【摘要】 为提高模糊C均值(FCM)算法的自动化程度,提出基于微分进化算法的FCM图像分割算法(DEFCM),利用微分进化算法全局性和鲁棒性的特点自动确定分类数和初始聚类中心,再将其作为模糊c均值聚类的初始聚类中心,弥补FCM算法的不足.实验表明该算法不仅能够正确地对图像分类,而且能获得较好的图像分割效果和质量.更多还原

【Abstract】 A fuzzy c-means algorithm based on differential evolution for image segmentation is proposed to increase the automaticity of the fuzzy c-means algorithm.First the overall robustness advantages of the differential evolution algorithm are used to get the classifying number and the cluster centers of image automatically.Then the results are obtained as the initial cluster centers of fuzzy C-means algorithm.The experimental results show that new algorithm can not only automatically estimate the appropriate number of clusters,it also can get better segmentation quality than FCM’s.更多还原