Research Article
Image Edge Detection using Modified Ant Colony Optimization Algorithm based on Weighted Heuristics
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 68 - Issue 15 |
| Published: April 2013 |
| Authors: Puneet Rai, Maitreyee Dutta |
10.5120/11653-7158
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Puneet Rai, Maitreyee Dutta . Image Edge Detection using Modified Ant Colony Optimization Algorithm based on Weighted Heuristics. International Journal of Computer Applications. 68, 15 (April 2013), 5-9. DOI=10.5120/11653-7158
@article{ 10.5120/11653-7158,
author = { Puneet Rai,Maitreyee Dutta },
title = { Image Edge Detection using Modified Ant Colony Optimization Algorithm based on Weighted Heuristics },
journal = { International Journal of Computer Applications },
year = { 2013 },
volume = { 68 },
number = { 15 },
pages = { 5-9 },
doi = { 10.5120/11653-7158 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2013
%A Puneet Rai
%A Maitreyee Dutta
%T Image Edge Detection using Modified Ant Colony Optimization Algorithm based on Weighted Heuristics%T
%J International Journal of Computer Applications
%V 68
%N 15
%P 5-9
%R 10.5120/11653-7158
%I Foundation of Computer Science (FCS), NY, USA
Abstract
Ant Colony Optimization (ACO) is nature inspired algorithm based on foraging behavior of ants. The algorithm is based on the fact how ants deposit pheromone while searching for food. ACO generates a pheromone matrix which gives the edge information present at each pixel position of image, formed by ants dispatched on image. The movement of ants depends on local variance of image's intensity value. This paper proposes an improved method based on heuristic which assigns weight to the neighborhood. Experimental results are provided to support the superior performance of the proposed approach.
References
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