Citation

Pang, Ying Han and Teoh, Andrew Ben Jin and Ngo, David Chek Ling (2005) Enhanced pseudo Zernike moments in face recognition. IEICE Electronics Express, 2 (3). pp. 70-75. ISSN 1349-2543

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Abstract

This paper presents an approach to boost the performance of pseudo Zernike moments in face recognition. This approach is a hybrid of a kernel trick, discriminant function and pseudo Zernike moments (PZM), namely as Kernel-based Fisher Pseudo Zernike Moments (KFPZM). KFPZM maps the moment-based features into a high dimensional feature space via kernel function for disclosing the underlying variables which carry significant information about the image. Then, it performs discriminant analysis onto the mapped features to enhance the discrimination power via Fisher's Linear Discriminant (FLD). Experimental results show that the proposed method outperforms the sole PZM and the integrated FLD with PZM methods, achieving recognition rate of 98.11% and 93.03% in the face databases with facial expression variations and illumination variations, respectively.

Item Type:	Article
Uncontrolled Keywords:	Face recognition, kernel, Fisher's Linear Discriminant, pseudo Zernike moments
Subjects:	T Technology > TA Engineering (General). Civil engineering (General)
Divisions:	Faculty of Information Science and Technology (FIST)
Depositing User:	Ms Rosnani Abd Wahab
Date Deposited:	12 Sep 2011 02:14
Last Modified:	05 Jan 2017 04:08
URII:	http://shdl.mmu.edu.my/id/eprint/2260

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