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Cuckoo Search and Firefly Algorithm Applied to Multilevel Image Thresholding

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Cuckoo Search and Firefly Algorithm

Part of the book series: Studies in Computational Intelligence ((SCI,volume 516))

Abstract

Multilevel image thresholding is a technique widely used in image processing, most often for segmentation. Exhaustive search is computationally prohibitively expensive since the number of possible thresholds to be examined grows exponentially with the number of desirable thresholds. Swarm intelligence metaheuristics have been used successfully for such hard optimization problems. In this chapter we investigate performance of two relatively new swarm intelligence algorithms, cuckoo search and firefly algorithm, applied to multilevel image thresholding. Particle swarm optimization and differential evolution algorithms have also been implemented for comparison. Two different objective functions, Kapur’s maximum entropy thresholding function and multi Otsu between-class variance, were used on standard benchmark images with known optima from exhaustive search (up to five threshold points). Results show that both, cuckoo search and firefly algorithm, exhibit superior performance and robustness.

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Acknowledgments

This reserach was supported by Ministry of Education and Science of Republic of Serbia, Grant III-44006.

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Authors and Affiliations

  1. University of Belgrade, Studentski trg 16, 11000 , Belgrade, Serbia

    Ivona Brajevic

  2. Megatrend University Belgrade, Bulevar umetnosti 29, 11070 , N. Belgrade, Serbia

    Milan Tuba

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  1. Ivona Brajevic
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  2. Milan Tuba
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Correspondence to Ivona Brajevic .

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Editors and Affiliations

  1. School of Science and Technology, Middlesex University, London, United Kingdom

    Xin-She Yang

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Brajevic, I., Tuba, M. (2014). Cuckoo Search and Firefly Algorithm Applied to Multilevel Image Thresholding. In: Yang, XS. (eds) Cuckoo Search and Firefly Algorithm. Studies in Computational Intelligence, vol 516. Springer, Cham. https://doi.org/10.1007/978-3-319-02141-6_6

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  • DOI: https://doi.org/10.1007/978-3-319-02141-6_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-02140-9

  • Online ISBN: 978-3-319-02141-6

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