(2D)2 DLDA for efficient face recognition

Authors:
Dong-uk Cho;Un-dong Chang;Kwan-dong Kim;Bong-hyun Kim;Se-hwan Lee
Affiliations:
Department of Information & Communication Engineering, Chungbuk Provincial University of Science & Technology, Chungbuk, Korea;Department of Computer Engineering, Chungbuk National University, Chungbuk, Korea;Department of Computer Engineering, Chungbuk National University, Chungbuk, Korea;Department of Computer Engineering, Hanbat National University, Daejeon, Korea;Department of Computer Engineering, Hanbat National University, Daejeon, Korea
Venue:
PSIVT'06 Proceedings of the First Pacific Rim conference on Advances in Image and Video Technology
Year:
2006

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Abstract

In this paper, a new feature representation technique called 2-directional 2-dimensional direct linear discriminant analysis ((2D)2 DLDA) is proposed. In the case of face recognition, the small sample size problem and need for many coeffficients are often encountered. In order to solve these problems, the proposed method uses the direct LDA and two directional image scatter matrix. The ORL face database is used to evaluate the performance of the proposed method. The experimental results show that the proposed method obtains better recognition rate and requires lesser memory than the direct LDA.