Multiobjective Genetic Algorithm for Image Thresholding

  • Layla Tahri
  • Mohamed Wakrim
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7340)


In this paper we present a new image thresholding method based on a multiobjective Genetic Algorithm using the Pareto optimality approach. We aim to optimize multiple criteria in order to increase the segmentation quality. Thus, we’ve adapted the well-known Non Domination Sorting Genetic Algorithm [1] for this purpose so that it takes into consideration the contribution of the objective functions in improving the reproduction step and then improving the optimal Pareto front of solutions. Our method was tested against NSGAII algorithm and has shown effectiveness and convergence speed.


Evolutionary approach Genetic algorithms Image segmentation Image thresholding Multiobjective optimization Pareto optimization 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Layla Tahri
    • 1
  • Mohamed Wakrim
    • 1
  1. 1.Faculty of Sciences, EMMSIbnZohr UniversityAgadirMorocco

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