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Image similarity detection in large visual data bases

机译:大型视觉数据基础中的图像相似性检测

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摘要

A method of similarity clusters detection in large visual databases is described in this work. Similarity clusters have been defined on the basis of a general concept of similarity measure. The method is based also on the properties of morphological spectra as a tool for image presentation. In the proposed method similarity of selected spectral components in selected basic windows are used to similarity of images evaluation. Similarity clusters are detected in an iterative process in which non-perspective subsets of images are step-by-step removed from considerations. In the method similarity graphs and hyper-graphs also play an auxiliary role. The method is illustrated by an example of a collection of medical images in which similarity clusters have been detected.
机译:在这项工作中描述了大型视觉数据库中的相似性簇检测的方法。相似群集已经根据相似度措施的一般概念定义。该方法还基于形态光谱的性质作为图像呈现的工具。在所选择的基本窗口中所选择的光谱分量的相似性,用于图像评估的相似性。在一个迭代过程中检测相似性集群,其中图像的非透视子集是从考虑中逐步移除。在方法中,相似性图和超图也播放了辅助作用。该方法是通过检测到相似性簇的医学图像的集合的示例来说明的。

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