DocumentCode :
2734453
Title :
A modified ant colony optimization based approach for image edge detection
Author :
Rajeswari, R. ; Rajesh, R.
Author_Institution :
Dept. of Comput. Applic., Bharathiar Univ., Coimbatore, India
fYear :
2011
fDate :
3-5 Nov. 2011
Firstpage :
1
Lastpage :
6
Abstract :
Ant Colony Optimization (ACO) is used to detect edges in digital images. Such techniques generate a pheromone matrix that represents the edge information at each pixel position on the routes formed by ants dispatched on the image. In this paper a modified ACO-based edge detection is proposed. Ants try to find possible edges by using a heuristic information based on the degree of edginess of each pixel. The proposed ACO-based approach also takes advantage of the fuzzy clustering to determine whether a pixel is edge or not. Experimental results demonstrate superior performance of the proposed approach.
Keywords :
edge detection; fuzzy set theory; image representation; optimisation; pattern clustering; digital images; edge information representation; fuzzy clustering; heuristic information; image edge detection; modified ACO-based edge detection; modified ant colony optimization; pheromone matrix; pixel position; Ant colony optimization; Cameras; Clustering algorithms; Data mining; Digital images; Image edge detection; Presses; aco-based algorithm; edge based heuristic information; edge detection; fuzzy clustering;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Information Processing (ICIIP), 2011 International Conference on
Conference_Location :
Himachal Pradesh
Print_ISBN :
978-1-61284-859-4
Type :
conf
DOI :
10.1109/ICIIP.2011.6108930
Filename :
6108930
Link To Document :
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