The Graphical Specification of Similarity Queries

S. Santini, R. Jain
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引用次数: 41

Abstract

Abstract Image databases will require a completely new organization due to the unstructured and ‘perceptual’ structure of the data they contain. We argue that similarity measures, rather than matching, will be the organizing principle of image databases. Similarity is a very elusive and complex judgment, and typical databases will have to rely on a number of different metrics to satisfy the different needs of their users. This poses the problem of how to combine different similarity measures in a coherent and intuitive way. In this paper we propose our solution, which is loosely based on ideas derived from fuzzy logic in that it uses the equivalent in the similarity domain of the and, or and not operations. The approach is much more general than that, however, and can be adapted to work with any operation that combines together similarity judgment. With this approach, a query can be described as a Directional Acyclic graph with certain properties. We analyse briefly the properties of this graph, and we present the interface we are developing to specify these queries.
相似查询的图形化规范
图像数据库将需要一个全新的组织,因为它们包含的数据是非结构化和“感知”结构。我们认为相似性度量,而不是匹配,将是图像数据库的组织原则。相似性是一个非常难以捉摸和复杂的判断,典型的数据库将不得不依赖许多不同的度量来满足其用户的不同需求。这就提出了如何以连贯和直观的方式组合不同相似性度量的问题。在本文中,我们提出了我们的解决方案,它松散地基于模糊逻辑的思想,因为它使用了和,或和非操作的相似域中的等价。然而,该方法比这要通用得多,并且可以适用于将相似性判断结合在一起的任何操作。使用这种方法,可以将查询描述为具有某些属性的定向无环图。我们简要地分析了这个图的属性,并给出了我们正在开发的接口来指定这些查询。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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