LAUSR

Face recognition is a most widely used and rapidly growing biometric technology. Lot of research has been done in this field, due to its significant applications in various sectors and their influence in our daily life such as securing financial transactions, information security, personal identification and surveillance systems. But face recognition systems are permeable to spoofing attack. The problem of spoofing can be minimized by detecting face liveness which is the main area of concern. Most researchers utilized only eyeblink as liveness indicator to detect face liveness. A novel face liveness detection algorithm with multiple liveness indicators has been proposed in this paper. Eyeblink sequence, lip movement and chin movement are the multiple liveness indicators that have been considered for reliable face liveness detection. Experimental results show that, the proposed method in conjunction with multiple liveness indicators significantly improves the security of face recognition system. The proposed method achieves higher liveness detection rate by detecting photo attack, eye-mouth photo imposter attack and video attack.