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Optical Engineering

Face detection in color images using efficient genetic algorithms
Author(s): Cheng-Jian Lin; Ho-Chin Chuang; Yong-Ji Xu
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Paper Abstract

Face detection from images is a key problem in human computer interaction studies and pattern recognition research. In this work, we propose an efficient genetic algorithm (EGA) that solves the face detection problem in color images. The proposed EGA is based on the Takagi-Sugeno-Kang(TSK)-type fuzzy model employed to perform parameter learning. Compared with traditional genetic algorithms, the EGA uses the sequential-search based-efficient generation (SSEG) method to generate an initial population to determine the most efficient mutation points. Experimental results show that the performance of the EGA is superior to the existing traditional genetic methods.

Paper Details

Date Published: 1 April 2006
PDF: 12 pages
Opt. Eng. 45(4) 047201 doi: 10.1117/1.2189290
Published in: Optical Engineering Volume 45, Issue 4
Show Author Affiliations
Cheng-Jian Lin, Chaoyang Univ. of Technology (Taiwan)
Ho-Chin Chuang, Chaoyang Univ. of Technology (Taiwan)
Yong-Ji Xu, Chaoyang Univ. of Technology (Taiwan)


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