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Abstract:Principal component analysis (PCA) has been applied in many face recognition systems, and achieved very good results. However, PCA has its limitations: a large amount of calculation and very low capacity of identification. In order to overcome these disadvantages, a new face recognition algorithm which is based on wavelet transform, principal component analysis and minimum distance classifier is proposed in the paper. The simulation experiments based on ORL face database show that the method not only improves the recognition rate, but also reduces the amount of computation. When the training sample is very large, the effectiveness of recognition systems is particularly important. © 2012 IEEE.

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