Multimodal biometric system based on information set theory and refined scores

Abstract

This paper presents the development of a multimodal biometric system comprising a behavioral biometric called gait and a physiological biometric called hand vein pattern. Toward the unified feature extraction, we use the information set approach to represent the frame of a gait sequence by the feature called the effective gait information and the vein pattern image by the feature called the effective vein information using the Hanman---Anirban entropy function. Using these two features for the two modalities, we go in for the score level fusion which gives a limited accuracy. In order to improve the performance refined scores approach is proposed where in the original scores are refined by using the cohort (neighborhood) scores. The performance of the proposed approach is demonstrated on two databases.