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Fourth International Conference on Software Engineering Research, Management and Applications (SERA'06)
2D Direct LDA Algorithm for Face Recognition
Seattle, Washington
August 09-August 11
ISBN: 0-7695-2656-X
Dong Uk Cho, Chungbuk Provincial University of Science & Technology, Chungbuk, South Korea
Un Dong Chang, Chungbuk National University, Chungbuk, South Korea
Bong Hyun Kim, Hanbat National University, Daejeon, South Korea
Se Hwan Lee, Daejeon, South Korea
Young Lae J.Bae, Chungbuk Provincial University of Science & Technology, Chungbuk, South Korea
Soo Cheol Ha, Daejeon University, Daejeon, South Korea
A new low-dimensional feature representation technique is presented in this paper. Linear discriminant analysis is a popular feature extraction method. However, in the case of high dimensional data, the computational difficulty and the small sample size problem are often encountered. In order to solve these problems, we propose Two Dimensional Direct LDA algorithm named 2D-DLDA, which directly extracts the image scatter matrix from 2D image and uses Direct LDA algorithm for face recognition. The ORL face database is used to evaluate the performance of the proposed method. The experimental results indicate that the performance of the proposed method is superior to DLDA.
Citation:
Dong Uk Cho, Un Dong Chang, Bong Hyun Kim, Se Hwan Lee, Young Lae J.Bae, Soo Cheol Ha, "2D Direct LDA Algorithm for Face Recognition," sera, pp.245-248, Fourth International Conference on Software Engineering Research, Management and Applications (SERA'06), 2006
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