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Research on Fuzzy Clustering Image Segmentation Algorithm based on GA and Gray Histogram

机译:基于GA和灰度直方图的模糊聚类图像分割算法研究

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When the traditional FCM algorithm is applied to image segmentation, it is sensitive to the selection of clustering center and can not automatically determine the number of clustering center. According to these problems, this paper proposes a fuzzy clustering image segmentation algorithm based on genetic algorithm and gray histogram. This algorithm uses the global search characters of genetic algorithm to avoid falling into local optimal solution, and the objective function is optimized and the number of the cluster center is determined by gray histogram. Experimental results show that the proposed method has strong robustness and good segmentation effect.
机译:当传统的FCM算法应用于图像分割时,它对聚类中心的选择很敏感,并且无法自动确定聚类中心的数量。根据这些问题,本文提出了一种基于遗传算法和灰度直方图的模糊聚类图像分割算法。该算法使用遗传算法的全局搜索特征来避免落入局部最佳解决方案,并且通过灰度直方图确定目标函数并确定集群中心的数量。实验结果表明,该方法具有强大的鲁棒性和良好的分割效果。

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