A low cost wrist vein sensor for biometric authentication
Raghavendra Ramachandra, Christoph Busch · 2016
Biometric recognition of an individual can be done based on physiological characteristics such as a face, palmprint, vein, etc. and behavioural characteristics which include gait, keystroke, mouse dynamics, etc. Among the various biometric modalities, the wrist vein recognition has been known for high accuracy, stability and resistance to spoofing. The success of wrist vein biometrics strongly correlates with the quality of the wrist vein image captured using the sensor. In this paper, we present a new wrist vein sensor that can capture a high-quality wrist vein image using Near infrared (NIR) lighting. The NIR lighting employed in this work can emit light in a spectrum of 940nm that in turn is used to illuminate the wrist area of the hand. The presented sensor employs a single camera with a simple physical structure that will further improve the quality of the light to properly illuminate the wrist hand region to capture good quality wrist vein images. Extensive experiments are carried out on our newly collected database comprised of 50 subjects resulting in 100 unique wrist veins. We also present a comprehensive evaluation of nine different state-of-the-art techniques that demonstrated the outstanding performance of the Log-Gabor and Sparse Representation Classifier (SRC) with an EER of 1.63% and the GMR of 94.01 at FMR = 10-1%.