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Journal of Optimization
Volume 2017, Article ID 9710719, 11 pages
Research Article

Robust Circle Detection Using Harmony Search

Lincoln Agritech Ltd., Lincoln, New Zealand

Correspondence should be addressed to Jaco Fourie; moc.liamg@eiruofocaj

Received 10 January 2017; Accepted 24 May 2017; Published 2 August 2017

Academic Editor: Ferrante Neri

Copyright © 2017 Jaco Fourie. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Automatic circle detection is an important element of many image processing algorithms. Traditionally the Hough transform has been used to find circular objects in images but more modern approaches that make use of heuristic optimisation techniques have been developed. These are often used in large complex images where the presence of noise or limited computational resources make the Hough transform impractical. Previous research on the use of the Harmony Search (HS) in circle detection showed that HS is an attractive alternative to many of the modern circle detectors based on heuristic optimisers like genetic algorithms and simulated annealing. We propose improvements to this work that enables our algorithm to robustly find multiple circles in larger data sets and still work on realistic images that are heavily corrupted by noisy edges.