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中文摘要：
针对实际应用中三维模型数据集的模型分类管理、检索聚类预处理等聚类问题,提出了一种基于划分方法的无监督聚类模型。该模型通过以傅里叶矩不变算法为基础的特征提取算法,综合运用了现有聚类算法,将特征提取和聚类计算有效结合起来,充分考虑了聚类模型数据格式的敏感性问题。计算结果表明,该方法对有一定类结构的数据集在有整体聚类效果的情况下有一定的局部最优性。
英文摘要：
In view of the practical application problems in three-dimensional model data sets clustering,such as model classification management,the clustering pretreatment for retrieval,etc,a new clustering model based on the classification method and which was featured by unsupervised learning,was proposed.Through adopting feature extraction algorithm grounded on the MFD（Moment Fourier Description） and integrating the existing sophisticated clustering algorithms,this model combined feature extraction with clustering computation effectively,besides taking full considerations of sensitivity issues of clustering data format.The compuatation results indicated that this model could gain local optimality to the certain classified structure data sets on the premise of having overall clustering effect.
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