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《Journal of South China University of Technology(Natural Science Edition)》 2007-01
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Principal Component Analysis Combined with Wavelet Low-Frequency Band

He Jia-zhong Du Ming-hui (School of Electronic and Information Engineering,South China Univ.of Tech.,Guangzhou 510640,Guangdong,China)  
This paper proposes a principal component analysis method combined with wavelet low-frequency band to deal with the face recognition with single training sample.To enhance the classification information of a single sa-mple image,the method combines the original training image with its reconstructed image based on wavelet low-frequency band,and performs the principal component analysis on the joined version of the training image.Experimental results on the ORL database show that,when each person has only one training sample,the proposed me-thod achieves 3.6% higher recognition accuracy and uses 14.8% fewer eigenfaces than the standard eigenface al-gorithm.
【Fund】: 广东省自然科学基金资助项目(05006593)
【CateGory Index】: TP391.41
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【Secondary References】
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