We bring out our video retrieval method based on multi-feature data association histogram and C-Mean fuzzy clustering algorithm.
基于多特征联合分布直方图理论和模糊c -均值聚类算法，我们提出了新的视频流模糊检索方法。
An algorithm for selecting episode representation frames by using an approach of key frame extraction based on multiple characters and C-Mean fuzzy clustering is detailed in the paper.
该文在子镜头的关键帧提取方法基础上，利用模糊c -均值聚类算法，实现了一种基于子镜头聚类的情节代表帧选取方法。
A method based on fuzzy C-mean clustering and image matching algorithms are proposed to detect atomization Angle and uniformity, applied to performance test-bed of engine nozzle.
提出了基于模糊C均值聚类和图像匹配，检测喷雾锥角和喷雾不均匀度的方法，并应用于发动机喷嘴性能检测。
Selecting train sample on the basis of fuzzy C-mean clustering can improve accuracy of train sample, singleness of train samples can be satisfied.
在模糊c -均值聚类的基础上选择训练样本，可以提高训练样本的准确度，满足了训练样本所需的单一性原则。
The rambutan flesh was segmented using the FCM (fuzzy C-mean) clustering method after removing the background of the image.
首先用阈值分割法去除红毛丹背景，然后用模糊C均值聚类方法来分割果肉区域。
Several new algorithms of fuzzy C-mean clustering with the combination of vector quantization are proposed for speaker identification.
该文提出了一种将模糊C -均值聚类法的各种改进算法与矢量量化法相结合的说话人辨认的新方法。
Selecting train sample on the basis of fuzzy C-mean clustering decreased subjective factor affecting selecting train sample, so higher classification accuracy can be achieved.
同时，在模糊C-均值聚类基础上选择训练样本比起直接基于真实地物图选择，减少了主观因素对训练样本选择的影响，因此取得了更高的分类精度。
Selecting train sample on the basis of fuzzy C-mean clustering decreased subjective factor affecting selecting train sample, so higher classification accuracy can be achieved.
同时，在模糊C-均值聚类基础上选择训练样本比起直接基于真实地物图选择，减少了主观因素对训练样本选择的影响，因此取得了更高的分类精度。
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