Palm Vein Imaging Enhancement in Highly Reflective Hand Scenarios

Palm vein recognition is an emerging biometric recognition technology that has received significant attention in recent years. However, we have discovered that in some challenging scenarios, such as wet or bright hands, the collected palm vein images are seriously reflective, which affects the recognition of palm veins. Rather than proposing a high-complexity suppression algorithm, in this paper, we (WeChat Pay Lab 33) present a palmprint collection system based on infrared polarization imaging for reflection suppression and palm vein imaging enhancement. The system's core concept involves using two polarizers to suppress surface reflections. Specifically, the first polarizer converts the emitted infrared light into linearly polarized light. The second polarizer filters out reflected light that is not in the correct direction. Furthermore, we conduct extensive experiments to explore the effects of the number and angle of polarizers on suppression and verify the effectiveness of this system in multiple scenarios.