NDLI: Novel presentation attack detection algorithm for face recognition system: Application to 3D face mask attack

Content Provider	IEEE Xplore Digital Library
Author	Raghavendra, R. Busch, Christoph
Copyright Year	2014
Description	Author affiliation: Norwegian Biometric Laboratory, Gj⊘vik University College, Norway (Raghavendra, R.; Busch, Christoph)
Abstract	The face biometric systems are highly vulnerable for the presentation attack that can be carried out by presenting a photo or video or even a 3D mask. In this paper, we present a novel Presentation Attack Detection (PAD) algorithm that can accurately detect and mitigate the 3D mask attacks on a face recognition system. The proposed scheme extracts both local and global features from the captured face image. The local features employed in this work corresponds to the eye (periocular) and nose region that are expected to provide clue on the presence of the mask. In addition, we also capture the micro-texture variation as a global feature using Binarized Statistical Image Features (BSIF). We then train a linear Support Vector Machine (SVM) independently on these two features whose scores are fused using the weighted sum rule before making the decision about a real face or an artefact. Extensive experiments are carried out on the public 3D mask database 3DMAD that shows the superiority of the proposed scheme with an outstanding performance of HTER = 0.03%.
Starting Page	323
Ending Page	327
File Size	477770
Page Count	5
File Format	PDF
ISBN	9781479957514
DOI	10.1109/ICIP.2014.7025064
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-10-27
Publisher Place	France
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Feature extraction Face Three-dimensional displays Face recognition Databases Nose Support vector machines Counter measure Biometrics Security face mask attack
Content Type	Text
Resource Type	Article

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