Abstract Taking advantage of quantum genetic algorithm, a nested optimization method is proposed aiming at the generalized fuzzy entropy parameters. Quantum genetic algorithm is used to automatically determine the optimal parameter m in (0,1) based on an image segmentation quality evaluation criterion and the parameters of the fuzzy membership function corresponding to each m based on the maximum fuzzy entropy criterion. Thus, the automatic selection of threshold is realized in generalized fuzzy entropy-based image segmentation method. Experimental results show that the proposed method can obtain good segmentation results for images with poor illumination.
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2009, Vol. 22 
