Effect of facial expression in face biometry for a multimodal approach

Abstract

With the advancement of technology, security has become an inseparable part of it. But many factors often influence the accuracy of the authentication system. In this current scenario, the multimodal biometric system is used where information from different modalities are fused to address the weakness of the system. In the present work, a robust biometric authentication system proposed using face and facial expression as biometric modalities. Facial recognition is the most commonly used biometric system over the years. Facial expressions of an individual are unique and it is integrated as an additional layer along with face recognition system to enhance the security of the system as the current scenario tends towards intelligent security systems for real-time surveillance. After pre-processing, eigenvalue-based and local binary pattern (LBP)-based features are extracted from the face and facial expression and the information are fused. Finally, the authentication is done using image Euclidian distance (IMED) based classifier. This proposed work evaluated using the JAFFE and Yale database and 95.71% and 88.89% authentication accuracy is achieved, respectively.