Title :
Face recognition using hybrid feature
Author :
Su, Hong-tao ; Feng, David-dagan ; Wang, Xiu-Ying ; Zhao, Rong-chun
Author_Institution :
Dept. of Comput. Sci. & Eng., Northwestern Polytech. Univ., Xi´´an, China
Abstract :
In this paper, a face recognition algorithm using hybrid feature is proposed. The algorithm consists of three steps. In the first step, a coarse classification is performed using Mutual Information match. In the second step, the Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) features of frequency spectrum are extracted, which will be taken as the input of the RBFN in the third step. In the last step, the classification is carried out by using RBFN. The proposed approach has been tested on ORL face database and Shimon database. The experimental results have demonstrated that the performance of this algorithm is superior to the other algorithms on the same database.
Keywords :
face recognition; pattern classification; principal component analysis; radial basis function networks; visual databases; LDA; ORL face database; PCA; RBFN; Shimon database; classification; coarse classification; face recognition algorithm; hybrid feature; linear discriminant analysis; mutual information match; principal component analysis; radial basis function network; Data mining; Face detection; Face recognition; Facial features; Linear discriminant analysis; Mutual information; Principal component analysis; Signal processing algorithms; Spatial databases; Testing;
Conference_Titel :
Machine Learning and Cybernetics, 2003 International Conference on
Print_ISBN :
0-7803-8131-9
DOI :
10.1109/ICMLC.2003.1260100