利用内容和模型注解的基于本体的语义web CBIR

P. Ambika, J. A. Samath
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引用次数: 1

摘要

随着互联网技术的发展和多媒体技术的普及,尤其是图像和视觉信息因其信息的丰富性和多样性,已成为信息检索的重要组成部分。传统的信息检索技术已不能满足用户的需求。近年来,基于内容的图像检索已成为研究的热点,基于内容的图像检索技术也取得了很大的发展。对基于颜色、纹理形状和语义的图像检索方法进行了讨论、分析和比较。基于语义的图像检索是解决语义缺口问题的较好方法,因此本文重点研究了基于本体的web图像检索方法。该模型考虑了本体论在可用性、智能性和有效性方面的要求。提出了基于内容和基于模型的标注模型,使图像查询变得简单有效。通过实证评估,我们的标注模型能够为语义web图像检索提供准确的结果。
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Ontology — Based semantic web CBIR by utilizing content and model annotations
With the internet technology development and the popularization of multimedia technology, especially images and visual information because of its rich and varied information, has become an important part of information retrieval. The traditional information retrieval techniques do not meet the users demand. Recently content based image retrieval has become the hottest topic and techniques of content based image retrieval has achieved great development. Image retrieval methods based on color, texture shape and semantics are discussed, analyzed and compared. The semantic based image retrieval is a better way to solve the semantic - gap problem, so Ontology - based web image retrieval method is stressed in this article. This model considers the ontological requirements in usability, intelligence and effectiveness. Based on the proposed content based and model based annotation models, the image query becomes easy and effective. Through empirical evaluations, our annotation models can deliver accurate results for semantic web image retrieval.
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