As a new and promising biometric feature, thermal palm vein pattern has drawn lots of attention in research and application areas. Many algorithms have been proposed for authentication since palm vein has special characteristics, such as liveness detection and hard to forgery. However, the detection accuracy of palm vein quite depends on the preprocessing and feature representation, which is supposed to be translation and rotation invariant to some extent. In this paper, we proposed an effective method for palm vein identification based on Gabor wavelet features which contains five steps: image acquisition, ROI detection, image preprocessing, features extraction, and matching. The 178 palm vein images from 101 persons were used to test the proposed palm vein recognition approach, where 176 images were correctly recognized with two in failure. The experimental results demonstrate the effectiveness of the proposed approach.