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