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Comparative study of global color and texture descriptors for web image retrieval

机译:Web图像检索中全局颜色和纹理描述符的比较研究

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摘要

This paper presents a comparative study of color and texture descriptors considering the Web as the envi ronment of use. We take into account the diversity and large-scale aspects of the Web considering a large number of descriptors (24 color and 28 texture descriptors, including both traditional and recently pro posed ones). The evaluation is made on two levels: a theoretical analysis in terms of algorithms complex ities and an experimental comparison considering efficiency and effectiveness aspects. The experimental comparison contrasts the performances of the descriptors in small-scale datasets and in a large hetero geneous database containing more than 230 thousand images. Although there is. a significant correlation between descriptors performances in the two settings, there are notable deviations, which must be taken into account when selecting the descriptors for large-scale tasks. An analysis of the correlation is pro vided for the best descriptors, which hints at the best opportunities of their use in combination.
机译:本文提出了一种将Web作为使用环境的颜色和纹理描述符的比较研究。考虑到大量的描述符(24种颜色和28种纹理描述符,包括传统和最近提出的描述符),我们考虑了Web的多样性和大规模方面。评估分为两个级别:从算法复杂性方面进行理论分析,以及从效率和有效性两方面进行实验比较。实验比较对比了描述符在小型数据集和包含23万多个图像的大型异构数据库中的性能。虽然有。两种设置中的描述符性能之间存在显着的相关性,存在明显的偏差,在为大型任务选择描述符时必须考虑这些偏差。提供了最佳描述符的相关性分析,这暗示了将它们组合使用的最佳机会。

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