Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/10161
Title: Post-processed LDA for face and palmprint recognition : what is the rationale
Authors: Zuo, W
Zhang, H
Zhang, D 
Wang, K
Keywords: Dimensionality reduction
Face recognition
Feature extraction
Linear discriminant analysis (LDA)
Palmprint recognition
Issue Date: 2010
Source: Signal processing, 2010, v. 90, no. 8, p. 2344-2352 How to cite?
Journal: Signal Processing 
Abstract: Linear discriminant analysis (LDA)-based methods have been very successful in face and palmprint recognition. Recently, a class of post-processing approaches has been proposed to improve the recognition performance of LDA in face recognition. In-depth analysis, however, has not been presented to reveal the effectiveness of the post-processing approach. In this paper, we first investigate the rationale of the post-processing approach using a Gaussian function, and demonstrate the mutual relationship between the post-processing approach and the image Euclidean distance (IMED) method. We further extend the post-processing approach to palmprint recognition and use the FERET face and the PolyU palmprint databases to evaluate the post-processed LDA method. Experimental results indicate that the post-processing approach is effective in improving the recognition rate for LDA-based face and palmprint recognition.
URI: http://hdl.handle.net/10397/10161
ISSN: 0165-1684
DOI: 10.1016/j.sigpro.2009.06.004
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