Enhanced pseudo Zernike moments in face recognition

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 featu...

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Main Authors: Pang, Ying Han, Teoh, Andrew Ben Jin, Ngo, David Chek Ling
Format: Article
Language:English
Published: The Institute of Electronics, Information and Communication Engineers 2005
Subjects:
Online Access:http://shdl.mmu.edu.my/2260/
http://shdl.mmu.edu.my/2260/1/Enhanced%20pseudo%20Zernike%20moments%20in%20face%20recognition.pdf
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author Pang, Ying Han
Teoh, Andrew Ben Jin
Ngo, David Chek Ling
author_facet Pang, Ying Han
Teoh, Andrew Ben Jin
Ngo, David Chek Ling
author_sort Pang, Ying Han
building MMU Institutional Repository
collection Online Access
description 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.
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spelling mmu-22602017-01-05T04:08:05Z http://shdl.mmu.edu.my/2260/ Enhanced pseudo Zernike moments in face recognition Pang, Ying Han Teoh, Andrew Ben Jin Ngo, David Chek Ling TA Engineering (General). Civil engineering (General) 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. The Institute of Electronics, Information and Communication Engineers 2005-02 Article NonPeerReviewed text en http://shdl.mmu.edu.my/2260/1/Enhanced%20pseudo%20Zernike%20moments%20in%20face%20recognition.pdf 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 http://dx.doi.org/10.1587/elex.2.70 doi:10.1587/elex.2.70 doi:10.1587/elex.2.70
spellingShingle TA Engineering (General). Civil engineering (General)
Pang, Ying Han
Teoh, Andrew Ben Jin
Ngo, David Chek Ling
Enhanced pseudo Zernike moments in face recognition
title Enhanced pseudo Zernike moments in face recognition
title_full Enhanced pseudo Zernike moments in face recognition
title_fullStr Enhanced pseudo Zernike moments in face recognition
title_full_unstemmed Enhanced pseudo Zernike moments in face recognition
title_short Enhanced pseudo Zernike moments in face recognition
title_sort enhanced pseudo zernike moments in face recognition
topic TA Engineering (General). Civil engineering (General)
url http://shdl.mmu.edu.my/2260/
http://shdl.mmu.edu.my/2260/
http://shdl.mmu.edu.my/2260/
http://shdl.mmu.edu.my/2260/1/Enhanced%20pseudo%20Zernike%20moments%20in%20face%20recognition.pdf