In order to overcome the error interference caused by changes in intensity and direction of illumination

a face recognition method based on label consistent（ LC）-KSVD dictionary learning is proposed.Firstly

the image is preprocessed by histogram equalization and wavelet denoising. Then

the PCA reduce dimensionality and extract feature on the image to construct an initial dictionary. Next

we introduce constraints in the process of dictionary learning. The new dictionary with discriminating ability is obtained. Then

the sparse coefficients of test samples under the new dictionary are calculated and the class association reconstruction is carried out. Finally

the recognition is completed according to the reconstruction error. The experimental results demonstrate the effectiveness of the improved algorithm.