A Hybrid Rough K-Means Algorithm and Particle Swarm Optimization for Image Classification

Authors:
Chih-Cheng Hung;Hendri Purnawan
Affiliations:
Southern Polytechnic State University, Marietta, USA GA 30060-2896;Southern Polytechnic State University, Marietta, USA GA 30060-2896
Venue:
MICAI '08 Proceedings of the 7th Mexican International Conference on Artificial Intelligence: Advances in Artificial Intelligence
Year:
2008

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Abstract

This paper proposes a hybrid rough K-means algorithm for image classification. The rough set theory is used to establish the lower and upper bound for data clustering in the K-means algorithm. Then, the particle swarm optimization (PSO) is employed to optimize the solutions of the rough K-means algorithm. The combined algorithm is called the Rough K-means PSO algorithm. Experimental results show that the proposed algorithm performs better and improves the classification in the blurred and vague areas of test images.