Fuzzy C mean clustering in off-line handwriting signature verfication system

This research is the first research that suggests the usage of the stable region of a signature for verification purpose. This research highlighted the design and development of the proposed Fuzzy C Mean clustering to determine the stable segments of a signature generated from windowing segmentation...

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Bibliographic Details
Main Author:	Lee, Beng Yong
Format:	Thesis
Language:	English
Published:	2006
Subjects:	QA76 Computer software
Online Access:	http://ir.unimas.my/id/eprint/1705/8/2013-02-thLeeBYfull.pdf
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id	my-unimas-ir.1705
record_format	uketd_dc
spelling	my-unimas-ir.17052023-03-07T08:20:04Z Fuzzy C mean clustering in off-line handwriting signature verfication system 2006 Lee, Beng Yong QA76 Computer software This research is the first research that suggests the usage of the stable region of a signature for verification purpose. This research highlighted the design and development of the proposed Fuzzy C Mean clustering to determine the stable segments of a signature generated from windowing segmentation process where features could be extracted from signature images. Six features are extracted from each stable segment i.e. Image Size, Ratio of height to width, slant, Maximum horizontal projection, Vertical centre of mass and Horizontal Relative gravity centre/ Horizontal centre of mass. Besides that, this research also demonstrated how to select a best features to represent each determined stable segment. Faculty of Computer Science and Information Technology 2006 Thesis http://ir.unimas.my/id/eprint/1705/ http://ir.unimas.my/id/eprint/1705/8/2013-02-thLeeBYfull.pdf text en validuser masters Universiti Malaysia Sarawak (UNIMAS) Faculty of Computer Science and Information Technology
institution	Universiti Malaysia Sarawak
collection	UNIMAS Institutional Repository
language	English
topic	QA76 Computer software
spellingShingle	QA76 Computer software Lee, Beng Yong Fuzzy C mean clustering in off-line handwriting signature verfication system
description	This research is the first research that suggests the usage of the stable region of a signature for verification purpose. This research highlighted the design and development of the proposed Fuzzy C Mean clustering to determine the stable segments of a signature generated from windowing segmentation process where features could be extracted from signature images. Six features are extracted from each stable segment i.e. Image Size, Ratio of height to width, slant, Maximum horizontal projection, Vertical centre of mass and Horizontal Relative gravity centre/ Horizontal centre of mass. Besides that, this research also demonstrated how to select a best features to represent each determined stable segment.
format	Thesis
qualification_level	Master's degree
author	Lee, Beng Yong
author_facet	Lee, Beng Yong
author_sort	Lee, Beng Yong
title	Fuzzy C mean clustering in off-line handwriting signature verfication system
title_short	Fuzzy C mean clustering in off-line handwriting signature verfication system
title_full	Fuzzy C mean clustering in off-line handwriting signature verfication system
title_fullStr	Fuzzy C mean clustering in off-line handwriting signature verfication system
title_full_unstemmed	Fuzzy C mean clustering in off-line handwriting signature verfication system
title_sort	fuzzy c mean clustering in off-line handwriting signature verfication system
granting_institution	Universiti Malaysia Sarawak (UNIMAS)
granting_department	Faculty of Computer Science and Information Technology
publishDate	2006
url	http://ir.unimas.my/id/eprint/1705/8/2013-02-thLeeBYfull.pdf
_version_	1783727900361490432

Fuzzy C mean clustering in off-line handwriting signature verfication system

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