Citation

Ong, Thian Song and Teoh, Andrew Beng Jin and Sonai Muthu Anbananthen, Kalaiarasi and Teng, Jackson Horlick (2013) Multi-instance finger vein recognition using minutiae matching. In: Image and Signal Processing (CISP), 2013 6th International Congress. IEEE, 1730 -1735. ISBN 978-1-4799-2763-0

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Abstract

Among the various multi-modal biometric approaches, multi-instance biometric appears to be understudied despite it inherits the merits of multimodal biometrics system. Multi-instance biometrics is useful when the signal quality is too low for robust verification. As compared to other multi-modal approach, multi-instance fusion reduces the need of multiple acquisitions using different sensors and thus lessen both transaction time and sensor cost. In this work, we propose a reliable two-stage multi-instance finger vein recognition system based on minutiae matching method by integrating a unified minutia alignment and pruning approach using Genetic algorithm and the k-modified Hausdorff distance (k-MHD) measurement. The proposed method is evaluated by using the SDUMLA-HMT Finger Vein database. Experiments show the proposed method is able to attain promising recognition rate compared to its single biometrics counterpart. The best result is achieved by applying the k-nearest neighbor measurement alongside, where the recognition rate can be up to 99.7% when MHD is used for matching.

Item Type:	Book Section
Uncontrolled Keywords:	finger vein, minutiae, genetic algorithm, k-MHD matching
Subjects:	T Technology > T Technology (General)
Divisions:	Faculty of Information Science and Technology (FIST)
Depositing User:	Ms Suzilawati Abu Samah
Date Deposited:	07 Mar 2014 04:41
Last Modified:	05 Jan 2017 09:41
URII:	http://shdl.mmu.edu.my/id/eprint/5378

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