Initialization Methods For Conventional Fuzzy C-Means And Its Application Towards Colour Image Segmentation

Due to its capability in providing a particularly promising solution to clustering problems, the conventional Fuzzy C-Mean (FCM) algorithm is widely used as a segmentation method. However, it is very sensitive to the initialization conditions of number of clusters and initial cluster centres. Thus,...

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Main Author:	Tan , Khang Siang
Format:	Thesis
Language:	English
Published:	2011
Subjects:	TK1-9971 Electrical engineering Electronics Nuclear engineering
Online Access:	http://eprints.usm.my/42775/1/TAN_KHANG_SIANG.pdf
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id	my-usm-ep.42775
record_format	uketd_dc
spelling	my-usm-ep.427752019-04-12T05:26:37Z Initialization Methods For Conventional Fuzzy C-Means And Its Application Towards Colour Image Segmentation 2011-05 Tan , Khang Siang TK1-9971 Electrical engineering. Electronics. Nuclear engineering Due to its capability in providing a particularly promising solution to clustering problems, the conventional Fuzzy C-Mean (FCM) algorithm is widely used as a segmentation method. However, it is very sensitive to the initialization conditions of number of clusters and initial cluster centres. Thus, three initialization schemes for the conventional FCM algorithm namely the Hierarchical Approach (HA), the Colour Quantization (CQ) and the Histogram Thresholding (HT) are proposed to automatically obtain the initialization conditions for the conventional FCM algorithm. 2011-05 Thesis http://eprints.usm.my/42775/ http://eprints.usm.my/42775/1/TAN_KHANG_SIANG.pdf application/pdf en public masters Universiti Sains Malaysia Pusat Pengajian Kejuteraan Elektrik & Elektronik
institution	Universiti Sains Malaysia
collection	USM Institutional Repository
language	English
topic	TK1-9971 Electrical engineering Electronics Nuclear engineering
spellingShingle	TK1-9971 Electrical engineering Electronics Nuclear engineering Tan , Khang Siang Initialization Methods For Conventional Fuzzy C-Means And Its Application Towards Colour Image Segmentation
description	Due to its capability in providing a particularly promising solution to clustering problems, the conventional Fuzzy C-Mean (FCM) algorithm is widely used as a segmentation method. However, it is very sensitive to the initialization conditions of number of clusters and initial cluster centres. Thus, three initialization schemes for the conventional FCM algorithm namely the Hierarchical Approach (HA), the Colour Quantization (CQ) and the Histogram Thresholding (HT) are proposed to automatically obtain the initialization conditions for the conventional FCM algorithm.
format	Thesis
qualification_level	Master's degree
author	Tan , Khang Siang
author_facet	Tan , Khang Siang
author_sort	Tan , Khang Siang
title	Initialization Methods For Conventional Fuzzy C-Means And Its Application Towards Colour Image Segmentation
title_short	Initialization Methods For Conventional Fuzzy C-Means And Its Application Towards Colour Image Segmentation
title_full	Initialization Methods For Conventional Fuzzy C-Means And Its Application Towards Colour Image Segmentation
title_fullStr	Initialization Methods For Conventional Fuzzy C-Means And Its Application Towards Colour Image Segmentation
title_full_unstemmed	Initialization Methods For Conventional Fuzzy C-Means And Its Application Towards Colour Image Segmentation
title_sort	initialization methods for conventional fuzzy c-means and its application towards colour image segmentation
granting_institution	Universiti Sains Malaysia
granting_department	Pusat Pengajian Kejuteraan Elektrik & Elektronik
publishDate	2011
url	http://eprints.usm.my/42775/1/TAN_KHANG_SIANG.pdf
_version_	1747821100217139200

Initialization Methods For Conventional Fuzzy C-Means And Its Application Towards Colour Image Segmentation

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