New ACO algorithm for image edge detection
New ACO algorithm for image edge detection
- Author(s): C.A. Martınez and M.E. Buemi
- DOI: 10.1049/14.2014.0003
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- Author(s): C.A. Martınez and M.E. Buemi Source: 6th Chilean Conference on Pattern Recognition (CCPR), 2014 page ()
- Conference: 6th Chilean Conference on Pattern Recognition (CCPR)
- DOI: 10.1049/14.2014.0003
- ISBN: 978-1-78561-081-3
- Location: Talca, Chile
- Conference date: 10-14 Nov. 2014
- Format: PDF
Ant Colony Optimization (ACO) is a metaheuristic based on real behavior of ants to solve optimization problems. Edge detection plays an important role in image processing. It consists in detecting edges or contours in images which allows to extract information from them. An ACO algorithm to edge detection is proposed. Using heuristic and knowledge information and applying an improvement operator, binary images including edges detected are obtained. The algorithm was tested with several images (real and synthetic, with and without presence of noise). The results reached were competitive in terms of quality of images and required computational time.
Inspec keywords: ant colony optimisation; feature extraction; edge detection
Subjects: Computer vision and image processing techniques; Optimisation techniques; Optimisation techniques; Optical, image and video signal processing
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