DocumentCode
2854328
Title
Improved Canny Edges Using Ant Colony Optimization
Author
Wong, Ya-Ping ; Soh, V.C.-M. ; Ban, Kar-Weng ; Bau, Yoon-Teck
Author_Institution
Fac. of Inf. Technol., Multimedia Univ., Cyberjaya
fYear
2008
fDate
26-28 Aug. 2008
Firstpage
197
Lastpage
202
Abstract
Ant colony optimization (ACO) is a metaheuristic approach for solving hard optimization problem. It has been applied to solve various image processing problems such as image segmentation, classification, image analysis and edge detection. In this paper, we present an Improved Canny edges (ICE-ACO) algorithm which uses ACO to solve the problem of linking disjointed edges produced by Canny edge detector.
Keywords
edge detection; optimisation; Canny edge detector; Canny edges; ant colony optimization; edge detection; hard optimization problem; image analysis; image classification; image processing problems; image segmentation; Algorithm design and analysis; Ant colony optimization; Cities and towns; Computer graphics; Detectors; Image edge detection; Image processing; Image segmentation; Joining processes; Visualization; Ant Colony Optimization (ACO); Canny Edge Detector; Edge Linking; Swarm Intelligence;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Graphics, Imaging and Visualisation, 2008. CGIV '08. Fifth International Conference on
Conference_Location
Penang
Print_ISBN
978-0-7695-3359-9
Type
conf
DOI
10.1109/CGIV.2008.54
Filename
4627007
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