Multimodal Biometric Authentication using Palmprint and Fingerprint

Abstract

Biometric based authentication systems are becoming the foundation of an extensive array of highly secure identification and personal verification solutions. Depending upon the implicational usage the biometric features are categorized and taken for authentication. For authentication, Biometric technologies provide best security concern than others, so biometrics is preferred most commonly. But the difficult task is to find the appropriate biometric technique. Unimodal biometric type relies on the evidence of a single source of biometric information for Personal Identification.  But it has a lot of limitations in terms of the security and privacy. Multimodal biometric system is an advance level of a multi-biometric system that may use more than one correlated biometric measurement. They address the problem of non-universality, noisy sensor data, and large intra-user variations and also provide anti-spoofing that are commonly found in unimodal biometric systems. In this paper, we propose a bimodal biometric authentication system based on the features of Palmprint and Fingerprint. The extracted features are fused at feature level to obtain the multibiometric template. Final decision is made by multitemplate matching approach.