Generalised kernel weighted fuzzy C-means clustering algorithm with local information

To improve the performance of segmentation for the images corrupted by noise, many variants of standard fuzzy C-means (FCM) clustering algorithm have been proposed that incorporate the local spatial neighbourhood information to perform image segmentation. Among them, the kernel weighted fuzzy local...

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Veröffentlicht in:	Fuzzy sets and systems Jg. 340; S. 91 - 108
Hauptverfasser:	Memon, Kashif Hussain, Lee, Dong-Ho
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.06.2018
Schlagworte:	Enhanced clustering performance Kernel fuzzy c-means Local similarity Neighbourhood for higher dimensional input data Robustness to noise and outliers Local similarity Neighbourhood for higher dimensional input data Robustness to noise and outliers Kernel fuzzy c-means Enhanced clustering performance
ISSN:	0165-0114, 1872-6801
Online-Zugang:	Volltext
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