基于内容的图像检索系统的自动视觉特征权重获取

Atoany N. Fierro-Radilla, K. Toscano-Medina, M. Nakano-Miyatake, H. Meana, M. Cedillo-Hernández, F. Garcia-Ugalde
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引用次数: 1

摘要

在基于内容的图像检索系统中,为了提高检索性能,需要组合多个视觉描述符。最常见的描述符是基于颜色、基于形状和基于纹理的描述符。当多个视觉描述符线性组合时,必须为每个视觉特征分配适当的权重。最常见的方法是为每个视觉特征设置相同的权重值。这些值的和必须等于1。然而,这一过程并不能保证CBIR系统的最佳性能。为了保证最佳的性能,需要进行多次实验来找到最优的权值组合。这是一个耗时且模糊的过程,因为权重值取决于数据库的性质。本文提出了一种自动计算最佳权值组合的方案,保证了系统的最佳性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic visual features weights obtention for Content-Based Image Retrieval Systems
In Content-Based Image Retrieval (CBIR) Systems it is necessary to combine more than one visual descriptor in order to improve the retrieval performance. The most common descriptors are Color-Based, Shape-Based and Texture-Based descriptors. When more than one visual descriptor is linearly combined, some adequate weight must be assigned to each visual feature. The most common manner is setting the same weight value for each visual feature. The sum of these values must be equal to one. However, this process does not guarantee the optimum performance of the CBIR system. In order to guarantee the best performance, it is necessary to do several experimentations to find the optimum weight values combination. This is time consuming process and ambiguous, due to the weights values depends on the nature of the databases. In this paper we proposed a scheme which computes automatically the best weight combination and guarantees the optimum performance of the CBIR system.
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