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Research on similarity measurement method of statistical sorting region based on differentiation and location information

机译:基于差异和位置信息的统计排序区域相似度测量方法研究

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In the process of content-based image retrieval, making reasonable matching strategy and similarity measurement is the key technology to ensure the accuracy, quality and matching speed of image matching and retrieval. In this chapter, we focus on the problem of image feature selection and similarity measurement in content-based image retrieval technology, and propose a regional similarity measurement method based on differentiation and location information by using large image plane position constraint. This method mainly includes the following two aspects. One is the feature selection method based on global feature differentiation; the other is the similarity measurement method based on location information. Finally, we use the idea of statistical sorting to synthesize the image matching strategy and similarity measurement criteria through the set of feature points in the hot area. Thus, the problem of image similarity measurement from single feature point matching to target region can be solved.
机译:在基于内容的图像检索过程中,制定合理的匹配策略和相似度度量是保证图像匹配和检索的准确性,质量和匹配速度的关键技术。在本章中,我们着重研究基于内容的图像检索技术中的图像特征选择和相似度测量问题,并通过使用大图像平面位置约束,提出一种基于差异和位置信息的区域相似度测量方法。该方法主要包括以下两个方面。一种是基于全局特征差异的特征选择方法。另一种是基于位置信息的相似度测量方法。最后,我们使用统计排序的思想通过热点区域中的特征点集来合成图像匹配策略和相似性度量标准。因此,可以解决从单个特征点匹配到目标区域的图像相似性测量的问题。

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