Article

Secure Face:Spoof Detection

Author(s):

Priyanka Agarwal, Pimpri Chinchwad College Of Engineering; Shambhavi Joshi ,Pimpri Chinchwad College Of Engineering; Kalyani Kamble ,Pimpri Chinchwad College Of Engineering

Keywords

Spoof Detection, Naive Bayes classifier, Edge Adaptive Hybrid Filter

Abstract

Spoofing attack against biometric systems is still an important issue. Face spoofing is a form of attack that is presenting a fake sample to the acquisition sensor with facial information of a valid user. Compared to various attacks against fingerprint, speech or iris recognition systems, the ubiquitous nature of image acquisition devices, such as cameras and smartphones, allows attackers to acquire facial images of a user easily and discretely. This paper presents a literature survey on spoof detection methods and proposes a method to detect whether the input face is spoofed or not. Edge Adaptive Hybrid Filter is used for image enhancement and Naive Bayes classifier is used for classification to detect spoofed face.

Reference

    [1] Tirunagari, Santosh, et al. "Detection of face spoofing using visual dynamics." IEEE Transactions on Information Forensics and Security 10.4 (2015): 762-777. [2] Boulkenafet, Zinelabidine, Jukka Komulainen, and Abdenour Hadid. "Face Spoofing Detection Using Colour Texture Analysis." IEEE Transactions on Information Forensics and Security 11.8 (2016): 1818-1830. [3] Li, Yuming, et al. "Face liveness detection and recognition using shearlet based feature descriptors." 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2016. [4] Alotaibi, Aziz, and Ausif Mahmood. "Enhancing computer vision to detect face spoofing attack utilizing a single frame from a replay video attack using deep learning." Optoelectronics and Image Processing (ICOIP), 2016 International Conference on. IEEE, 2016. [5] Phan, Quoc-Tin, et al. "FACE spoofing detection using LDP-TOP." Image Processing (ICIP), 2016 IEEE International Conference on. IEEE, 2016. [6] Boulkenafet, Zinelabidine, et al. "Scale space texture analysis for face anti-spoofing." Biometrics (ICB), 2016 International Conference on. IEEE, 2016. [7] Diviya, M., and Susmita Mishra. "A novel approach for detecting facial image spoofing using local ternary pattern." Science Technology Engineering and Management (ICONSTEM), Second International Conference on. IEEE, 2016.

Other Details

Paper ID: GRDJEV02I030012
Published in: Volume : 2, Issue : 3
Publication Date: 2017-03-01
Page(s): 1 - 3

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