Information Technology: Coding and Computing, International Conference on (2005)
Las Vegas, Nevada
Apr. 4, 2005 to Apr. 6, 2005
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ITCC.2005.157
M. Ameer Ali , Monash University, Australia
Laurence S. Dooley , Monash University, Australia
Gour C. Karmakar , Monash University, Australia
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.
M. A. Ali, L. S. Dooley and G. C. Karmakar, "Fuzzy Image Segmentation Combing Ring and Elliptic Shaped Clustering Algorithms," Information Technology: Coding and Computing, International Conference on(ITCC), Las Vegas, Nevada, 2005, pp. 118-122.