【Key words】 mechanical parts image； contour feature； feature extraction； edge moment； horizontal tilt correction； means clustering algorithm；
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Fuzzy C-Means Clustering Algorithm 模糊C均值聚类算法
fuzzy K means clustering algorithm 模糊K均值聚类算法
k-means clustering algorithm K均值聚类算法
c means clustering algorithm c均值聚类算法
Spherical K-means clustering Algorithm 球面k均值聚类算法
weighting fuzzy c-means clustering algorithm 加权模糊c均值聚类算法
Kernel-Based Fuzzy C-Means Clustering Algorithm 核函数模糊C均值聚类算法
In the experiments,the K means clustering algorithm was used to classify the parts based on the extracted contour features,and the results proved its effectiveness.
最后,采用K均值聚类算法对提取的零件轮廓特征进行分类,实验结果证明了该方法的有效性。
参考来源 - 基于边界矩的机械零件图像轮廓特征提取技术·2,447,543篇论文数据，部分数据来源于NoteExpress
Results Fuzzy K means clustering algorithm can segment white matter, gray matter and CSF better from the MR head images.
结果模糊K- 均值聚类算法能很好地分割出磁共振颅脑图像中的灰质、 白质和脑脊液。
According to the characteristics of traffic flow, it USES fuzzy C-means clustering algorithm to deal with these fuzzy factors.
根据交通流特性，运用模糊C均值聚类算法对交通流各要素进行模糊分析处理。
The results revealed that fuzzy c-means clustering algorithm could be used to delineate management zones by using the given variables.
利用所选取的变量，模糊c均值聚类算法可以较好地进行管理分区划分。
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