Images information retrieval using Gustafson-Kessel relevance feedback

The goal of CBIR is to retrieve images that are visually similar to the query image. Relevance feedback retrieval systems ask the user for feedback on retrieval results and then use this feedback on later retrievals with the goal of increasing retrieval performance. The objectives of this research a...

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Bibliographic Details
Main Author:	Zainuddin, Nurulhuda
Format:	Thesis
Language:	English
Published:	2006
Subjects:	QA75 Electronic computers Computer science
Online Access:	http://eprints.utm.my/id/eprint/5383/1/NurulhudaZainuddinMFSKSM2006.pdf
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id	my-utm-ep.5383
record_format	uketd_dc
spelling	my-utm-ep.53832018-03-07T20:59:28Z Images information retrieval using Gustafson-Kessel relevance feedback 2006-06 Zainuddin, Nurulhuda QA75 Electronic computers. Computer science The goal of CBIR is to retrieve images that are visually similar to the query image. Relevance feedback retrieval systems ask the user for feedback on retrieval results and then use this feedback on later retrievals with the goal of increasing retrieval performance. The objectives of this research are to compare CBIR based with Gustafson-Kessel (GK) clustering and relevant feedback approach and to evaluate the effectiveness of GK relevance feedback for images retrieval. The research requires a better understanding of GK clustering and probabilistic relevance feedback method in turn to figure out different methods that can be used in solving similar problems. This project will give better insights in the usage of relevance feedback learning in order to reduce the gap between low-level features and high-level human concepts. The research will evaluate Gustafson-Kessel clustering and probabilistic relevance feedback method to improve the retrieval performance. 2006-06 Thesis http://eprints.utm.my/id/eprint/5383/ http://eprints.utm.my/id/eprint/5383/1/NurulhudaZainuddinMFSKSM2006.pdf application/pdf en public masters Universiti Teknologi Malaysia, Faculty of Computer Science and Information System Faculty of Computer Science and Information System
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	QA75 Electronic computers Computer science
spellingShingle	QA75 Electronic computers Computer science Zainuddin, Nurulhuda Images information retrieval using Gustafson-Kessel relevance feedback
description	The goal of CBIR is to retrieve images that are visually similar to the query image. Relevance feedback retrieval systems ask the user for feedback on retrieval results and then use this feedback on later retrievals with the goal of increasing retrieval performance. The objectives of this research are to compare CBIR based with Gustafson-Kessel (GK) clustering and relevant feedback approach and to evaluate the effectiveness of GK relevance feedback for images retrieval. The research requires a better understanding of GK clustering and probabilistic relevance feedback method in turn to figure out different methods that can be used in solving similar problems. This project will give better insights in the usage of relevance feedback learning in order to reduce the gap between low-level features and high-level human concepts. The research will evaluate Gustafson-Kessel clustering and probabilistic relevance feedback method to improve the retrieval performance.
format	Thesis
qualification_level	Master's degree
author	Zainuddin, Nurulhuda
author_facet	Zainuddin, Nurulhuda
author_sort	Zainuddin, Nurulhuda
title	Images information retrieval using Gustafson-Kessel relevance feedback
title_short	Images information retrieval using Gustafson-Kessel relevance feedback
title_full	Images information retrieval using Gustafson-Kessel relevance feedback
title_fullStr	Images information retrieval using Gustafson-Kessel relevance feedback
title_full_unstemmed	Images information retrieval using Gustafson-Kessel relevance feedback
title_sort	images information retrieval using gustafson-kessel relevance feedback
granting_institution	Universiti Teknologi Malaysia, Faculty of Computer Science and Information System
granting_department	Faculty of Computer Science and Information System
publishDate	2006
url	http://eprints.utm.my/id/eprint/5383/1/NurulhudaZainuddinMFSKSM2006.pdf
_version_	1747814588364095488

Images information retrieval using Gustafson-Kessel relevance feedback

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