Segmentation d’images par FCM modifié considérant le contexte spatiale.

Please use this identifier to cite or link to this item: https://dspace.univ-ouargla.dz/jspui/handle/123456789/3377

Full metadata record

DC Field	Value	Language
dc.contributor.author	N.NASRI , K.MOKRANI	-
dc.date.accessioned	2013-12-22T09:56:46Z	-
dc.date.available	2013-12-22T09:56:46Z	-
dc.date.issued	2013-12-22	-
dc.identifier.issn	waf	-
dc.identifier.uri	http://hdl.handle.net/123456789/3377	-
dc.description	The INTERNATIONAL CONFERENCE ON ELECTRONICS & OIL: FROM THEORY TO APPLICATIONS March 05-06, 2013, Ouargla, Algeria	en_US
dc.description.abstract	In this work, we are interested by FCM [1] (fuzzy C- means) algorithm, one of the most popular clustering methods based on minimization of a criterion. However,the performance of this algorithm may significantly degrade in the presence of noise and intensity inhomogeneities. The use of algorithms which incorporate spatial information in their objective functions could improve the quality of segmentation. Solutions such as FCM_S [3] (FCM with Spatial constraints) can be used. Test on synthetic and IRM images show that these algorithms succeed to minimize the effect of noise and intensity inhomogeneities.	en_US
dc.language.iso	fr	en_US
dc.subject	Segmentation d’images	en_US
dc.subject	FCM	en_US
dc.subject	le contexte spatiale	en_US
dc.title	Segmentation d’images par FCM modifié considérant le contexte spatiale.	en_US
dc.type	Article	en_US
Appears in Collections:	3. Faculté des sciences appliquées

Files in This Item:

File	Description	Size	Format
N_NASRI.pdf		580,99 kB	Adobe PDF	View/Open

DSpace JSPUI