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Fast Circle Detection Using Harmony Search Optimization

  • Conference paper
EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation II

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 175))

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Abstract

Automatic circle detection in digital images has received considerable attention over the last years. Recently, several robust circle detectors, based on evolutionary algorithms (EA), have been proposed. They have demonstrated to provide better results than those based on the Hough Transform. However, since EA-detectors usually need a large number of computationally expensive fitness evaluations before a satisfying result can be obtained; their use for real time has been questioned. In this work, a new algorithm based on the Harmony Search Optimization (HSO) is proposed to reduce the number of function evaluation in the circle detection process. In order to avoid the computation of the fitness value of several circle candidates, the algorithm estimates their values by considering the fitness values from previously calculated neighboring positions. As a result, the approach can substantially reduce the number of function evaluations preserving the good search capabilities of HSO. Experimental results from several tests on synthetic and natural images with a varying complexity range have been included to validate the efficiency of the proposed technique regarding accuracy, speed and robustness.

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Author information

Authors and Affiliations

  1. Dept. de C. Comput, CUCEI-UDEG, Av. Revolución 1500, Guadalajara, Jal, Mexico

    Erik Cuevas, Daniel Zaldivar & Marco Pérez-Cisneros

  2. CIC-IPN, Juan de Dios Batiz S/N, Col. Nva. Industrial Vallejo, Mexico City, Mexico

    Humberto Sossa & Valentín Osuna

Authors
  1. Erik Cuevas
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  2. Humberto Sossa
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  3. Valentín Osuna
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  4. Daniel Zaldivar
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  5. Marco Pérez-Cisneros
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Corresponding author

Correspondence to Erik Cuevas .

Editor information

Editors and Affiliations

  1. , Computer Science Department, CINVESTAV-IPN, Col. San Pedro Zacatenco 2508, Mexico City, 07360, Mexico

    Oliver Schütze

  2. , Computer Science Department, CINVESTAV-IPN, Col. San Pedro Zacatenco 2508, Mexico City, 07360, Mexico

    Carlos A. Coello Coello

  3. , Computer Science and Communications, University of Luxembourg, rue Richard Coudenhove-Kalergi 6, Luxembourg, 1359, Luxembourg

    Alexandru-Adrian Tantar

  4. Computer Science and Communications, Research Unit, University of Luxembourg, rue Richard Coudenhove-Kalergi 6, Luxembourg, L-1359, Luxembourg

    Emilia Tantar

  5. Computer Science, and Communications, University of Luxembourg, rue Richard Coudenhove-Kalergi 6, Luxembourg, L-1359, Luxembourg

    Pascal Bouvry

  6. Bordeaux Mathematical Institute, INRIA Bordeaux-Sud Ouest, Université Bordeaux I, cours de la Libération 351, Talence Cedex, 33405, France

    Pierre Del Moral

  7. Bâtiment Leyteire, UFR Sciences et Modélisation, Université Bordeaux II, 3ter place de la Victoire, Bordeaux, 33000, France

    Pierrick Legrand

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Cuevas, E., Sossa, H., Osuna, V., Zaldivar, D., Pérez-Cisneros, M. (2013). Fast Circle Detection Using Harmony Search Optimization. In: Schütze, O., et al. EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation II. Advances in Intelligent Systems and Computing, vol 175. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31519-0_20

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  • DOI: https://doi.org/10.1007/978-3-642-31519-0_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31518-3

  • Online ISBN: 978-3-642-31519-0

  • eBook Packages: EngineeringEngineering (R0)

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