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A comparative study of curvature scale space and Fourier descriptors for shape-based image retrieval

机译:基于形状的图像检索的曲率尺度空间和傅立叶描述符的比较研究

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摘要

Contour shape descriptors are among the important shape description methods. Fourier descriptors (FDs) and curvature scale space descriptors (CSSDs) are widely used as contour shape descriptors for image retrieval in the literature. In MPEG-7, CSSD has been proposed as one of the contour-based shape descriptors. However, no comprehensive comparison has been made between these two shape descriptors. In this paper we study and compare FD and CSSD using standard principles and standard database. The study targets image retrieval application. Our experimental results show that FD outperforms CSSD in terms of robustness, low computation, hierarchical representation, retrieval performance, and suitability for efficient indexing.
机译:轮廓形状描述符是重要的形状描述方法之一。在文献中,傅立叶描述符(FDs)和曲率尺度空间描述符(CSSD)被广泛用作图像检索的轮廓形状描述符。在MPEG-7中,已经提出CSSD作为基于轮廓的形状描述符之一。但是,这两个形状描述符之间没有进行全面的比较。在本文中,我们使用标准原理和标准数据库来研究和比较FD和CSSD。该研究针对图像检索应用。我们的实验结果表明,FD在健壮性,低计算量,分层表示,检索性能以及对高效索引的适用性方面均优于CSSD。

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