Artificial Bee Colony (ABC) algorithm and its use in digital image processing

Authors

  • Erik Cuevas

DOI:

https://doi.org/10.4114/intartif.vol18iss55pp50-68

Abstract

Classical methods often face great difficulties in solving image processing problems in images containing noise and distortions. Under such conditions, the use of bio-inspired optimization approaches has been extended. This paper explores the use of the Artificial Bee Colony (ABC) algorithm for digital image processing seen as an optimization problem. ABC is a heuristic algorithm motivated by the biological behaviour of honey-bees which has been successfully employed to solve complex optimization problems. In this paper, image segmentation and circle detection tasks are considered as examples, both issues approached as optimization problems. In segmentation, an image 1-D histogram is approximated through a Gaussian mixture model whose parameters are calculated by the ABC algorithm. On the other hand, the circle detector uses a combination of three edge points as parameters to construct candidate circles. A matching function determines is such candidate circles are actually present in the image. Experimental results show that the generated solutions are able to solve properly the considered problems.

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Published

2015-06-18

How to Cite

Cuevas, E. (2015). Artificial Bee Colony (ABC) algorithm and its use in digital image processing. Inteligencia Artificial, 18(55), 50-68. https://doi.org/10.4114/intartif.vol18iss55pp50-68