Edge Detection of an Image Based on Ant Colony Optimization Technique
Abstract: ACO is introduced to think about the image edge detection issues where the purpose is to evolve the edge information existing in the picture, since it is critical to understand the images content. The main mechanism of ACO is the discovery of good tours is the positive feedback done through the pheromone update by the ants. Ant colony optimization is inspired by food foraging behaviour exhibited by ant societies to find approximate solutions to the tough issues. An ACO algorithm is the combination of prior information regarding the structure of a solution with the information regarding the structure of previously obtained good solutions. Experimental results show the success of the technique in extracting edges from a digital image.
Keywords: Ant colony optimization, Feature extraction, Image Edge detection, Mean square error, Peak signal to noise ratio
How to Cite?: Charu Gupta, Sunanda Gupta, "Edge Detection of an Image Based on Ant Colony Optimization Technique", Volume 2 Issue 6, June 2013, International Journal of Science and Research (IJSR), Pages: 114-120, https://www.ijsr.net/getabstract.php?paperid=IJSROFF2013253, DOI: https://dx.doi.org/10.21275/IJSROFF2013253