2020/04/16 by Liping Zhang, Weijun Li, Zhang, Liping +3
Biochemistry, Genetics and Molecular Biology · Computer Science · #Biometric Identification and Security #Computer Vision and Pattern Recognition (cs.CV) #Dermatoglyphics and Human Traits #FOS: Computer and information sciences #Face recognition and analysis #cs.CV
paper · pdf · doi:10.48550/arxiv.2004.07489
arxiv created 2020/04/16 · openalex publication_date 2020/04/16 · arxiv updated 2020/04/17 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Local feature descriptors exhibit great superiority in finger vein recognition due to their stability and robustness against local changes in images. However, most of these are methods use general-purpose descriptors that do not consider finger vein-specific features. In this work, we propose a finger vein-specific local feature descriptors based physiological characteristic of finger vein patterns, i.e., histogram of oriented physiological Gabor responses (HOPGR), for finger vein recognition. First, prior of directional characteristic of finger vein patterns is obtained in an unsupervised manner. Then the physiological Gabor filter banks are set up based on the prior information to extract the physiological responses and orientation. Finally, to make feature has robustness against local changes in images, histogram is generated as output by dividing the image into non-overlapping cells and overlapping blocks. Extensive experimental results on several databases clearly demonstrate that the proposed method outperforms most current state-of-the-art finger vein recognition methods.