Face recognition algorithm based on wavelet transform and 2DNMF
基于小波变换和二维非负矩阵分解的人脸识别算法

This paper advanced a new fusion recognition algorithm 2DDWT+2DNMF through synthesizing two advantages of 2DDWT and 2DNMF. It firstly used wavelet transform to decompose face image to four sub-band images. Afterwards it focused on fusion of three high frequency sub-band images, and then used 2DNMF algorithm to extract the features of low frequency sub-band image and fusion image. At last it weighted these extracted features. Experimental results from ORL and YALE face image database show that compared with PCA, SVD, NMF and 2DDWT+NMF algorithms, the new fusion method can shorten training time and improve recognition rates effectively.