ISSN 1000-1239 CN 11-1777/TP

Journal of Computer Research and Development ›› 2018, Vol. 55 ›› Issue (3): 643-650.doi: 10.7544/issn1000-1239.2018.20160417

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LBP and Multilayer DCT Based Anti-Spoofing Countermeasure in Face Liveness Detection

Tian Ye1, Xiang Shijun1,2   

  1. 1(School of Information Science and Technology, Jinan University, Guangzhou 510632); 2(State Key Laboratory of Information Security (Institute of Information Engineering, Chinese Academy of Sciences), Beijing 100093)
  • Online:2018-03-01

Abstract: As security problem has become the tightest bottleneck in the application of face recognition systems, rendering a face recognition system robust against spoof attacks is of great significance to be dealt with. In this paper, aimed at video-based facial spoof attacks, an innovative face antispoofing algorithm based on local binary patterns (LBP) and multilayer discrete cosine transform (DCT) is proposed. First, we extract face images from a target video at a fixed time interval. Second, the low-level descriptors, i.e., the LBP features are generated for each extracted face image. After that, we perform multilayer DCT on the low-level descriptors to obtain the high-level descriptors (LBP-MDCT features). To be more exact, in each layer, the DCT operation is implemented along the ordinate axis of the obtained low-level descriptors, namely the time axis of the entire target video. In the last stage, the high-level descriptors are fed into a support vector machine (SVM) classifier to determine whether the target video is a spoof attack or a valid access. In contrast to existing approaches, the outstanding experimental results attained by the proposed approach on two widely-used datasets (Replay-Attack dataset and CASIA-FASD dataset) demonstrat its performance superiority as well as its low complexity and high efficiency.

Key words: face antispoofing, local binary patterns (LBP), multilayer discrete cosine transform (DCT), Replay-Attack database, CASIA-FASD database

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