Face Spoofing and Counter-Spoofing: A Survey of State-of-the-art Algorithms


  • Dakshina Ranjan Kisku Department of Computer Science and Engineering, National Institute of Technology Durgapur, Mahatma Gandhi Avenue, Durgapur 713209, West Bengal, INDIA http://orcid.org/0000-0003-1116-2972
  • Rinku Datta Rakshit Department of Information Technology, Asansol Engineering College Asansol, West Bengal, India




Biometrics, Face biometric, Face spoofing, Face anti-spoofing, Printed photo attack, Replay video attack, 3D mask attack, Plastic surgery attack, Texture analysis, Motion analysis, Liveness detection, Image quality analysis


In the current scenario of biometric-based identity verification, a face is still being proved to be an essential physiological evidence for successful person identification without letting know the target. Nevertheless, repeated attacks of intruders can cause the face recognition system insecure because of easy availability of face images or pictures of a person in social networks or in other networked resources. Spoofing facial identity in a biometric system is not a difficult task for intruders. When an intruder presents a photograph or a video containing a face of a person in front of a networked camera which is integrated with a face biometric system, spoofing is referred to as presentation attack. Without anti-spoofing mechanisms, biometric systems are at high risk in case of susceptible attacks. Thus, detecting face spoof in a face biometric system is a challenging research field. The aim of this book is to summarize some of the most popular face spoof detection techniques which are proved to be beneficial for the researchers to make it an indispensable aspect.

Author Biography

Dakshina Ranjan Kisku, Department of Computer Science and Engineering, National Institute of Technology Durgapur, Mahatma Gandhi Avenue, Durgapur 713209, West Bengal, INDIA

Department of Computer Science and Engineering

Assistant Professor


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How to Cite

Kisku, D. R., & Datta Rakshit, R. (2017). Face Spoofing and Counter-Spoofing: A Survey of State-of-the-art Algorithms. Transactions on Machine Learning and Artificial Intelligence, 5(2), 31. https://doi.org/10.14738/tmlai.52.3130