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Evolutionary algorithm-based face verification

delete2004-12-01
delete17
PRE
AI
J
Jun-Su Jang *
K
Kuk-Hyun Han
J
Jong-Hwan Kim
DOI:10.1016/j.patrec.2004.08.013delete
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Abstract

Abstract

En 中文
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.
Keywords:
face verification
principal components analysis
evolutionary algorithm
quantum-inspired evolutionary algorithm

Journal

Pattern Recognition Letters cover
Pattern Recognition Letters
IF:
3.3
Papers:
7.9K
Citations:
1.6W

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