NDLI: Combination of dual-tree complex wavelet and SVM for face recognition

Content Provider	IEEE Xplore Digital Library
Author	Guo-Yun Zhang Shi-Yu Peng Hong-Min Li
Copyright Year	2008
Description	Author affiliation: Dept. of Phys. & Electron. Inf., Hunan Inst. of Sci. & Technol., Yueyang (Guo-Yun Zhang)
Abstract	Based on the attractive property such as shift invariance, good directional selectivity, limited redundancy and efficient computation of dual-tree complex wavelet transform, a novel face recognition method with combining of dual-tree complex wavelet transform and support vector machine is proposed in this paper. Firstly, it uses 2D dual-tree complex wavelet transform to decompose each face image into six band-pass sub-images that are strongly oriented at 6 different angles and two low-pass sub-images and extracts the human face features. Then principal component analysis technique is used to reduce the feature dimensions. Finally, support vector machine is used as classifier. Through the comparative experiments between the Gabor wavelet approach and the 2D dual-tree complex wavelet transform approach, the results show that the proposed approach can achieve higher recognition rate no matter what SVM kernel is used. Also, experiments show that the proposed method needs least computation time.
Starting Page	2815
Ending Page	2819
File Size	370484
Page Count	5
File Format	PDF
ISBN	9781424420957
DOI	10.1109/ICMLC.2008.4620887
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-07-12
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Wavelet transforms Support vector machines Transforms Face Feature extraction Face recognition Kernel Dual-tree complex wavelet transform SVM Principal component analysis
Content Type	Text
Resource Type	Article

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