A discriminant pseudo Zernike moments in face recognition

Pang, Ying Han and Teoh, Andrew Ben Jin and Ngo, David Chek Ling (2006) A discriminant pseudo Zernike moments in face recognition. Journal of Research and Practice in Information Technology, 38 (2). pp. 197-211. ISSN 1443-458X

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Abstract

This paper introduces a novel discriminant moment-based method as a feature extraction technique for face recognition. In this method, pseudo Zernike moments are performed before the application of Fisher's Linear Discriminant to achieve a stable numerical computation and good generalization in small-sample-size problems. Fisher's Linear Discriminant uses pseudo Zernike moments to derive an enhanced subset of moment features by maximizing the between-class scatter, while minimizing the within-class scatter, which leads to a better discrimination and classification performance. Experimental results show that the proposed method achieves superior performance with a recognition rate of 97.51% in noise free environment and 97.12% in noise induced environment for the Essex Face94 database. For the Essex Face95 database, the recognition rates obtained are 91.73% and 90.30% in noise free and noise induced environments, respectively.

Item Type: Article
Subjects: Q Science > QA Mathematics > QA75.5-76.95 Electronic computers. Computer science
Divisions: Faculty of Information Science and Technology (FIST)
Depositing User: Ms Rosnani Abd Wahab
Date Deposited: 10 Aug 2011 03:10
Last Modified: 05 Jan 2017 03:46
URI: http://shdl.mmu.edu.my/id/eprint/1982

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