The week's pick
Random Articles
Reseach Article
The Artificial Bee Colony Algorithm for Unsupervised Classification of Meteorological Satellite Images
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 112 - Number 12 |
| Year of Publication: 2015 |
| Authors: Rafik Deriche, Hadria Fizazi |
10.5120/19720-0825
|
Rafik Deriche, Hadria Fizazi . The Artificial Bee Colony Algorithm for Unsupervised Classification of Meteorological Satellite Images. International Journal of Computer Applications. 112, 12 ( February 2015), 28-32. DOI=10.5120/19720-0825
Abstract
The processing of satellite images plays an important role. It uses different attributes of images, and multiple mathematical and physical tools. Among the techniques of image processing, there exists the unsupervised classification which is based on the combination of image pixels into categories or themes. The classification algorithm designed and implemented in this article says Artificial Bee Colony (ABC) is one of bio inspired algorithms, it is very simple and very flexible compared to existing algorithms bio-inspired, and it has the advantage of rapid convergence and reduced memory size. We will apply the ABC algorithm to achieve an unsupervised classification of the meteorological satellite images of the Météosat-9 satellite.
References
- S. Banerjee, A. Bharadwaj, D. Gupta, and V. K. Panchal, Remote Sensing Image Classification Using Artificial Bee Colony Algorithm, international journal of computer science and informatics, volume 2, issue 3, 2012.
- K. V. Frisch, Bees: Their Vision, Chemical Senses And Language, Cornell University Press, Ithaca, NY, pp. 157, 1971.
- T. D. Seeley, The Wisdom of the Hive: The Social Physiology of Honey Bee Colonies, Harvard University Press, Cambridge, 1996.
- E. Bonabeau, M. Dorigo, and G. Theraulaz, Swarm Intelligence from Nature to Artificial System, First Edition, Oxford University Press, USA, pp. 1-24, 1999.
- D. Karaboga, An Idea Based On Honey Bee Swarm for Numerical Optimization, Technical Report-TR06, Erciyes University, Engineering Faculty, Computer Engineering Department 2005.
- D. T. Pham, A. Ghanbarzadeh, E. Koc, S. Otri, S. Rahim, and M. Zaidi, The bees algorithm-a novel tool for complex optimization problems, Proceedings of the 2nd Virtual International Conference on Intelligent production machines and systems (IPROMS 2006), Elsevier, Oxford, pp. 454-459, 2006.
- X. L. Xie, G. Beni, A validity measure for fuzzy clustering, IEEE Trans, Pattern Anal, Mach, Intell, vol. 13, no. 8, pp. 841-847, 1991.
Index Terms
Keywords