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Block-based Against Segmentation-based Texture Image Retrieval

机译:基于块的反对基于分割的纹理图像检索

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摘要

This paper concerns the best approach to the capture of local texture features for use in content-based image retrieval (CBIR) applications. From our previous work, two approaches have been suggested, the multiscale block-based approach and the automatic texture segmentation approach. Performance comparison as well as advantages and disadvantages of the two methods are presented in this paper. The databases used are the Brodatz and VisTex databases, as well as three museum image collections of various sizes and contents, with each collection presenting different challenges to the CBIR systems. Experimental observations suggest that the two approaches both perform well, with the multiscale technique having the edge in retrieval performance and scale invariance, while the segmentation technique has the edge in lighter computational complexity as well as having the shape information for later purposes. The choice between the two approaches thus depends on application.
机译:本文涉及用于基于内容的图像检索(CBIR)应用程序中捕获局部纹理特征的最佳方法。从我们以前的工作中,提出了两种方法,基于多尺度块的方法和自动纹理分割方法。本文介绍了两种方法的性能比较以及优缺点。所使用的数据库是Brodatz和VisTex数据库,以及三个具有不同大小和内容的博物馆图像集合,每个集合对CBIR系统提出了不同的挑战。实验观察表明,这两种方法均表现良好,多尺度技术在检索性能和尺度不变性方面具有优势,而分段技术在计算复杂度方面具有优势,并且具有用于以后用途的形状信息。因此,两种方法之间的选择取决于应用。

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