Citation
Ardianto, William and Ong, Thian Song and Lau, Siong Hoe and Goh, Michael Kah Ong (2016) Finger Vein verification using local histogram of hybrid texture descriptors. In: 2015 IEEE International Conference on Signal and Image Processing Applications (ICSIPA). IEEE, pp. 304-308. ISBN 978-1-4799-8996-6
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Official URL: http://doi.org/10.1109/ICSIPA.2015.7412209
Abstract
Lately, finger vein has been recognized as an efficacious biometric method for user authentication due to the uniqueness of vein patterns and its insusceptibility to forgery because the vein patterns reside inside the human body. In this work, hybrid histogram descriptor is the proposed method. This method utilizes the sign and magnitude components of the texture extracted by using Binary Gradient Contour (BGC). Subsequently, the histogram is locally computed to determine the weight distribution of the sign and magnitude value for the hybrid texture descriptors. The extensive experimental results demonstrate the overall superiority of the proposed method with the EER as low as 0.353%.
Item Type: | Book Section |
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Uncontrolled Keywords: | magnitude, BGC, local histogram, texture, sign |
Subjects: | T Technology > TA Engineering (General). Civil engineering (General) |
Divisions: | Faculty of Information Science and Technology (FIST) |
Depositing User: | Ms Rosnani Abd Wahab |
Date Deposited: | 08 Dec 2017 15:08 |
Last Modified: | 08 Dec 2017 15:08 |
URII: | http://shdl.mmu.edu.my/id/eprint/6589 |
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