Recognition algorithm based on wavelet preprocessing and tensor PCA
一种融合小波变化和张量PCA的人耳识别的算法*

Wavelet transform has good time-frequency analysis features, but also has characteristics of fast algorithms, while playing the role of dimension reduction. Tensor principal component analysis (PCA) method is used to identify the human ear than the PCA method can get higher recognition rate. Comprehensive utilization of the advantages of these two algorithms, proposed a new recognition algorithm of the human ear, to the human ear images using wavelet transform to do the first pre-processing to be four sub-band image, and then for each sub-band images using tensor PCA feature extraction to achieve efficient human ear image recognition. Simulation results show that using this method and only the principal component analysis identified tensor compared to improve the recognition rate.