Since the original Local Phase Quantization (LPQ) operator has a poor performance in extracting the texture features under illumination or noise effect, a method of face description is proposed which extracts the histogram sequence of Local Shearlet Phase Quantization (HLSPQ) from the magnitudes of Shearlet coefficients. First, In order to extract the multi-orientation information, the average fusion method is proposed to fuse the original Shearlet features of the same scale. Second, the fused image is divided into several units from which the local phase quantization operates is used to extract the local neighbor patterns. Then, the LPQ operates on each unit to extract the local neighbor patterns. Finally, the input face image is described by the histogram sequence extracted from all these region patterns. The experimental results on ORL, FERET and YALE face database can achieve high face recognition rate up to 98%, 95% and 97.78%, which shows that the proposed method has better effect on improving the recognition rate.