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Transactions: WSEAS TRANSACTIONS ON SIGNAL PROCESSING
Transactions ID Number: 89-545
Full Name: Anna Veronica Baterina
Position: Student
Age: ON
Sex: Female
Address: #34 11th Avenue, Murphy, Q. C.
Country: PHILIPPINES
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E-mail address: nbaterina@gmail.com
Other E-mails: nikbat02@yahoo.com
Title of the Paper: Image Edge Detection Using Ant Colony Optimization
Authors as they appear in the Paper: Anna Veronica Baterina, Carlos Oppus
Email addresses of all the authors: nbaterina@gmail.com, coppus@ateneo.edu
Number of paper pages: 10
Abstract: Ant colony optimization (ACO) is a population-based metaheuristic that mimics the foraging behavior of ants to find approximate solutions to difficult optimization problems. It can be used to find good solutions to combinatorial optimization problems that can be transformed into the problem of finding good paths through a weighted construction graph. In this paper, an edge detection technique that is based on ACO is presented. The proposed method establishes a pheromone matrix that represents the edge information at each pixel based on the routes formed by the ants dispatched on the image. The movement of the ants is guided by the local variation in the image's intensity values. The proposed ACO-based edge detection method takes advantage of the improvements introduced in ant colony system, one of the main extensions to the original ant system. Experimental results show the success of the technique in extracting edges from a digital image.
Keywords: Ant colony optimization, Image edge detection, Swarm algorithm
EXTENSION of the file: .pdf
Special (Invited) Session: Ant Colony Optimization for Image Edge Detection
Organizer of the Session: 640-792
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IP ADDRESS: 112.201.17.44
