Outlier rejection fuzzy c-means (ORFCM) algorithm for image segmentation

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Main Authors: Fasahat Ullah, Siddiqui, Nor Ashidi, Mat Isa, Assoc. Prof. Dr., Abid, Yahya, Dr.
Other Authors: ashidi@eng.usm.my
Format: Article
Language:English
Published: Scientific and Technical Research Council of Turkey 2014
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Online Access:http://dspace.unimap.edu.my:80/dspace/handle/123456789/35577
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Institution: Universiti Malaysia Perlis
Language: English
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spelling my.unimap-355772014-06-16T08:29:47Z Outlier rejection fuzzy c-means (ORFCM) algorithm for image segmentation Fasahat Ullah, Siddiqui Nor Ashidi, Mat Isa, Assoc. Prof. Dr. Abid, Yahya, Dr. ashidi@eng.usm.my abid@unimap.edu.my Clustering Fuzzy c-means K-means K-means Outlier Outlier rejection fuzzy c-means Link to publisher's homepage at www.tubitak.gov.tr/en This paper presents a fuzzy clustering-based technique for image segmentation. Many attempts have been put into practice to increase the conventional fuzzy c-means (FCM) performance. In this paper, the sensitivity of the soft membership function of the FCM algorithm to the outlier is considered and the new exponent operator on the Euclidean distance is implemented in the membership function to improve the outlier rejection characteristics of the FCM. The comparative quantitative and qualitative studies are performed among the conventional k-means (KM), moving KM, and FCM algorithms; the latest state-of-the-art clustering algorithms, namely the adaptive fuzzy moving KM , adaptive fuzzy KM, and new weighted FCM algorithms; and the proposed outlier rejection FCM (ORFCM) algorithm. It is revealed from the experimental results that the ORFCM algorithm outperforms the other clustering algorithms in various evaluation functions. 2014-06-16T08:29:47Z 2014-06-16T08:29:47Z 2013 Article Turkish Journal of Electrical Engineering and Computer Sciences, vol. 21(6), 2013, pages 1801-1819 1300-0632 (P) 1303-6203 (O) http://mistug.tubitak.gov.tr/bdyim/toc.php?dergi=elk&yilsayi=2013/6 http://dspace.unimap.edu.my:80/dspace/handle/123456789/35577 en Scientific and Technical Research Council of Turkey
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Clustering
Fuzzy c-means
K-means
K-means
Outlier
Outlier rejection fuzzy c-means
spellingShingle Clustering
Fuzzy c-means
K-means
K-means
Outlier
Outlier rejection fuzzy c-means
Fasahat Ullah, Siddiqui
Nor Ashidi, Mat Isa, Assoc. Prof. Dr.
Abid, Yahya, Dr.
Outlier rejection fuzzy c-means (ORFCM) algorithm for image segmentation
description Link to publisher's homepage at www.tubitak.gov.tr/en
author2 ashidi@eng.usm.my
author_facet ashidi@eng.usm.my
Fasahat Ullah, Siddiqui
Nor Ashidi, Mat Isa, Assoc. Prof. Dr.
Abid, Yahya, Dr.
format Article
author Fasahat Ullah, Siddiqui
Nor Ashidi, Mat Isa, Assoc. Prof. Dr.
Abid, Yahya, Dr.
author_sort Fasahat Ullah, Siddiqui
title Outlier rejection fuzzy c-means (ORFCM) algorithm for image segmentation
title_short Outlier rejection fuzzy c-means (ORFCM) algorithm for image segmentation
title_full Outlier rejection fuzzy c-means (ORFCM) algorithm for image segmentation
title_fullStr Outlier rejection fuzzy c-means (ORFCM) algorithm for image segmentation
title_full_unstemmed Outlier rejection fuzzy c-means (ORFCM) algorithm for image segmentation
title_sort outlier rejection fuzzy c-means (orfcm) algorithm for image segmentation
publisher Scientific and Technical Research Council of Turkey
publishDate 2014
url http://dspace.unimap.edu.my:80/dspace/handle/123456789/35577
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