Multiobjective genetic algorithm for image thresholding

  • Authors:

  • Layla Tahri;Mohamed Wakrim

  • Affiliations:

  • Faculty of Sciences, EMMS, IbnZohr University, Agadir, Morocco;Faculty of Sciences, EMMS, IbnZohr University, Agadir, Morocco

  • Venue:
  • ICISP'12 Proceedings of the 5th international conference on Image and Signal Processing
  • Year:
  • 2012

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Abstract

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.