2021 International Conference on INnovations in Intelligent SysTems and Applications (INISTA) | 2021

A Review of Face Anti-spoofing Methods for Face Recognition Systems

 
 
 

Abstract


The applicability, popularity, and usage of face recognition systems are undoubtedly increasing due to their advantages of being very convenient, contactless, and nonintrusive when compared with other biometric systems such as voice recognition and fingerprint. Unfortunately, it is the most vulnerable to spoofing attacks as a registered user’s photographs/videos can be gotten with ease through the internet or simply capturing their face using a camera, even without the consent or physical contact with him/her. Hence, the need for the development of anti-spoofing measures against such attacks. Several efforts have been in place in research for the development of face anti-spoofing methods. In this study, authors reviewed various anti-spoofing methods by several authors by searching related papers using keywords from online sources. This paper discusses several approaches to face spoof detection, the different types of face-spoof attack, and provide a taxonomy of the various anti-spoofing methods. The results are presented in a tabular form, providing a comprehensive list of publicly available face anti-spoof databases and a performance comparison table of several approaches.

Volume None
Pages 1-9
DOI 10.1109/INISTA52262.2021.9548404
Language English
Journal 2021 International Conference on INnovations in Intelligent SysTems and Applications (INISTA)

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