Optimal face classification by using nonsingular discriminant waveletfaces for a face recognition

Authors:
Jin Ok Kim;Kwang Hoon Chung;Chin Hyun Chung
Affiliations:
Faculty of Multimedia, Daegu Haany University, Gyeongsangbuk-do, Korea;Department of Information and Control Engineering, Kwangwoon University, Seoul, Korea;Department of Information and Control Engineering, Kwangwoon University, Seoul, Korea
Venue:
ICADL'05 Proceedings of the 8th international conference on Asian Digital Libraries: implementing strategies and sharing experiences
Year:
2005

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Abstract

This paper proposes an algorithm on a face classification by using 2D wavelet subband transform and nonsingular fisher discriminant analysis for a face recognition. For a feature extraction, we apply the multiresolution wavelet transform to extract waveletfaces. We also perform the linear discriminant on waveletfaces to reinforce the discriminant power. During classification, the nonsingular fisher discriminant waveletfaces are used. In this study, we found that NDW (Nonsingular Discriminant Waveletface) solves the small sample size matter. Thus, NDW is superior to LDA for an efficient face classification.