Transparent non-intrusive multimodal biometric system for video conference using the fusion of face and ear recognition

Mono-modal biometric systems face many limitations such as noisy data, intra-class variations, distinctiveness, spoof attacks, non-universality, and unacceptable error rates. Working on enhancing the performance of a mono-modal biometric system may not be highly efficient and effective. A multimodal biometric system combines two or more biometric features into a single identification system. It aims to improve several of the mono-modal biometric systems drawbacks and improve the recognition coverage and performance. In this paper, a transparent non-intrusive multimodal biometric system based on the fusion of the face and ear biometrics is proposed to identify individuals during a video conference environment with minimal explicit user involvement and hassle. The results of the experiment show that the performance of the transparent non-intrusive multimodal biometric system of the face and ear is higher than that of the mono-modal face or ear.