Evolutionary algorithm-based face verification

Authors:
Jun-Su Jang;Kuk-Hyun Han;Jong-Hwan Kim
Affiliations:
Departement of Electrical Engineering and Computer Science, Korea Advanced Institute of Science and Technology (KAIST), 373-1, Guseong-dong, Yuseong-gu, Daejon 305-701, Republic of Korea;Digital Media R&D Center, Samsung Electronics Co., Ltd., 416, Maetan-3dong, Youngtong-gu, Suwon, Gyeonggi 442-742, Republic of Korea;Departement of Electrical Engineering and Computer Science, Korea Advanced Institute of Science and Technology (KAIST), 373-1, Guseong-dong, Yuseong-gu, Daejon 305-701, Republic of Korea
Venue:
Pattern Recognition Letters
Year:
2004

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Abstract

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.