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Ellipse Detection on Images Inspired by the Collective Animal Behavior

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Applications of Evolutionary Computation in Image Processing and Pattern Recognition

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 100))

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Abstract

This chapter presents an effective technique for extracting multiple ellipses from an image. The approach employs an evolutionary algorithm that mimic the way in which animals behave collectively assuming the overall detection process as a multi-modal optimization problem. In the algorithm, searcher agents emulate a group of animals that interact to each other using simple biological rules which are modeled as evolutionary operators. In turn, such operators are applied to each agent considering that the complete group has a memory to store optimal solutions (ellipses) seen so-far by applying a competition principle. The detector uses a combination of five edge points as parameters to determine ellipse candidates (possible solutions) while a matching function determines if such ellipse candidates are actually present in the image. Guided by the values of such matching functions, the set of encoded candidate ellipses are evolved through the evolutionary algorithm so that the best candidates can be fitted into the actual ellipses within the image. Just after the optimization process ends, an analysis over the embedded memory is executed in order to find the best obtained solution (the best ellipse) and significant local minima (remaining ellipses). Experimental results over several complex synthetic and natural images have validated the efficiency of the resultant technique regarding accuracy, speed and robustness.

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Authors and Affiliations

  1. CUCEI, Universidad de Guadalajara, Av. Revolución 1500, Guadalajara, Mexico

    Erik Cuevas & Daniel Zaldívar

  2. Centro Universitario de Tonalá, Universidad de Guadalajara, Av. Nuevo Periférico No. 555 Ejido San José Tatepozco, 48525, Tonalá, JAL, Mexico

    Marco Perez-Cisneros

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  1. Erik Cuevas
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  2. Daniel Zaldívar
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  3. Marco Perez-Cisneros
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Correspondence to Erik Cuevas .

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Cuevas, E., Zaldívar, D., Perez-Cisneros, M. (2016). Ellipse Detection on Images Inspired by the Collective Animal Behavior. In: Applications of Evolutionary Computation in Image Processing and Pattern Recognition. Intelligent Systems Reference Library, vol 100. Springer, Cham. https://doi.org/10.1007/978-3-319-26462-2_4

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  • DOI: https://doi.org/10.1007/978-3-319-26462-2_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-26460-8

  • Online ISBN: 978-3-319-26462-2

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