Short Communication: Image segmentation using PSO and PCM with Mahalanobis distance

Authors:
Yong Zhang;Dan Huang;Min Ji;Fuding Xie
Affiliations:
College of Computer and Information Technology, Liaoning Normal University, Dalian 116081, China and College of Computer Science and Technology, Dalian University of Technology, Dalian 116024, Chi ...;College of Computer and Information Technology, Liaoning Normal University, Dalian 116081, China;College of Computer and Information Technology, Liaoning Normal University, Dalian 116081, China;College of Urban and Environmental Sciences, Liaoning Normal University, Dalian 116029, China
Venue:
Expert Systems with Applications: An International Journal
Year:
2011

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Abstract

Fuzzy clustering algorithm is widely used in image segmentation. Possibilistic c-means algorithm overcomes the relative membership problem of fuzzy c-means algorithm, and has been shown to have satisfied the ability of handling noises and outliers. This paper replaces Euclidean distance with Mahalanobis distance in the possibilistic c-means clustering algorithm, and optimizes the initial clustering centers using particle swarm optimization method. Experimental results show that the proposed algorithm has a significant improvement on the effect and efficiency of segmentation comparing with the standard FCM clustering algorithm.