Robust Iris and fingerprint biometric fusion in multimodal feature template matching

Abstract

A fusion scheme in multimodal biometric system is proposed in the name of Multimodal Feature Template Matching (MTM) system derived from the two picture fused values of average point and weighted assessment point. The main objective of MTM algorithm is to design the average point fusion and weighted average point by fusion of Iris and fingerprint features. The MTM algorithm is assigned with avgweights based on their verification accuracy. A hybrid approach of combining biometric image level information id presented. The raw information is merged at image level. This integration addressed, provides a small template and resilience to attacks. However it does not improve the recognition performance, but the performances is also less combination to its unimodal counterpart. Confidence level integration of compatible features of two different uncorrelated biometric traits fingerprint and iris provides sustainable improvement in performance accuracy compared to other integration methods as well as best unimodal system. Fingerprint and iris integration approaches presented in this proposed are more robust and reliable.