Finger vein recognition algorithms are usually based on grayscale images of vein distributions. However, because of the limitations of image acquisition devices, the uncertainties in the illumination intensity and the complexity of the tissue around the finger vessels (among other factors)even after image processing cause the resulting grayscale images to possess irregular shadows and non-venous characteristics, which may reduce the accuracy of the recognition results. Therefore, this paper proposed a new finger vein identification algorithm based on binary images to minimize the interference of non-venous factors in the identification process. First, the features from accelerated segment test algorithm was used to extract the pixel points at the edges of vein textures as feature points, and then the feature vectors were constructed. Further, to improve the matching precision, a new matching algorithm based on circular neighborhoods was proposed. The weighted matching distance was used to describe the degree of similarity between images. The average recognition rate of the proposed method when applied to the finger vein database published by Shandong University is 0.993, and the equal error rate is 0.019 6.These results demonstrate the effectiveness of the algorithm and provide a new basis for the design of vein recognition algorithms.