Evolutionary algorithm-based face verification

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This paper proposes a novel face verification method using principal components analysis (PCA) and evolutionary algorithm (EA). Although PCA related algorithms have shown outstanding performance, the problem lies in making decision rules or distance measures. To solve this problem, quantum-inspired evolutionary algorithm (QEA) is employed to find out the optimal weight factors in the distance measure for a predetermined threshold value which distinguishes between face images and non-face images. Experimental results show the effectiveness of the proposed method through the improved verification rate and false alarm rate. (C) 2004 Elsevier B.V. All rights reserved.
Publisher
ELSEVIER SCIENCE BV
Issue Date
2004-12
Language
English
Article Type
Article
Keywords

RECOGNITION

Citation

PATTERN RECOGNITION LETTERS, v.25, pp.1857 - 1865

ISSN
0167-8655
DOI
10.1016/j.patrec.2004.08.013
URI
http://hdl.handle.net/10203/12754
Appears in Collection
EE-Journal Papers(저널논문)
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