Citation

Seow, Albert Wei Jiann and Ong, Thian Song and Teng, Jackson Horlick (2025) Robust Presentation Attack Detection in Finger Vein Recognition using ECS-LTP And LPQ Methods. In: 2025 International Conference on Information and Communication Technology, ICoICT 2025, 30 July 2025 - 31 July 2025, Bandung, Indonesia.

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Abstract

This research focuses on the development of a Presentation Attack Detection method for Finger Vein Recognition systems. Finger vein biometrics is an emerging technology that utilizes the unique vascular patterns within the finger for personal recognition. However, finger vein systems remain vulnerable to impersonate attacks by using forged images, commonly refer to as presentation attacks. This study incorporates two robust texture-based PAD methods, namely Extended Centre Symmetric Local Ternary Pattern and Local Phase Quantization. The proposed methods are evaluated using SCUT-FVD datasets from South China University of Technology and VERA from Idiap Research Institute, achieving lowest Average Classification Error Rate of 0.12% and 0%, respectively

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	Anti-spoofing, ECS-LTP, Feature Extraction, Finger Vein, LPQ, presentation attack detection
Subjects:	Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science
Divisions:	Faculty of Information Science and Technology (FIST)
Depositing User:	Nurin Syazwani Azmi
Date Deposited:	10 Dec 2025 08:09
Last Modified:	13 Dec 2025 11:52
URII:	http://shdl.mmu.edu.my/id/eprint/15047

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