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Proceedings Paper

Pattern recognition based on morphological transforms and genetic algorithms
Author(s): Ning Wang; Liren Liu; Bingquan Wang; Yaozu Yin; Xiaona Yan
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Paper Abstract

This paper proposes a novel pattern recognition methodology based on morphological transforms and genetic algorithms. An entropy function is defined to demonstrate the match degree between two functions used in genetic algorithms. Based on morphological transforms and genetic algorithms, an optimal and adaptive set of structure elements as shape discrimination operators is developed by training patterns, moreover the string of variable structure elements is utilized to encode an image and construct the DNA of the image that maps arbitrary shapes into intrinsic and compact image features. Comparing the DNA string of the image with those of stored patterns, we can implement pattern recognition and classify an image. Then an optoelectronic pattern recognition architecture based on the algorithm is shown.

Paper Details

Date Published: 27 March 1997
PDF: 7 pages
Proc. SPIE 3073, Optical Pattern Recognition VIII, (27 March 1997); doi: 10.1117/12.270403
Show Author Affiliations
Ning Wang, Shanghai Institute of Optics and Fine Mechanics (China)
Liren Liu, Shanghai Institute of Optics and Fine Mechanics (China)
Bingquan Wang, Shanghai Institute of Optics and Fine Mechanics (China)
Yaozu Yin, Shanghai Institute of Optics and Fine Mechanics (China)
Xiaona Yan, Shanghai Institute of Optics and Fine Mechanics (China)


Published in SPIE Proceedings Vol. 3073:
Optical Pattern Recognition VIII
David P. Casasent; Tien-Hsin Chao, Editor(s)

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