Multiobjective Genetic Algorithm for Image Thresholding
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  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.
KeywordsEvolutionary approach Genetic algorithms Image segmentation Image thresholding Multiobjective optimization Pareto optimization
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