In order to improve the recognition speed with effective recognition performance of palm vein identification system, a fast palm vein identification algorithm based on grayscale surface matching is proposed. The algorithm extracts region of interest (ROI) of palm vein image firstly. Then, the ROI is equally divided into several sub-regions. The algorithm computes average value of the grayscale of every sub-region. These average values construct an image for matching. At the stage of matching, the algorithm computes the difference between two pixels from two matching images and gets the grayscale difference surface. It calculates the variance of the grayscale difference surface and considers this variance as the distance between two feature surfaces. At last, it decides whether these two images come from the same hand or not according to the variance. A self-built palm vein database is used in the experiment. The experimental result shows that the scheme with sub-region parameter of 8 pixel×8 pixel reaches correct recognition rate (CRR) of 97.94%, with recognition time of only 0.163 ms. Compared with the traditional palm vein recognition method, the proposed method increases recognition speed with effective recognition performance.