A novel null space-based kernel discriminant analysis for face recognition

Authors:
Tuo Zhao;Zhizheng Liang;David Zhang;Yahui Liu
Affiliations:
Harbin Institute of Technology;Harbin Institute of Technology;Hongkong Polytechnic University;Harbin Institute of Technology
Venue:
ICB'07 Proceedings of the 2007 international conference on Advances in Biometrics
Year:
2007

Citing 5
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Abstract

The symmetrical decomposition is a powerful method to extract features for image recognition. It reveals the significant discriminative information from the mirror image of symmetrical objects. In this paper, a novel null space kernel discriminant method based on the symmetrical method with a weighted fusion strategy is proposed for face recognition. It can effectively enhance the recognition performance and shares the advantages of Null-space, kernel and symmetrical methods. The experiment results on ORL database and FERET database demonstrate that the proposed method is effective and outperforms some existing subspace methods.