a genetic-algorithm-based learning strategy that models membership functions of the fuzzy attributes of surfaces in a model based machine vision system. The objective function aims at enhancing recognition performance in terms of maximizing the degree of discrimination among classes. As a result, the accuracy of recognizing known instances of objects and generalization capability by recognizing unknown instances of known objects are greatly improved. Performance enhancement is achieved by incorporating an o-line learning mechanism using genetic algorithm in the feedback path of the recognition system.

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