A Classification Algorithm Using Ant Colony System 


Vol. 15,  No. 3, pp. 245-252, Jun.  2008
10.3745/KIPSTB.2008.15.3.245


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  Abstract

We present a classification algorithm based on ant colony system(ACS) for classifying digital images. The ACS has been recently emerged as a useful tool for the pattern recognition, image extraction, and edge detection. The classification algorithm of digital images is very important in the application areas of digital image coding, image analysis, and image recognition because it significantly influences the quality of images. The conventional procedures usually classify digital images with the fixed value for the associated parameters and it requires postprocessing. However, the proposed algorithm utilizing randomness of ants yields the stable and enhanced images even for processing the rapidly changing images. It is also expected that, due to this stability and flexibility of the present procedure, the digital images are stably classified for processing images with various noises and error signals arising from processing of the drastically fast moving images could be automatically compensated and minimized.

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[IEEE Style]

I. K. Kim and M. Y. Yun, "A Classification Algorithm Using Ant Colony System," The KIPS Transactions:PartB , vol. 15, no. 3, pp. 245-252, 2008. DOI: 10.3745/KIPSTB.2008.15.3.245.

[ACM Style]

In Kyeom Kim and Min Young Yun. 2008. A Classification Algorithm Using Ant Colony System. The KIPS Transactions:PartB , 15, 3, (2008), 245-252. DOI: 10.3745/KIPSTB.2008.15.3.245.

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