Face Recognition Based on Collaborative Sparse Representation with Dictionary Learning

For sparse face recognition algorithm lacking of identification information, face recognition based on collaborative representation with dictionary learning is proposed. Firstly the LC-KSVD dictionary learning algorithm is used to get a discriminant dictionary. The collaborative sparse representation algorithm is conditioned to complete the classification, the sparse coefficients of the sample in the dictionary are solved by using the L2 norm instead of the L1 norm. The collaborative representation is accustomed to calculate the residuals of each category. Finally, the category is got by comparison. Experimental results on the common face database show that the algorithm can effectively improve the recognition rate without reducing the speed.