Face Spoofing Detection Using Local Graph Structure
Housam Khalifa Bashier, Siong Hoe Lau, Pang Ying Han, Liew Yee Ping, Chiang Mee Li
Housam Khalifa Bashier
Available Online January 2014.
- https://doi.org/10.2991/ccit-14.2014.70How to use a DOI?
- Local Graph Structure, image processing, pattern recognition, face recognition, face spoofing.
- 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
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 - https://doi.org/10.2991/ccit-14.2014.70 ID - Bashier2014/01 ER -