Finger Vein Image Enhancement Using RPL, Segmentation with Neural Networks

Abstract—Biometrics is a validation methodology that depends upon the automated identification or verification of personage based on their physiological or behavioural attributes. Finger Vein recognition is introduced as a foremost biometric identification technology in the perspective of security and reliability. Finger Vein provides the precise rates (very low FRR, FAR) of user identification among modern biometric technologies, making finger, one of the most consistent security solutions. This paper emphasis on improving and segmenting the reliability and effectiveness of the finger vein networks. The aim of the proposed hybrid approach is to minimize the computation time by enhancing the precision of vein pattern. Simulation results show that by merging these methods i.e. Repeated Line Tracking, Gabor Filter, Segmentation with Neural Networks, more accurate results are obtained than individually