Study of Finger Biometrics on Finger Semantic Segmentation and Finger Shape Authentication

Junduan Huang, Dacan Luo, Weili Yang, Jiahui Pan, Wenxiong Kang

Abstract: In hand-based biometrics, fingerprint, finger vein, finger knuckle print, palm print, palm vein, dorsal hand vein, and hand shape are the traits that are getting much attention. However, finger shape (FS), a forgettable trait, has not been studied specifically for identification purposes. In this work, we explore this content as a complement to the hand-based biometrics. Firstly, we annotate the FS on a publicly available finger vein dataset as the ground truth for finger semantic segmentation. Then we explore the finger semantic segmentation task on the annotated data and propose a lightweight network, namely FinSeg-Net (finger segmentation network). Finally, we conduct the FS authentication experiment based on four matching methods; experimental results show that the FS traits can achieve identity authentication. This work is the first study for FS biometrics specifically, and built the first FS dataset, which will be accessed via: https://github.com/SCUT-BIP-Lab/FinSeg.

External IDs:dblp:conf/icmcs/HuangLYPK25