Citation

Ardianto, William and Ong, Thian Song and Tee, Connie and Goh, Michael Kah Ong (2015) Multi-instance finger vein recognition using local hybrid binary gradient contour. In: 2015 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA). IEEE Xplore, pp. 1226-1231. ISBN 978-9-8814-7680-7

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Abstract

In a finger vein authentication system, the image of a finger acquired for recognition always suffers from noises due to imperfect acquisition device, signal distortion, and variability of individual physical appearance over time. To improve the system performance, we propose a multi-instances finger vein recognition using feature level fusion. Local Hybrid Binary Gradient Contour (LHBGC) is proposed as the finger texture descriptor and SVM is used for classification. Experiments are conducted using the Shandong finger vein database (SDUMLA-HMT) and also the University Sains Malaysia finger vein database (FV-USM). Experimental results show a significant increase in performance accuracy when more than one fingers are combined, with an EER as low as 0.0038%.

Item Type:	Book Section
Uncontrolled Keywords:	finger vein, LHBGC, BGC, multi-instance
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:	Faculty of Information Science and Technology (FIST)
Depositing User:	Ms Rosnani Abd Wahab
Date Deposited:	30 Nov 2017 17:51
Last Modified:	30 Nov 2017 17:51
URII:	http://shdl.mmu.edu.my/id/eprint/6537

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