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Similarity Estimation of Textile Materials Based on Image Quality Assessment Methods

机译:基于图像质量评估方法的纺织材料相似度估计

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In this paper some experimental results obtained by the application of various image quality assessment methods for the estimation of similarity of textile materials are presented. Such approach is considered as a part of an artificial intelligence based system developed for the recognition of clothing styles based on multi-dimensional analysis of descriptors and features. For the verification of the usefulness of image quality metrics for this purpose, mainly those based on the comparison of the local similarity of image fragments have been chosen. Nevertheless, since the most of them are applied only for grayscale images, various methods of color to grayscale conversion have been analyzed. Obtained results are promising and may be successfully applied in combination with some other algorithms used e.g. in CBIR systems. Since the analyzed metrics do not use any information related to shape of objects, further combination with shape and color descriptors may be used.
机译:本文介绍了通过应用各种图像质量评估方法估算纺织品材料相似性而获得的一些实验结果。这种方法被认为是基于人工智能的系统的一部分,该系统是基于对描述符和特征的多维分析来识别服装样式而开发的。为了验证图像质量度量是否为此目的有用,主要选择了基于图像片段局部相似性比较的图像质量度量。但是,由于大多数仅用于灰度图像,因此已经分析了各种从颜色到灰度的转换方法。所获得的结果是有希望的,并且可以与所使用的一些其他算法(例如,算法)结合成功地应用。在CBIR系统中。由于分析的度量不使用任何与对象形状有关的信息,因此可以使用形状和颜色描述符的进一步组合。

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