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http://dx.doi.org/10.3745/KIPSTB.2006.13B.3.315

Improved Edge Detection Algorithm Using Ant Colony System  

Kim In-Kyeom (성결대학교 정보통신공학부)
Yun Min-Young (성결대학교 정보통신공학부)
Publication Information
The KIPS Transactions:PartB / v.13B, no.3, 2006 , pp. 315-322 More about this Journal
Abstract
Ant Colony System(ACS) is easily applicable to the traveling salesman problem(TSP) and it has demonstrated good performance on TSP. Recently, ACS has been emerged as the useful tool for the pattern recognition, feature extraction, and edge detection. The edge detection is wifely utilized in the area of document analysis, character recognition, and face recognition. However, the conventional operator-based edge detection approaches require additional postprocessing steps for the application. In the present study, in order to overcome this shortcoming, we have proposed the new ACS-based edge detection algorithm. The experimental results indicate that this proposed algorithm has the excellent performance in terms of robustness and flexibility.
Keywords
Ant Colony System; Image Processing; Edge Detection;
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Times Cited By KSCI : 1  (Citation Analysis)
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