Universiti Teknologi Malaysia Institutional Repository

Hybrid image segmentation using fuzzy c-means and gravitational search algorithm

Mozafari Majd, Emadaldin and As'ari, Muhammad Amir and Ullah Sheikh, Usman and Syed Abu Bakar, Syed Abdul Rahman (2012) Hybrid image segmentation using fuzzy c-means and gravitational search algorithm. In: 4th International Conference on Digital Image Processing, ICDIP 2012. SPIE, Bellingham, USA, pp. 1-5. ISBN 978-081948991-3

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Official URL: http://dx.doi.org/10.1117/12.956460

Abstract

In this paper, we propose a new hybrid approach for image segmentation. The proposed approach exploits spatial fuzzy c-means for clustering image pixels into homogeneous regions. In order to improve the performance of fuzzy c-means to cope with segmentation problems, we employ gravitational search algorithm which is inspired by Newton's rule of gravity. Gravitational search algorithm is incorporated into fuzzy c-means to take advantage of its ability to find optimum cluster centers which minimizes the fitness function of fuzzy c-means. Experimental results show effectiveness of the proposed method in segmentation different types of images as compared to classical fuzzy c-means.

Item Type:Book Section
Additional Information:Indexed by Scopus
Uncontrolled Keywords:cluster centers, fitness functions, fuzzy c mean, gravitational search algorithms, homogeneous regions, hybrid approach, hybrid image segmentations, image pixels
Subjects:Q Science
Divisions:Biosciences and Medical Engineering
ID Code:35802
Deposited By:INVALID USER
Deposited On:04 Dec 2013 09:16
Last Modified:02 Feb 2017 14:01

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