Improved (2D)² DLDA for Face Recognition 


Vol. 31,  No. 10, pp. 942-947, Oct.  2006


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  Abstract

In this paper, a new feature representation technique called Improved 2-directional 2-dimensional direct linear discriminant analysis (Improved (2D)2 DLDA) is proposed. In the case of face recognition, thesmall 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 2-directional image scatter matrix. Moreover the selection method of feature vector and the method of similarity measure are proposed. 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.

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  Cite this article

[IEEE Style]

D. Cho, U. Chang, Y. Kim, K. Kim, J. Ahn, B. Kim, S. Lee, "Improved (2D)² DLDA for Face Recognition," The Journal of Korean Institute of Communications and Information Sciences, vol. 31, no. 10, pp. 942-947, 2006. DOI: .

[ACM Style]

Dong-uk Cho, Un-dong Chang, Young-gil Kim, Kwan-dong Kim, Jae-hyeong Ahn, Bong-hyun Kim, and Se-hwan Lee. 2006. Improved (2D)² DLDA for Face Recognition. The Journal of Korean Institute of Communications and Information Sciences, 31, 10, (2006), 942-947. DOI: .

[KICS Style]

Dong-uk Cho, Un-dong Chang, Young-gil Kim, Kwan-dong Kim, Jae-hyeong Ahn, Bong-hyun Kim, Se-hwan Lee, "Improved (2D)² DLDA for Face Recognition," The Journal of Korean Institute of Communications and Information Sciences, vol. 31, no. 10, pp. 942-947, 10. 2006.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880