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.
Keywords
Cite This Article
M. Zhang, K. Zeng and J. Wang, "A survey on face anti-spoofing algorithms,"
Journal of Information Hiding and Privacy Protection, vol. 2, no.1, pp. 21–34, 2020. https://doi.org/10.32604/jihpp.2020.010467