融合小波变换和张量PCA的人脸识别算法

Abstract

Abstract:

The accuracy rate of the face recognition by tensor PCA is higher than that by PCA. And wavelet has two abilities to capture localized time-frequency information and to reduce the dimension of images. According to the two advantages of the above algorithms, a new face recognition algorithm based on wavelet transform and tensor PCA is proposed. Wavelet transform is firstly used and then tensor PCA is used to extract the feature of subband images, and the efficient recognition of face images can be realized. The recognition rate of the proposed alogorithm is 6％ higher than that of the tensror PCA algorithm, and the recognition time of the proposed algorithm is 35.74％ that of the tensor PCA algorithm, which is illustraed in experimental results.

Key words: face recognition, tensor principal component analysis, wavelet transforms, feature extraction

CLC Number:

TP391.41

WEN Hao;LU Zhao-yang;GAO Quan-xue. Face recognition algorithm based on wavelet preprocessing and tensor PCA[J].J4, 2009, 36(4): 602-607.

References

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Face recognition algorithm based on wavelet preprocessing and tensor PCA

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