Title :
2D Direct LDA Algorithm for Face Recognition
Author :
Cho, Dong Uk ; Chang, Un Dong ; Kim, Bong Hyun ; Lee, Se Hwan ; Bae, Young Lae J ; Ha, Soo Cheol
Author_Institution :
Dept. of Inf. & Commun. Eng., Chungbuk Provincial Univ. of Sci. & Technol.
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 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
Keywords :
S-matrix theory; face recognition; feature extraction; image representation; visual databases; 2D direct linear discriminant analysis algorithm; 2D image feature extraction method; ORL face database; face recognition; image scatter matrix; low-dimensional feature representation technique; Covariance matrix; Data mining; Face recognition; Feature extraction; Image databases; Kernel; Linear discriminant analysis; Null space; Principal component analysis; Scattering;
Conference_Titel :
Software Engineering Research, Management and Applications, 2006. Fourth International Conference on
Conference_Location :
Seattle, WA
Print_ISBN :
0-7695-2656-X
DOI :
10.1109/SERA.2006.1