Palm vein recognition is a relatively new method in biometrics. This paper presents an effective palm vein feature extraction approach for improving the efficiency of palm vein identification. In this paper, relevant preprocessing steps as rotation and extraction of the Region of Interest are presented. In feature extraction, multiple 2D Gabor filters with 4 orientations are employed to extract the phase information on a palm vein image, which is then merged into unique feature according to an encoding rule. Hamming distance is used for vein recognition. Experiments are carried on a selfmade palm vein database. Experimental results show that the method in this paper achieved a higher correct recognition rate and a faster speed.