A Fusion of Palm Print and Palm Vein Features for Person Identification Using Grey Coding Technique

Abstract

An effective bimodal palm print and palm vein biometric person recognition method is suggested in this paper. Palm print is referred to as the external biometric line comprising main lines, wrinkles, and ridges on the palm surface and the palm vein is the structure of the lines below the palm surface. For individuals, these patterns are unique, stable and they provide enormous important information for person identification. The features of both modalities are extracted using a Sobel operator and grey code encoding techniques. The suggested framework is rigorously checked on the CASIA multispectral database and uses decision level and feature level fusion techniques to achieve the best FAR 0.0047 & FRR 0.050. The Proposed image fusion technique results in performance improvement than the individual biometric identification.