Combined nearest mean classifiers for multiple feature classification

Pattern classification is an important stage in many image processing applications. This paper proposes a technique that is based on nearest mean classifier for classification.The proposed technique integrates three classifiers and uses colour and shape features. Experiment on small training samples...

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Main Authors:	Abdullah,, Ku-Mahamud, Ku Ruhana
Format:	Conference or Workshop Item
Language:	English
Published:	2011
Subjects:	QA76 Computer software
Online Access:	http://repo.uum.edu.my/3999/1/Ab.pdf http://repo.uum.edu.my/3999/ http://www.icoci.cms.net.my
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Institution:	Universiti Utara Malaysia
Language:	English

id	my.uum.repo.3999
record_format	eprints
spelling	my.uum.repo.39992015-04-07T03:26:45Z http://repo.uum.edu.my/3999/ Combined nearest mean classifiers for multiple feature classification Abdullah, , Ku-Mahamud, Ku Ruhana QA76 Computer software Pattern classification is an important stage in many image processing applications. This paper proposes a technique that is based on nearest mean classifier for classification.The proposed technique integrates three classifiers and uses colour and shape features. Experiment on small training samples has been conducted to evaluate the performance of the proposed combined nearest mean classiffiers and results obtained showed that the technique was able to provide good accuracy 2011-06-08 Conference or Workshop Item PeerReviewed application/pdf en http://repo.uum.edu.my/3999/1/Ab.pdf Abdullah, , and Ku-Mahamud, Ku Ruhana (2011) Combined nearest mean classifiers for multiple feature classification. In: 3rd International Conference on Computing and Informatics (ICOCI 2011), 8-9 June 2011 , Bandung, Indonesia. http://www.icoci.cms.net.my
institution	Universiti Utara Malaysia
building	UUM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Utara Malaysia
content_source	UUM Institutionali Repository
url_provider	http://repo.uum.edu.my/
language	English
topic	QA76 Computer software
spellingShingle	QA76 Computer software Abdullah, , Ku-Mahamud, Ku Ruhana Combined nearest mean classifiers for multiple feature classification
description	Pattern classification is an important stage in many image processing applications. This paper proposes a technique that is based on nearest mean classifier for classification.The proposed technique integrates three classifiers and uses colour and shape features. Experiment on small training samples has been conducted to evaluate the performance of the proposed combined nearest mean classiffiers and results obtained showed that the technique was able to provide good accuracy
format	Conference or Workshop Item
author	Abdullah, , Ku-Mahamud, Ku Ruhana
author_facet	Abdullah, , Ku-Mahamud, Ku Ruhana
author_sort	Abdullah, ,
title	Combined nearest mean classifiers for multiple feature classification
title_short	Combined nearest mean classifiers for multiple feature classification
title_full	Combined nearest mean classifiers for multiple feature classification
title_fullStr	Combined nearest mean classifiers for multiple feature classification
title_full_unstemmed	Combined nearest mean classifiers for multiple feature classification
title_sort	combined nearest mean classifiers for multiple feature classification
publishDate	2011
url	http://repo.uum.edu.my/3999/1/Ab.pdf http://repo.uum.edu.my/3999/ http://www.icoci.cms.net.my
_version_	1644278647254679552

Combined nearest mean classifiers for multiple feature classification

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