Image segmentation with cyclic load balanced parallel Fuzzy C - Means cluster analysis

Author

Vadiveloo, Mogana ; Abdullah, Rosni ; Rajeswari, Mandava ; Abu-Shareha, Ahmad Adel

Author_Institution

Sch. of Comput. Sci., Univ. Sains Malaysia, Minden, Malaysia

fYear

2011

fDate

17-18 May 2011

Firstpage

124

Lastpage

129

Abstract

This paper proposes a cyclic load balancing strategy to parallel Fuzzy C-Means cluster analysis algorithm. The problem is to minimize the total time cost and maximize the parallel processing efficiency when a subset of clusters is distributed over a set of processors cores on shared memory architecture. The parallel Fuzzy C - Means (FCM) cluster analysis algorithm is composed by two distinct parts. The two distinct parts are; first: the cluster analysis whereby using the FCM algorithm to calculate the cluster centers and second: the evaluation of the subset of clusters whereby using the cluster validity functions to produce the result of the optimal cluster. The experimental result shows that the cyclic load balanced parallel FCM cluster analysis algorithm presents good speed up especially when the size of clusters is large as compared to the parallel FCM cluster analysis algorithm.

Keywords

fuzzy set theory; image segmentation; pattern clustering; resource allocation; cyclic load balancing strategy; image segmentation; parallel fuzzy c-means cluster analysis algorithm; Algorithm design and analysis; Clustering algorithms; Gray-scale; Image segmentation; Instruction sets; Load management; Pixel; Clustering; Load Balancing; Parallel Fuzzy C - Means Cluster Analysis; Shared Memory Architecture;

fLanguage

English

Publisher

ieee

Conference_Titel

Imaging Systems and Techniques (IST), 2011 IEEE International Conference on

Conference_Location

Penang

Print_ISBN

978-1-61284-894-5

Type

conf

DOI

10.1109/IST.2011.5962212

Filename

5962212