Unsupervised Clustering of Images Using Harmony Search Algorithm

Bekoouche Ibtissem^1, and Fizazi Hadria¹

¹Department of Computer Science Laboratory SIMPA,University of Science and Technology of Oran-Mohamed Boudiaf- Faculty of Sciences Oran, Algeria

Cite this paper:
Bekoouche Ibtissem and Fizazi Hadria. Unsupervised Clustering of Images Using Harmony Search Algorithm. Journal of Computer Sciences and Applications. 2013; 1(5):91-99. doi: 10.12691/jcsa-1-5-3

Abstract

Clustering plays an important role in the image processing. It permits to assign a label to each point of the image from a collection of defined classes. Among the domains that use the clustering, we can mention the Remote Sensing for identification of different regions constituting a satellite image. Evaluation of the clustering algorithm results is based on the validity index. In this paper, we applied the Harmony Search algorithm (HS) for make an unsupervised clustering. Thereafter, we evaluated the performance of this tool by analyzing the results obtained. These results show that the validity index determines automatically the appropriate number of classes that represent an image. The study realized with several validity indices allowed us to find the best validity index to evaluate the performance and robustness of the algorithm HS. The experiences obtained with this algorithm show the effectiveness and performance in the stable clustering for given problem.

Keywords:
harmony search processing of image unsupervised clustering validity index

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