Presentation Attack Detection Algorithms for Finger Vein Biometrics: A Comprehensive Study

Finger vein biometric systems have shown a vulnerability to presentation attacks (or direct attack or spoof attack). The presentation attacks have raised crucial security issues for finger vein biometric systems mainly due to the widespread application of these biometric sensors in the financial sector. In this paper, we present a novel algorithm to detected the presentation attack on a finger vein recognition system. The proposed method relies on the texture analysis using steerable pyramids, and the final decision is carried out by classifying the textures features using Support Vector Machines (SVM). Furthermore, we have also introduced a new kind of attack by using a smartphone display for the first time. Extensive experiments are carried out on a large-scale database of 300 unique finger veins collected from 100 subjects. We introduce a new finger vein artefact database collected using three different kinds of artefacts namely: (1) ink jet print (2) laser jet print and (3) smartphone display. An extensive comparison of the proposed scheme with ten different Presentation Attack Detection (PAD) demonstrated the efficacy of the proposed scheme.