Citation

Ashari, Nurul Nabihah and Ong, Thian Song and Tee, Connie and Teng, Jackson Horlick and Leong, Yu Fan (2021) Multi-Scale Texture Analysis For Finger Vein Anti-Spoofing. In: 2021 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET), 13-15 Sept. 2021, Kota Kinabalu, Malaysia.

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Abstract

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.

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	Biometrics, spoofing attack detection, presentation attack detection, multi-scale analysis
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800-8360 Electronics
Divisions:	Faculty of Engineering (FOE)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	05 Dec 2021 14:25
Last Modified:	31 Oct 2023 02:21
URII:	http://shdl.mmu.edu.my/id/eprint/9819

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