Face Anti-Spoofing Techniques and Challenges: A short survey

Face images are the most commonly used and easily available biometric data in extremely accurate face recognition systems.Even while biometric technology is precise and improves system security, it is still vulnerable to spoof attacks when deceptive biometrics are used. Before submitting the face image to biometric systems, a face anti-spoofing system is often essential. Face recognition-based authentication methods are easily spoofed by a diverse range of attacks. The most common face attacks used in spoofing are replay,video,print, and 3D mask attacks reflected in texture, motion, and depth information.So, there is a need to design and develop a highly robust and accurate facing anti-spoofing algorithm with strong generalization ability, whichis the focus of this current research.Work of Literature shows the use of hand-crafted features and deep learning approaches to solve the spoofing issues. This survey aimstoexploreface anti-spoofing methods, assess the pre-eminent compromise between the criteria for identifying real from fake facial looks, and study the existing problems and prospects.