Image clustering comparison of two color segmentation techniques

The clustering research is regarding the area of data mining and implementation of the clustering algorithms. The image clustering is major part of data mining where study about how to binds the similar data together in a cluster and show the meaningful data. There are many algorithm for analysing c...

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Main Author:	Subramaniam, Kavitha Pichaiyan
Format:	Thesis
Language:	English English
Published:	2010
Subjects:	T Technology (General)
Online Access:	http://eprints.utem.edu.my/id/eprint/12808/1/Image_clustering_comparison_of_two_color_segmentation_techniques24_pages.pdf http://eprints.utem.edu.my/id/eprint/12808/3/Image%20clustering%20comparison%20of%20two%20color%20segmentation%20techniques.pdf
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id	my-utem-ep.12808
record_format	uketd_dc
spelling	my-utem-ep.128082022-11-11T08:47:12Z Image clustering comparison of two color segmentation techniques 2010 Subramaniam, Kavitha Pichaiyan T Technology (General) TA Engineering (General). Civil engineering (General) The clustering research is regarding the area of data mining and implementation of the clustering algorithms. The image clustering is major part of data mining where study about how to binds the similar data together in a cluster and show the meaningful data. There are many algorithm for analysing clustering each having its own method to do clustering. This clustering technique increasingly common and has yield many insights into segmentation factors, would effect image functioning and performance. The enormous researches going on extract image with background subtraction. We focus on the outlier detection and background subtraction on image. This project proposed a two color segmentation techniques such as K-means and Fuzzy C-means clustering algorithm that are accurately segment the desired images, which have the same color as the pre-selected pixels with background subtraction. In the software development testing we examine image based clustering, as we can used clustering by distance base, by pixel (red, green, blue) value etc., The problem is solved by region based method which is based on connect component and background detection techniques. The appropriate Java codes are developed for solve this task. The developed patterns are applied in the field of real-time analysis. Finally, the algorithm found, which would solve the image segmentation problem. 2010 Thesis http://eprints.utem.edu.my/id/eprint/12808/ http://eprints.utem.edu.my/id/eprint/12808/1/Image_clustering_comparison_of_two_color_segmentation_techniques24_pages.pdf text en public http://eprints.utem.edu.my/id/eprint/12808/3/Image%20clustering%20comparison%20of%20two%20color%20segmentation%20techniques.pdf text en validuser https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=63009 mphil masters Universiti Teknikal Malaysia Melaka Faculty of Information and Communication Technology Herman, Nanna Suryana
institution	Universiti Teknikal Malaysia Melaka
collection	UTeM Repository
language	English English
advisor	Herman, Nanna Suryana
topic	T Technology (General) T Technology (General)
spellingShingle	T Technology (General) T Technology (General) Subramaniam, Kavitha Pichaiyan Image clustering comparison of two color segmentation techniques
description	The clustering research is regarding the area of data mining and implementation of the clustering algorithms. The image clustering is major part of data mining where study about how to binds the similar data together in a cluster and show the meaningful data. There are many algorithm for analysing clustering each having its own method to do clustering. This clustering technique increasingly common and has yield many insights into segmentation factors, would effect image functioning and performance. The enormous researches going on extract image with background subtraction. We focus on the outlier detection and background subtraction on image. This project proposed a two color segmentation techniques such as K-means and Fuzzy C-means clustering algorithm that are accurately segment the desired images, which have the same color as the pre-selected pixels with background subtraction. In the software development testing we examine image based clustering, as we can used clustering by distance base, by pixel (red, green, blue) value etc., The problem is solved by region based method which is based on connect component and background detection techniques. The appropriate Java codes are developed for solve this task. The developed patterns are applied in the field of real-time analysis. Finally, the algorithm found, which would solve the image segmentation problem.
format	Thesis
qualification_name	Master of Philosophy (M.Phil.)
qualification_level	Master's degree
author	Subramaniam, Kavitha Pichaiyan
author_facet	Subramaniam, Kavitha Pichaiyan
author_sort	Subramaniam, Kavitha Pichaiyan
title	Image clustering comparison of two color segmentation techniques
title_short	Image clustering comparison of two color segmentation techniques
title_full	Image clustering comparison of two color segmentation techniques
title_fullStr	Image clustering comparison of two color segmentation techniques
title_full_unstemmed	Image clustering comparison of two color segmentation techniques
title_sort	image clustering comparison of two color segmentation techniques
granting_institution	Universiti Teknikal Malaysia Melaka
granting_department	Faculty of Information and Communication Technology
publishDate	2010
url	http://eprints.utem.edu.my/id/eprint/12808/1/Image_clustering_comparison_of_two_color_segmentation_techniques24_pages.pdf http://eprints.utem.edu.my/id/eprint/12808/3/Image%20clustering%20comparison%20of%20two%20color%20segmentation%20techniques.pdf
_version_	1776103066179731456

Image clustering comparison of two color segmentation techniques

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