Issue |
MATEC Web Conf.
Volume 292, 2019
23rd International Conference on Circuits, Systems, Communications and Computers (CSCC 2019)
|
|
---|---|---|
Article Number | 04006 | |
Number of page(s) | 5 | |
Section | Signal Processing | |
DOI | https://doi.org/10.1051/matecconf/201929204006 | |
Published online | 24 September 2019 |
Visible/Infrared face spoofing detection using texture descriptors
1 Computer Science Department, Faculty of Computers & Information Helwan University, 11795, Ain Helwan, Cairo, Egypt
2 College of Computing and Information Technology Arab Academy for Science, Technology and Maritime Transport AASTMT Smart Village, Giza, Egypt
* Corresponding author: shaimaa_muhammad@fci.helwan.edu.eg
With extensive applications of face recognition technologies, face anti-spoofing played an important role and has drawn a great attention in the security systems. This study represents a multi-spectral face anti-spoofing method working with both visible (VIS) and near-infrared (NIR) spectra imaging. Spectral imaging is the capture of images in multiple bands. Since these attacks are carried out at the sensor, operating in the visible range, a sensor operating in another band can give more cues regarding the artifact or disguise used to carry out the attack. Our experimental results of public datasets proved that the proposed algorithms gain promising results for different testing scenarios and that our methods can deal with different illuminations and both photo and screen spoofing.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.