International Journal of Internet, Broadcasting and Communication

The Institute of Internet, Broadcasting and Communication (한국인터넷방송통신학회)
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A Margin-based Face Liveness Detection with Behavioral Confirmation

  • Tolendiyev, Gabit (Department of Computer Engineering, Dongseo University) ;
  • Lim, Hyotaek (Department of Computer Engineering, Dongseo University) ;
  • Lee, Byung-Gook (Department of Computer Engineering, Dongseo University)
  • Received : 2021.03.25
  • Accepted : 2021.04.04
  • Published : 2021.05.31
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Abstract

This paper presents a margin-based face liveness detection method with behavioral confirmation to prevent spoofing attacks using deep learning techniques. The proposed method provides a possibility to prevent biometric person authentication systems from replay and printed spoofing attacks. For this work, a set of real face images and fake face images was collected and a face liveness detection model is trained on the constructed dataset. Traditional face liveness detection methods exploit the face image covering only the face regions of the human head image. However, outside of this region of interest (ROI) might include useful features such as phone edges and fingers. The proposed face liveness detection method was experimentally tested on the author's own dataset. Collected databases are trained and experimental results show that the trained model distinguishes real face images and fake images correctly.

Keywords

Acknowledgement

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2020R1A2C1008589).

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