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  2009, Vol. 22 Issue (4): 635-638    DOI:
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Face Recognition Based on Circularly Symmetrical Gabor Transforms and Weighted PCA
WANG Jin-Jun1, WANG Hui-Yuan1,2, WU Xiao-Juan1
1.School of Information Science and Engineering, Shandong University, Jinan 250100
2.Instituto de Engenharia Electrónicae Telemática de Aveiro, Universidade de Aveiro, Campus Universitario de Santiago, 3810-193 Aveiro, Portugal

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Abstract  Circularly symmetrical Gabor transforms (CSGT) has two advantageous properties:reduced redundancy and rotation invariance. A face recognition method is proposed based on circularly symmetrical Gabor transforms and weighted PCA feature. The face image is transformed to CSGT, and then the discriminant features for face recognition are extracted using weighted PCA. Detailed theoretical analysis is presented and simulation results on three face databases are given. Comparative experiments of various face recognition schemes are carried out. The experimental results show the feasibility and advantages of the proposed method.
Key wordsFace Recognition      Circularly Symmetrical Gabor Transform (CSGT)      Principal Component Analysis (PCA)      Weighted Principal Components Analysis (PCA)     
Received: 14 July 2008     
ZTFLH: TP391.41  
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WANG Jin-Jun
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Cite this article:   
WANG Jin-Jun,WANG Hui-Yuan,WU Xiao-Juan. Face Recognition Based on Circularly Symmetrical Gabor Transforms and Weighted PCA[J]. , 2009, 22(4): 635-638.
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