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Hybrid Swarms Optimization Based Image Segmentation

  • Mohamed Abd El AzizEmail author
  • Ahmed A. Ewees
  • Aboul Ella Hassanien
Chapter

Abstract

This chapter proposed multilevel thresholding hybrid swarms optimization algorithm for image segmentation. The proposed algorithm is inspired by the behavior of fireflies and real spider. It uses Firefly Algorithm (FA) and Social Spider Optimization (SSO) algorithm (FASSO). The objective function used for achieving multilevel thresholding is the maximum between class variance criterion. The proposed algorithm uses the FA to optimize threshold, and then uses this thresholding value to partition the images through SSO algorithm of a powerful global search capability. Experimental results demonstrate the effectiveness of the FASSO algorithm of image segmentation and provide faster convergence with relatively lower CPU time.

Keywords

Swarms optimization Firefly Algorithm Social Spider Optimization Multilevel thresholding Image segmentation 

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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Mohamed Abd El Aziz
    • 1
    Email author
  • Ahmed A. Ewees
    • 2
  • Aboul Ella Hassanien
    • 3
    • 4
  1. 1.Department of Mathematics, Faculty of ScienceZagazig UniversityZagazigEgypt
  2. 2.Department of ComputerDamietta UniversityDamiettaEgypt
  3. 3.Faculty of Computers and InformationCairo UniversityGizaEgypt
  4. 4.Scientific Research Group in Egypt (SRGE)GizaEgypt

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