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Hybrid ACO algorithm for edge detection

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Abstract

Ant colony optimization is a metaheuristic where a colony of artificial ants cooperate to find good solutions to different optimization problems. Edge detection plays an important role in image processing. It consists in detecting edges or contours in images that allow to extract relevant information. Here, an algorithm based on the ACO metaheuristic for edge detection is proposed. Using heuristic and knowledge information in the construction phase and a repair operator in the improvement phase, a binary image containing detected edges is reached. Our proposal was tested with several images in and without presence of noise. Results are competitive in terms of output images, effectiveness and CPU time.

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Correspondence to Cristian A. Martínez.

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Martínez, C.A., Buemi, M.E. Hybrid ACO algorithm for edge detection. Evolving Systems 12, 849–860 (2021). https://doi.org/10.1007/s12530-019-09321-5

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  • DOI: https://doi.org/10.1007/s12530-019-09321-5

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