Study of Machine Learning Algorithm based on Face Anti-Spoofing Detection

– Face spoofing detection is one of the most well-studied problems in computer vision. Face recognition has become a widely adopted technique in biometric authentication systems. In face recognition based authentication techniques, the system first recognized the person to verify the legitimacy of the user before granting access to the system resources. The system must be able to determine the liveness of the person in front of the camera, for example, by recognizing the face and denying the types of face presentation attacks related to photographs, videos and the 3D mask of the targeted person. Attackers try to directly or indirectly, masquerade the biometric system as another person by forging biometric traits and get unauthorized access. This work studies computer vision- based feature extraction techniques for real and spoof face imaging and combines different features in the area of face anti-spoofing.