基于空间相似度和标注的图像检索系统

SooCheol Lee, Eenjun Hwang
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引用次数: 13

摘要

基于内容的图像检索(CBIR)系统通常依赖于全局图像特征,如颜色和纹理直方图,但不依赖于图像组件对象之间的空间关系。在本文中,我们描述了一种新的图像检索方案,该方案首先识别图像中感兴趣的对象,并注释它们之间的空间关系以及它们的特征(包括语义信息)以表示图像。该系统的一个重要且独特的方面是,允许用户根据图像的对象及其空间关系制定查询。这可以提高从图像数据库中检索图像的精度和灵活性。在原型系统中,对象感兴趣的语义信息和它们之间的空间关系被捕获并使用XML表示。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Spatial similarity and annotation-based image retrieval system
Content-based image retrieval (CBIR) systems often rely on global image characteristics such as color and texture histograms, but not the spatial relationships among component objects of an image. In this paper, we describe a new image retrieval scheme where objects of interest in an image are first identified and spatial relationships among them as well as their features including semantic information are annotated to represent the image. An important and unique aspect of the system is that users are allowed to formulate a query based on both objects of an image and their spatial relationships. This could give better precision and flexibility to retrieve images from image databases. In the prototype system, semantic information of interest for objects and the spatial relationships among them are captured and represented using XML.
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