2D Direct LDA Algorithm for Face Recognition 


Vol. 30,  No. 12, pp. 1162-1166, Dec.  2005


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  Abstract

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, 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.

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  Cite this article

[IEEE Style]

D. Cho, U. Chang, Y. Kim, Y. Song, J. Ahn, B. Kim, "2D Direct LDA Algorithm for Face Recognition," The Journal of Korean Institute of Communications and Information Sciences, vol. 30, no. 12, pp. 1162-1166, 2005. DOI: .

[ACM Style]

Dong-uk Cho, Un-dong Chang, Young-gil Kim, Young-jun Song, Jae-hyeong Ahn, and Bong-hyun Kim. 2005. 2D Direct LDA Algorithm for Face Recognition. The Journal of Korean Institute of Communications and Information Sciences, 30, 12, (2005), 1162-1166. DOI: .

[KICS Style]

Dong-uk Cho, Un-dong Chang, Young-gil Kim, Young-jun Song, Jae-hyeong Ahn, Bong-hyun Kim, "2D Direct LDA Algorithm for Face Recognition," The Journal of Korean Institute of Communications and Information Sciences, vol. 30, no. 12, pp. 1162-1166, 12. 2005.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880