Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/26316
Title: Uncorrelated projection discriminant analysis and its application to face image feature extraction
Authors: Yang, J
Yang, JY
Frangi, AF
Zhang, D 
Keywords: Eigenfaces
Face recognition
Feature extraction
Fisherfaces
Linear discriminant analysis (LDA)
Issue Date: 2003
Source: International journal of pattern recognition and artificial intelligence, 2003, v. 17, no. 8, p. 1325-1347 How to cite?
Journal: International Journal of Pattern Recognition and Artificial Intelligence 
Abstract: In this paper, a novel image projection analysis method (UIPDA) is first developed for image feature extraction. In contrast to Liu's projection discriminant method, UIPDA has the desirable property that the projected feature vectors are mutually uncorrelated. Also, a new LDA technique called EULDA is presented for further feature extraction. The proposed methods are tested on the ORL and the NUST603 face databases. The experimental results demonstrate that: (i) UIPDA is superior to Liu's projection discriminant method and more efficient than Eigenfaces and Fisherfaces; (ii) EULDA outperforms the existing PCA plus LDA strategy; (iii) UIPDA plus EULDA is a very effective two-stage strategy for image feature extraction.
URI: http://hdl.handle.net/10397/26316
ISSN: 0218-0014
DOI: 10.1142/S0218001403002903
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