This paper presents a face recognition method based on Local Phase Quantization and Multi-Metric classification.First

LPQ operator is used to extract the LPQ Histogram Sequence(LPQHS) from block grey-level face images.Second

The feature selection method based on PCA+LDA is applied to extract feature subspace.Finally

Face recognition is realized based on the multi-metric classification principle.The proposed method can effectively extract the face texture

and can greatly reduce the amount of training data

and the dimension of the amount of data has nothing to do with the original image size.The simulation experiments illustrate that the proposed method obtains better recognition rate on ORL face database comparing to other classical methods.