Open Access

REVIEW

A Survey on Face Anti-Spoofing Algorithms

Meigui Zhang^*, Kehui Zeng, Jinwei Wang

Nanjing University of Information Science and Technology, Nanjing, 210044, China

* Corresponding Author: Meigui Zhang. Email:

Journal of Information Hiding and Privacy Protection 2020, 2(1), 21-34. https://doi.org/10.32604/jihpp.2020.010467

Received 21 May 2020; Accepted 10 June 2020; Issue published 15 October 2020

Abstract

The development of artificial intelligence makes the application of face recognition more and more extensive, which also leads to the security of face recognition technology increasingly prominent. How to design a face anti-spoofing method with high accuracy, strong generalization ability and meeting practical needs is the focus of current research. This paper introduces the research progress of face anti-spoofing algorithm, and divides the existing face anti-spoofing methods into two categories: methods based on manual feature expression and methods based on deep learning. Then, the typical algorithms included in them are classified twice, and the basic ideas, advantages and disadvantages of these algorithms are analyzed. Finally, the methods of face anti-spoofing are summarized, and the existing problems and future prospects are expounded.

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Keywords

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