Multi-Scale Texture Analysis For Finger Vein Anti-Spoofing

In the recent years, finger vein biometrics has been gaining traction in commercial uses. Despite its wide deployment for user authentication, there is still a risk associated with insecure biometric capture process known as presentation attacks where the attacker uses fake finger vein pattern to sp...

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Bibliographic Details
Published in:	2021 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET) pp. 1 - 6
Main Authors:	binti Ashari, Nurul Nabihah, Ong, Thian Song, Connie, Tee, Teng, Jackson Horlick, Leong, Yu Fan
Format:	Conference Proceeding
Language:	English
Published:	IEEE 13-09-2021
Subjects:	Authentication Benchmark testing biometrics Biometrics (access control) Conferences Fingers Histograms multi-scale analysis presentation attack detection spoofing attack detection Veins
Online Access:	Get full text
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Summary:	In the recent years, finger vein biometrics has been gaining traction in commercial uses. Despite its wide deployment for user authentication, there is still a risk associated with insecure biometric capture process known as presentation attacks where the attacker uses fake finger vein pattern to spoof the finger vein sensor. This raises the need for an efficient method to detect spoofed finger vein images to ensure the security of the system. In this paper, a multi-scale histogram of oriented gradients representation is proposed for presentation attack detection (PAD) with minimal pre-processing step involved. The results are evaluated with a benchmark dataset and compared with the other PAD methods with promising results.
DOI:	10.1109/IICAIET51634.2021.9574036