Multimodal Biometric System by Feature Level Fusion of Palmprint and Fingerprint

Abstract

Biometrics is the technology for measuring and analyzing human characteristics such as palmprint, fingerprint, voice, facial pattern, signature etc, for authentication purposes. Biometrics has been emerged as the most powerful and reliable means of personal authentication. Most biometric systems are unimodal, which rely on single source of information for authentication. But these systems have major problems such as noisy data, non-universality, intra-class variation, inter class similarities and spoofing attacks. To overcome these drawbacks, multimodal biometrics emerged as new research area in the field of security. This paper focuses on the fusion of palmprint and fingerprint with feature level fusion. The feature values of fingerprint and palmprint are extracted using thinning and Hidden Markov Model and then their values are fused.