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首页> 外文期刊>IAENG Internaitonal journal of computer science >Some Notes on Fuzzy Similarity Measures and Application to Classification of Shapes, Recognition of Arabic Sentences and Mosaic
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Some Notes on Fuzzy Similarity Measures and Application to Classification of Shapes, Recognition of Arabic Sentences and Mosaic

机译：关于模糊相似性度量的一些注意事项及其在形状分类，阿拉伯语句子和马赛克识别中的应用

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摘要

Fuzzy Similarity measures are used to compare different kinds of objects such as images. Their definitions are based on proximity measures, operations on fuzzy sets etc. which makes different propositions of properties of similarity measures. Consequently, the latter are not common for all similarity measures presented in literature. In this paper we present and discuss the properties of fuzzy similarity and distance measures. We present fuzzy similarity measures from literature and we discuss their validation to the common existing properties. In order to compare and show the differences between fuzzy similarity measures, we apply them to three applications using different data sets defined with fuzzy attributes. The obtained results are good for most existing similarity measures, but some measures give best results and some others worst results. Therefore, relationships between obtained results and measures validation to their properties are discussed to know the influence of some properties on the results.
机译：模糊相似性度量用于比较不同种类的对象，例如图像。它们的定义基于接近度度量，对模糊集的运算等，从而对相似性度量的性质提出了不同的主张。因此，后者对于文献中提出的所有相似性度量并不普遍。在本文中，我们介绍并讨论了模糊相似度和距离测度的性质。我们从文献中提出了模糊相似性度量，并讨论了它们对常见现有属性的验证。为了比较并显示模糊相似性度量之间的差异，我们将它们应用于使用模糊属性定义的不同数据集的三个应用程序。所获得的结果对于大多数现有的相似性度量来说都是好的，但是某些度量给出了最佳结果，而另一些则给出了最差的结果。因此，讨论了获得的结果与度量验证对其属性之间的关系，以了解某些属性对结果的影响。

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