Multi-Instance Finger Vein Recognition System using Local Hybrid Binary Gradient Contour

Finger vein recognition is a type of biometric technology that uses the vein pattern inside the finger as a personal authenticator. Finger vein images are usually acquired using an infrared imaging device. Finger vein recognition has several advantages over the other hand-based biometrics like finge...

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主要作者:	Ardianto, William
格式:	Thesis
出版:	2016
主題:	TK7800-8360 Electronics
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id	my-mmu-ep.6889
record_format	uketd_dc
spelling	my-mmu-ep.68892017-09-07T10:30:07Z Multi-Instance Finger Vein Recognition System using Local Hybrid Binary Gradient Contour 2016-04 Ardianto, William TK7800-8360 Electronics Finger vein recognition is a type of biometric technology that uses the vein pattern inside the finger as a personal authenticator. Finger vein images are usually acquired using an infrared imaging device. Finger vein recognition has several advantages over the other hand-based biometrics like fingerprint. For example, finger vein is hard to counterfeit as it reside in the human body, and the vein pattern is not affected by skin condition. Generally, there are three kinds of features that can be extracted from a finger vein, namely line-based, texture-based, and points-based features. Line-based feature uses the blood vascular pattern as a feature, while texture-based feature extracts the texture of the finger vein. On the other hand, points-based feature employs the minutiae of a segmented vein pattern as a feature. Line-based and point-based features can achieve high accuracy in recognition. However the accuracy depends very much on the quality of the image. Low quality images such as optical blurring, irregular shading or noise may lead to false or missing vein pattern, thus affecting the recognition accuracy. To solve this problem, texture-based feature is chosen in this study. This feature representation also has an advantage in terms of processing time because it does not require additional vein pattern extraction process. In this research, Local Hybrid Binary Gradient Contour (LHBGC) and Hierarchical Local Binary Pattern (HLBP) are proposed as the texture descriptor. LHBGC is a modified version of Binary Gradient Contour (BGC). The original BGC only extracts the sign component from the image. However, LHBGC utilises both the sign and magnitude components from the image. Local histogram is used to generate the vector representation from the texture and magnitude components. HLBP is multiscale LBP that fully utilised the non-uniform texture pattern without any training required. HLBP firstly extract the uniform pattern for biggest radius. Then, for those non-uniform patterns, the counterpart LBP of smaller radius is extracted. Among the new LBP, those non-uniform patterns is further processed to extract the uniform pattern in even smaller radius. 2016-04 Thesis http://shdl.mmu.edu.my/6889/ http://library.mmu.edu.my/diglib/onlinedb/dig_lib.php masters Multimedia University Faculty of Information Science and Technology
institution	Multimedia University
collection	MMU Institutional Repository
topic	TK7800-8360 Electronics
spellingShingle	TK7800-8360 Electronics Ardianto, William Multi-Instance Finger Vein Recognition System using Local Hybrid Binary Gradient Contour
description	Finger vein recognition is a type of biometric technology that uses the vein pattern inside the finger as a personal authenticator. Finger vein images are usually acquired using an infrared imaging device. Finger vein recognition has several advantages over the other hand-based biometrics like fingerprint. For example, finger vein is hard to counterfeit as it reside in the human body, and the vein pattern is not affected by skin condition. Generally, there are three kinds of features that can be extracted from a finger vein, namely line-based, texture-based, and points-based features. Line-based feature uses the blood vascular pattern as a feature, while texture-based feature extracts the texture of the finger vein. On the other hand, points-based feature employs the minutiae of a segmented vein pattern as a feature. Line-based and point-based features can achieve high accuracy in recognition. However the accuracy depends very much on the quality of the image. Low quality images such as optical blurring, irregular shading or noise may lead to false or missing vein pattern, thus affecting the recognition accuracy. To solve this problem, texture-based feature is chosen in this study. This feature representation also has an advantage in terms of processing time because it does not require additional vein pattern extraction process. In this research, Local Hybrid Binary Gradient Contour (LHBGC) and Hierarchical Local Binary Pattern (HLBP) are proposed as the texture descriptor. LHBGC is a modified version of Binary Gradient Contour (BGC). The original BGC only extracts the sign component from the image. However, LHBGC utilises both the sign and magnitude components from the image. Local histogram is used to generate the vector representation from the texture and magnitude components. HLBP is multiscale LBP that fully utilised the non-uniform texture pattern without any training required. HLBP firstly extract the uniform pattern for biggest radius. Then, for those non-uniform patterns, the counterpart LBP of smaller radius is extracted. Among the new LBP, those non-uniform patterns is further processed to extract the uniform pattern in even smaller radius.
format	Thesis
qualification_level	Master's degree
author	Ardianto, William
author_facet	Ardianto, William
author_sort	Ardianto, William
title	Multi-Instance Finger Vein Recognition System using Local Hybrid Binary Gradient Contour
title_short	Multi-Instance Finger Vein Recognition System using Local Hybrid Binary Gradient Contour
title_full	Multi-Instance Finger Vein Recognition System using Local Hybrid Binary Gradient Contour
title_fullStr	Multi-Instance Finger Vein Recognition System using Local Hybrid Binary Gradient Contour
title_full_unstemmed	Multi-Instance Finger Vein Recognition System using Local Hybrid Binary Gradient Contour
title_sort	multi-instance finger vein recognition system using local hybrid binary gradient contour
granting_institution	Multimedia University
granting_department	Faculty of Information Science and Technology
publishDate	2016
_version_	1747829641626779648

Multi-Instance Finger Vein Recognition System using Local Hybrid Binary Gradient Contour

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