Performance Evaluation of Micropattern Representation on Gabor Features for Face Recognition

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Title Performance Evaluation of Micropattern Representation on Gabor Features for Face Recognition
Author Zhao, Sanqiang; Gao, Yongsheng; Zhang, Baochang
Publication Title Proceedings of the 20th International Conference on Pattern Recognition (ICPR 2010)
Editor IAPR
Year Published 2010
Place of publication United States
Publisher IEEE Computer Society
Abstract Face recognition using micropattern representation has recently received much attention in the computer vision and pattern recognition community. Previous researches demonstrated that micropattern representation based on Gabor features achieves better performance than its direct usage on gray-level images. This paper conducts a comparative performance evaluation of micropattern representations on four forms of Gabor features for face recognition. Three evaluation rules are proposed and observed for a fair comparison. To reduce the high feature dimensionality problem, uniform quantization is used to partition the spatial histograms. The experimental results reveal that: 1) micropattern representation based on Gabor magnitude features outperforms the other three representations, and the performances of the other three are comparable; and 2) micropattern representation based on the combination of Gabor magnitude and phase features performs the best.
Peer Reviewed Yes
Published Yes
Alternative URI http://dx.doi.org/10.1109/ICPR.2010.317
Copyright Statement Copyright 2010 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
ISBN 1051-4651
Conference name The 20th International Conference on Pattern Recognition (ICPR 2010)
Location Istanbul, Turkey
Date From 2010-08-23
Date To 2010-08-26
URI http://hdl.handle.net/10072/36141
Date Accessioned 2010-10-11
Date Available 2011-04-18T06:54:32Z
Language en_AU
Research Centre Institute for Integrated and Intelligent Systems
Faculty Faculty of Science, Environment, Engineering and Technology
Subject Computer Vision; Pattern Recognition and Data Mining
Publication Type Conference Publications (Full Written Paper - Refereed)
Publication Type Code e1

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