Face Spoofing Detection Using Local Graph Structure

DOI

10.2991/ccit-14.2014.70How to use a DOI?

Keywords

Local Graph Structure, image processing, pattern recognition, face recognition, face spoofing.

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.

Copyright

© 2014, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Housam Khalifa Bashier
AU  - Siong Hoe Lau
AU  - Pang Ying Han
AU  - Liew Yee Ping
AU  - Chiang Mee Li
PY  - 2014/01
DA  - 2014/01
TI  - Face Spoofing Detection Using Local Graph Structure
BT  - Proceedings of the 2014 International Conference on Computer, Communications and Information Technology
PB  - Atlantis Press
SP  - 270
EP  - 273
SN  - 1951-6851
UR  - https://doi.org/10.2991/ccit-14.2014.70
DO  - 10.2991/ccit-14.2014.70
ID  - Bashier2014/01
ER  -