An efficient segmentation method based upon fuzzy c-means (FCM) clustering principles is proposed. The approach utilizes a pyramid data structure for the hierarchical ana - lysis of color images.
这里提出了一种高效的基于模糊c均值(FCM)聚类的彩色图像分割方法，它利用塔形数据结构对彩色图像进行多层分割。
A new method integrated with fluctuation method and fuzzy C-means clustering was put forward and solved the above difficult problems.
文中提出的波动法与模糊c -均值聚类相结合的状态评级则有效地解决了上述问题。
Considering fuzzy C-means clustering algorithms are sensitive to initialization and easy fall - en to local minimum, a novel optimization method is proposed.
针对模糊C均值聚类算法对初始值敏感、易陷入局部最优的缺陷，提出一种新的优化方法。
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