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Image Segmentation Using an Evolutionary Method Based on Allostatic Mechanisms

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Image Feature Detectors and Descriptors

Part of the book series: Studies in Computational Intelligence ((SCI,volume 630))

Abstract

In image analysis, segmentation is considered one of the most important steps. Segmentation by searching threshold values assumes that objects in a digital image can be modeled through distinct gray level distributions. In this chapter it is proposed the use of a bio-inspired algorithm, called Allostatic Optimisation (AO), to solve the multi threshold segmentation problem. Our approach considers that an histogram can be approximated by a mixture of Cauchy functions, whose parameters are evolved by AO. The contributions of this chapter are on three fronts, by using: a Cauchy mixture to model the original histogram of digital images, the Hellinger distance as an objective function, and AO algorithm. In order to illustrate the proficiency and robustness of the proposed approach, it has been compared to the well-known Otsu method, over several standard benchmark images.

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Author information

Authors and Affiliations

  1. Departamento de Ingenierías, CUTonalá, Universidad de Guadalajara, Tonalá, Jalisco, Mexico

    Valentín Osuna-Enciso & Virgilio Zúñiga

  2. Departamento de Ciencias Computacionales, Tecnológico de Monterrey, Campus Guadalajara, Guadalajara, Jalisco, Mexico

    Diego Oliva

  3. Departamento de Ciencias Computacionales, CUCEI, Universidad de Guadalajara, Guadalajara, Jalisco, Mexico

    Erik Cuevas

  4. Instituto Politécnico Nacional-CIC, México D.F., Mexico

    Humberto Sossa

Authors
  1. Valentín Osuna-Enciso
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  2. Virgilio Zúñiga
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  3. Diego Oliva
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  4. Erik Cuevas
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  5. Humberto Sossa
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Corresponding author

Correspondence to Valentín Osuna-Enciso .

Editor information

Editors and Affiliations

  1. Department of Computer Science, Luleå University of Technology, Luleå, Sweden

    Ali Ismail Awad

  2. Image and Video Processing Lab, Faculty, South Valley University, Qena, Egypt

    Mahmoud Hassaballah

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Osuna-Enciso, V., Zúñiga, V., Oliva, D., Cuevas, E., Sossa, H. (2016). Image Segmentation Using an Evolutionary Method Based on Allostatic Mechanisms. In: Awad, A., Hassaballah, M. (eds) Image Feature Detectors and Descriptors . Studies in Computational Intelligence, vol 630. Springer, Cham. https://doi.org/10.1007/978-3-319-28854-3_10

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  • DOI: https://doi.org/10.1007/978-3-319-28854-3_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-28852-9

  • Online ISBN: 978-3-319-28854-3

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