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Robust Circle Detection Using Harmony Search
Author
Source
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-08-02
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Fourie, Jaco. 2017. Robust Circle Detection Using Harmony Search. Journal of Optimization،Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1185975
Modern Language Association (MLA)
Fourie, Jaco. Robust Circle Detection Using Harmony Search. Journal of Optimization No. 2017 (2017), pp.1-11.
https://search.emarefa.net/detail/BIM-1185975
American Medical Association (AMA)
Fourie, Jaco. Robust Circle Detection Using Harmony Search. Journal of Optimization. 2017. Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1185975
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1185975