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Multimedia Image Mining Method Based on Fuzzy Pixels Difference Iterative Clustering

机译:基于模糊像素差异迭代聚类的多媒体图像挖掘方法

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摘要

The traditional multimedia image mining based on association rules, has a big flaw in mining time, thus a multimedia image mining method based on fuzzy pixel difference iterative clustering is proposed. In this method, multimedia image index characteristic value is converted into relative membership degree for fuzzy concept index. On the basis of the multimedia image samples and fuzzy pixel difference comprehensive tradeoff metric equations of different types, the Lagrange function is constructed to acquire fuzzy pixel difference iterative clustering loop iteration model. The model is adopted to analyze average divergence inside the cluster and average separation degree between clusters and choose the optimal clustering number value, so as to achieve mining of multimedia image. The results of simulation experiment show that the mining time and energy consumption of the proposed method are better than the traditional method, and the proposed method has a high value of application.
机译:基于关联规则的传统多媒体图像挖掘在采矿时具有大缺陷,因此提出了一种基于模糊像素差迭代聚类的多媒体图像挖掘方法。 在此方法中,多媒体图像索引特征值被转换为模糊概念索引的相对隶属度。 在多媒体图像样本和模糊像素差异综合术略公制等于不同类型的基础上,构造了拉格朗日函数以获取模糊像素差迭代聚类循环迭代模型。 采用该模型分析集群内的平均分歧和集群之间的平均分离程度,并选择最佳聚类数值,从而实现多媒体图像的挖掘。 仿真实验结果表明,所提出的方法的采矿时间和能耗优于传统方法,提出的方法具有高价值的应用。

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