Sparse representation for face recognition based on partitioning energy sub-band of Gabor wavelet
Qiusheng Lian · Journal of Yanshan University · 2013
Face recognition based on sparse representation classification often extracts the entire features,such as Eigenfaces,Randomfaces and Fisherfaces,but neglects the superiority of local features in terms of overcoming illumination and facial expression changes.For solving the above problems,the sparse representation for face recognition algorithm based on partitioning energy sub-band of Gabor wavelet is proposed.Firstly,face image is transformed by Gabor wavelet at different scales and orientations,every sub-band is divided into several blocks.Secondly,every sub-band is blend into eigenvector and each sub-band eigenvector is combined together to get enhanced Gabor eigenvector.Finally,such eigenvector is applied to sparse representation for face recognition.The result of the experiment indicates that the algorithm has more strongly robust to the change of illumination and facial expression.