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
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;
Conference_Titel :
Computer Graphics, Imaging and Visualisation, 2008. CGIV '08. Fifth International Conference on
Conference_Location :
Penang
Print_ISBN :
978-0-7695-3359-9
DOI :
10.1109/CGIV.2008.54
