Automated multimodal biometrics using face and ear

Abstract

In this paper, we present an automated multimodal biometric system for the detection and recognition of humans using face and ear as input. The system is totally automated, with a trained detection system for face and for ear. We look at individual recognition rates for both face and ear, and then at combined recognition rates, and show that an automated multimodal biometric system achieves significant performance gains. We also discuss methods of combining biometric input and the recognition rates that each achieves. © 2009 Springer Berlin Heidelberg.