图像数据库的模糊对象查询语言(FOQL)

S. Nepal, M. Ramakrishna, J. Thom
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引用次数: 43

摘要

基于内容的检索系统已经开发出来用于查询图像数据,其中用户可以基于视觉属性(如颜色和纹理)提出查询。这些系统虽然在图像数据库系统中取得了进步,但明显缺乏正式的查询语言。传统的查询语言无法捕捉图像数据和基于内容的查询固有的模糊性。本文提出的模糊对象查询语言(FOQL)解决了图像数据库需要支持模糊值和模糊集合的问题。它可用于定义模式和高级概念,以及查询图像数据库。它通过保持查询结果相对于其他查询语言的模糊性,抓住了基于内容的检索固有的模糊性。用户可以使用FOQL中的递归和命名查询定义构造交互式地改进查询和高级概念定义。作为ODMG-OQL的扩展,FOQL可以很容易地映射到符合odmg的可视化查询语言。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A fuzzy object query language (FOQL) for image databases
Content based retrieval systems have been developed for querying image data in which the users can pose queries based on visual properties such as color and texture. These systems, which have advanced the state of the art in image database systems, remarkably lack formal query languages. The traditional query languages are unable to capture the inherent fuzzy nature of the image data and content based querying. The fuzzy object query language (FOQL) presented in this paper addresses the need to support fuzzy values and fuzzy collections required for image databases. It can be used for defining schemas and high level concepts, and for querying image databases. It captures the inherent fuzzy nature of content based retrieval by keeping the query results fuzzy as against other query languages. The users can interactively refine their queries and high level concept definitions using recursive and named query definition constructs in FOQL. Being an extension of ODMG-OQL, FOQL can be easily mapped to ODMG-compliant visual query languages.
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