Efficient colour image segmentation using exponential particle swarm optimization

Authors:
K. M. Murugesan;S. Palaniswami
Affiliations:
Department of Electrical and Electronics Engineering, Anna University, Coimbatore, Tamil Nadu, India;Department of Electrical and Electronics Engineering, Anna University, Coimbatore, Tamil Nadu, India
Venue:
ICNVS'10 Proceedings of the 12th international conference on Networking, VLSI and signal processing
Year:
2010

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Abstract

Image colour classification and Image segmentation using comprehensive learning particle swarm optimization (CLPSO) technique was developed by Parag Puranik, Dr. P.R. Baja, Prof. P.M. Palsodkar [1], the aim was to produce a fuzzy system for colour classification and image segmentation with least number of rules and minimum error rate. In this paper we propose exponential particle swarm optimization (EPSO). EPSO has a great impact on global and local exploration it is supposed to bring out the search behaviour quickly and intelligently as it avoid the particles from stagnation of local optima by varying inertia weight exponentially, so that the movement of the particles will be faster and distant from each other. The EPSO is used to find optimal fuzzy rules and membership functions. The best fuzzy rule is selected for image segmentation.EPSO give best rule set than standard PSO.