Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/14323
Title: Holistic orthogonal analysis of discriminant transforms for color face recognition
Authors: Jing, X
Liu, Q
Lan, C
Man, J
Li, S
Zhang, D 
Keywords: Color face recognition
Discriminant transforms
Feature extraction
Holistic orthogonal analysis
Issue Date: 2010
Source: Proceedings - International Conference on Image Processing, ICIP, 2010, p. 3841-3844 How to cite?
Abstract: The key of color face recognition technique is how to effectively utilize the complementary information between color components and remove their redundancy. Present color face recognition methods generally reduce the correlations between color components in the image pixel level, and then extract the discriminant features from the uncorrelated color face images. In this paper, we propose a novel color face recognition approach based on the holistic orthogonal analysis (HOA) of discriminant transforms of color images. HOA can reduce the correlation of color information in the feature level. It in turn achieves the discriminant transforms of red, green and blue color images by using the Fisher criterion, and simultaneously makes the achieved transforms mutually orthogonal. Experimental results on the AR and FRGC-2 public color face image databases demonstrate that the proposed approach acquires better recognition performance than several representative color face recognition methods.
Description: 2010 17th IEEE International Conference on Image Processing, ICIP 2010, Hong Kong, 26-29 September 2010
URI: http://hdl.handle.net/10397/14323
ISBN: 9781424479948
ISSN: 1522-4880
DOI: 10.1109/ICIP.2010.5654099
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