Abstract:

In order to improve the image segmentation accuracy, in view of the problems in the traditional fuzzy clustering algorithm, the author proposed an image segmentation algorithm based on improved genetic algorithm optimizing fuzzy means clustering center. First of all, the direction factor was introduced into the crossover operation of standard genetic algorithm to make individual in cross approach to the best individual so as to accelerate the convergence speed, and inter group information sharing mechanism was enhanced to improve the algorithm’s global search capability and avoid the premature convergence so as to improve the accuracy of global solution. Then the initial cluster centers of fuzzy kmeans clustering algorithm were selected by improved genetic algorithm to realize image segmentation. Finally the performance was tested by simulation experiments. The experimental results show that compared with the traditional fuzzy Cmeans clustering algorithm and other images segmentation algorithm, the proposed algorithm is better in segmentation accuracy rate, the segmentation speed and robustness.

Key words: image segmentation, fuzzy means clustering algorithm, genetic algorithm, orientation factor, information sharing