A Novel Approach Based Multi Biometric Finger Vein Template Recognition System using HGF

Abstract

Abstract Finger vein(s) based biometrics is another way to deal with individual's distinguishing proof and has recently received much consideration. The strategy in light of low-level components, like the dark surface of finger vein is taken as standard. However, it is typically looked with numerous difficulties that involves affectability to noise and low neighbourhood consistency. Generally finger vein recognition in view of abnormal state highlights the portrayal that has ended up being a promising method to successfully defeat the above restrictions and enhance the framework execution. This research work proposes finger vein-based recognition technique making use of Hybrid BM3D Filter along with grouped sparse representation for image denoising and feature selection (Local Binary Pattern – LBP, Scale Invariant Feature Transform – SIFT) to evaluate features, key-points and perform recognition. The experimental results on two open databases of finger vein, i.e., HKPU and SDU show that the proposed method has enhanced the overall performance of finger vein pattern recognition system compared with other existing methods.