Paper Info
Title
Fuzzy Image Segmentation Combing Ring and Elliptic Shaped Clustering Algorithms
Abstract
Results from any existing clustering algorithm that are used for segmentation are highly sensitive to features that limit their generalization. Shape is one important attribute of an object. The detection and separation of an object using fuzzy ring-shaped clustering (FKR) and elliptic ring-shaped clustering (FKE) already exists in the literature. Not all real objects however, are ring or elliptical in shape, so to address these issues, this paper introduces a new shape-based algorithm, called fuzzy image segmentation combing ring and elliptic shaped clustering algorithms (FCRE) by merging the initial segmented results produced by FKR and FKE. The distribution of unclassified pixels is performed by connectedness and fuzzy c-means (FCM) using a combination of pixel intensity and normalized pixel location. Both qualitative and quantitative analysis of the results for different varieties of images proves the superiority of the proposed FCRE algorithm compared with both FKR and FKE.
Year
DOI
Venue
2005
10.1109/ITCC.2005.157
ITCC (2)
Keywords
DocType
ISBN
existing clustering algorithm,segmentation combing ring,new shape-based algorithm,fuzzy ring-shaped clustering,elliptic ring-shaped clustering,pixel intensity,normalized pixel location,proposed fcre algorithm,fuzzy c-means,fuzzy image,fuzzy image segmentation,real object,image analysis,algorithm design and analysis,merging,shape,pixel,image segmentation,clustering algorithms,information technology
Conference
0-7695-2315-3
Citations 
PageRank 
References 
3
0.45
7
Authors
3
Name
Order
Citations
PageRank
M. Ameer Ali151.57
Laurence S. Dooley2191.72
Gour C. Karmakar3353.25