Face spoofing detection based on improved local graph structure

Bashier, Housam Khalifa and Pang, Ying Han and Liew, Yee Ping and Chiang, Mee Li and Siong, Hoe Lau (2014) Face spoofing detection based on improved local graph structure. In: 2014 International Conference on Information Science and Applications (ICISA). Atlantis Press, pp. 270-273. ISBN 978-90786-77-97-0

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Abstract

Face spoofing attack is one of the recent security traits that face recognition systems are proven to be vulnerable to. The spoofing occurs when an attacker bypass the authentication scheme by presenting a copy of the face image for a valid user. Therefore, it’s very easy to perform face recognition spoofing attack with compare to other biometrics. This paper, addresses the problem of detecting imposter face image from live image. In practically, we address this problem from texture analysis point of view because the printed face usually has less quality defect that can be observed by extracting texture features. We adopt Local graph structure LGS to extract the features. Moreover, LGS is based on applying a dominant graph into the input image and it’s proved to be a powerful texture operator. Finally, extensive experimental analysis on NUAA showed an encouraging performance.

Item Type: Book Section
Uncontrolled Keywords: Local Graph Structure, image processing, pattern recognition, face recognition, face spoofing
Subjects: Q Science > QA Mathematics > QA75.5-76.95 Electronic computers. Computer science > QA76.75-76.765 Computer software
Divisions: Faculty of Information Science and Technology (FIST)
Depositing User: Ms Nurul Iqtiani Ahmad
Date Deposited: 25 Aug 2014 04:02
Last Modified: 05 Jan 2017 04:49
URI: http://shdl.mmu.edu.my/id/eprint/5693

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