An Efficient Process of Human Recognition Fusing Palmprint and Speech features

This paper presents fusion of two biometric traits, i.e., palmprint and speech signal, at matching score level architecture uses weighted sum of score technique. The features are extracted from the pre-processed palm image and pre-processed speech signal. The features of a query image and speech signal are compared with those of a database images and speech signal to obtain matching scores. The individual scores generated after matching are passed to the fusion module. This module consists of three major steps i.e., normalization, generation of similarity score and fusion of weighted scores. The final score is then used to declare the person as genuine or an impostor. The system is tested on database collected by the authors for 120 subjects and gives an overall accuracy of 98.47% with FAR of 1.36% and FRR of 87%.