NDLI: Face liveness detection: fusing colour texture feature and deep feature

Content Provider	IET Digital Library
Author	Chen, Fu Mei Wen, Chang Xie, Kai Wen, Fang Qing Sheng, Guan Qun Tang, Xin Gong
Abstract	The identification which uses biological characteristics has been a current top in the recent past. However, numerous spoofing skills occur with the rising prosperity of advance recognition technology, especially in the detection and recognition of a face. In allusion to the problem above, more robust and accurate face spoofing detection schemes have been put forward. Convolutional neural networks (CNNs) have demonstrated extraordinary success in face liveness detection recently. In this study, an effective face anti-spoofing detection method based on CNN and rotation invariant local binary patterns (RI-LBP) has been proposed. First, the authors use CNN to extract deep features and use RI-LBP to extract colour texture features. In addition, the principal component analysis approach is employed to decrease the dimensions of deep characteristic. Moreover, two different features are fused before applying to support vector machine (SVM). Finally, the SVM classifier is adopted to identify genuine faces from fake faces. They have conducted extensive experiments to obtain a scheme of better generalisation capability for face anti-spoofing detection. The analysis results indicate that the proposed approach implements great generalisation capability over other state-of-the-art approaches within the intra-databases and cross-databases.
Starting Page	369
Ending Page	377
Page Count	9
ISSN	20474938
Volume Number	8
e-ISSN	20474946
Issue Number	Issue 6, Nov (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-bmt/8/6
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-bmt.2018.5235
Journal	IET Biometrics
Publisher Date	2019-05-03
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Accurate Face Advance Recognition Technology Biological Characteristic CNN Colour Texture Features Computer Vision And Image Processing Technique Convolutional Neural Network Deep Characteristic Deep Feature Detection Scheme Different Features Effective Face Anti-spoofing Detection Method Face Liveness Detection Face Recognition Fake Face Feature Extraction Fusing Colour Texture Feature Genuine Face Image Classification Image Colour Analysis Image Recognition Image Texture Knowledge Engineering Technique Neural Nets Numerous Spoofing Skills Optical, Image And Video Signal Processing Pattern Classification Principal Component Analysis Robust Face Rotation Invariant Local Binary Pattern Statistics Support Vector Machine Use RI-LBP
Content Type	Text
Resource Type	Article
Subject	Signal Processing Computer Vision and Pattern Recognition Software

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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