Improved Liveness Detection in Dorsal Hand Vein Videos using Photoplethysmography

In this study, a previously published infrared finger vein liveness detection scheme is tested for its applicability on dorsal hand vein videos. A custom database consisting of five different types of presentation attacks recorded with transillumination as well as reflected light illumination is examined. Additionally, two different methods for liveness detection are presented in this work. All methods described employ the concept of generating a signal through the change in average pixel illumination, which is referred to as Photoplethysmography. Feature vectors in order to classify a given video sequence are generated using spectral analysis of the time series. Experimental results show the effectiveness of the proposed methods.