Bimodal recognition based on thumbprint and thumb image using bayesian classfier

The purpose of this project is to develop a Thumb image classification module which able to predict the gender from the image input. This module can be integrated into the current thumb print recognition system to form a bi-modal biometric system. With this add in module, the performance of the reco...

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Main Author:	Low, Zhi Wei
Format:	Thesis
Language:	English
Published:	2010
Subjects:	Unspecified
Online Access:	http://eprints.utm.my/id/eprint/26427/1/LowZhiWeiMFKE2010.pdf
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id	my-utm-ep.26427
record_format	uketd_dc
spelling	my-utm-ep.264272017-06-14T04:32:55Z Bimodal recognition based on thumbprint and thumb image using bayesian classfier 2010 Low, Zhi Wei Unspecified The purpose of this project is to develop a Thumb image classification module which able to predict the gender from the image input. This module can be integrated into the current thumb print recognition system to form a bi-modal biometric system. With this add in module, the performance of the recognition system will significantly increase since the database search time is reduce into almost half when only the gender matched is considered. The development of this module is based on the Bayesian Classifier method by having input of the textural analysis, thumb area consumption and the thumb width size. The textural analysis is using the GLCM (Gray Level Co-occurrence Matrix) with its properties of contrast, correlation, energy and homogeneity. The thumb area and size calculation is based on a cropped image which has the thumb over a certain boundary. Due to the usage model of searching the database, the training set and the verification set is coming from the same data sets. The Bayesian Classifier algorithm is implemented in the MATLAB code. Few GLCM pixel distance analysis was done to evaluate the module performance. With the distance pixel of 2, it had shown the best accuracy among the result of other pixel combination. Result for male matching 82.35% and female matching is 81.82%. 2010 Thesis http://eprints.utm.my/id/eprint/26427/ http://eprints.utm.my/id/eprint/26427/1/LowZhiWeiMFKE2010.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:77855?queryType=vitalDismax&query=+Bimodal+recognition+based+on+thumbprint+and+thumb+image+using+bayesian+classfier+&public=true masters Universiti Teknologi Malaysia, Faculty of Electrical Engineering Faculty of Electrical Engineering
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	Unspecified
spellingShingle	Unspecified Low, Zhi Wei Bimodal recognition based on thumbprint and thumb image using bayesian classfier
description	The purpose of this project is to develop a Thumb image classification module which able to predict the gender from the image input. This module can be integrated into the current thumb print recognition system to form a bi-modal biometric system. With this add in module, the performance of the recognition system will significantly increase since the database search time is reduce into almost half when only the gender matched is considered. The development of this module is based on the Bayesian Classifier method by having input of the textural analysis, thumb area consumption and the thumb width size. The textural analysis is using the GLCM (Gray Level Co-occurrence Matrix) with its properties of contrast, correlation, energy and homogeneity. The thumb area and size calculation is based on a cropped image which has the thumb over a certain boundary. Due to the usage model of searching the database, the training set and the verification set is coming from the same data sets. The Bayesian Classifier algorithm is implemented in the MATLAB code. Few GLCM pixel distance analysis was done to evaluate the module performance. With the distance pixel of 2, it had shown the best accuracy among the result of other pixel combination. Result for male matching 82.35% and female matching is 81.82%.
format	Thesis
qualification_level	Master's degree
author	Low, Zhi Wei
author_facet	Low, Zhi Wei
author_sort	Low, Zhi Wei
title	Bimodal recognition based on thumbprint and thumb image using bayesian classfier
title_short	Bimodal recognition based on thumbprint and thumb image using bayesian classfier
title_full	Bimodal recognition based on thumbprint and thumb image using bayesian classfier
title_fullStr	Bimodal recognition based on thumbprint and thumb image using bayesian classfier
title_full_unstemmed	Bimodal recognition based on thumbprint and thumb image using bayesian classfier
title_sort	bimodal recognition based on thumbprint and thumb image using bayesian classfier
granting_institution	Universiti Teknologi Malaysia, Faculty of Electrical Engineering
granting_department	Faculty of Electrical Engineering
publishDate	2010
url	http://eprints.utm.my/id/eprint/26427/1/LowZhiWeiMFKE2010.pdf
_version_	1747815473779572736

Bimodal recognition based on thumbprint and thumb image using bayesian classfier

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