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基于纹理特征图像检索的研究与实现

Research and Implement of Texture-based Image Retrieval

【作者】 贾婧

【导师】 王忠芝;

【作者基本信息】 北京林业大学 , 计算机应用技术, 2010, 硕士

【摘要】 随着计算机网络和多媒体技术的发展,越来越多的图像信息出现在人们的生活中,那么如何在海量图像数据中找出所需要的图像成为研究热点。基于内容的图像检索技术应运而生,它不同于传统基于文本的检索,实际上是一种模糊查询技术,通过对图像提取一定的特征,找出在特征空间中与查询要求接近的图像。本文主要对基于纹理的图像检索技术进行了深入研究。首先对基于内容图像检索技术的基本原理和框架进行了概要介绍。然后对纹理特征的提取进行了深入的研究,重点研究的是灰度共生矩阵方法和包含颜色信息的三维共生矩阵方法,之后研究了基于内容图像检索的关键技术,包括相似性度量和相关反馈,最后设计并实现了一个基于纹理的图像检索系统,对系统的性能进行了评价,并提出了下一步的研究方向。在系统的实现部分,本文采用了一种边计算边排序的方法进行结果图像的相似程度排序。并为系统添加了相关反馈机制,通过调整权值进行重新检索后使用新的规则进行排序显示。通过对Corel图像库进行实验的结果表明,将三维共生矩阵法和本文设计的相关反馈机制相结合,能够使系统检索结果更符合用户需求。

【Abstract】 According to the development of computer network and multimedia technology, more and more image information appear in people’s lives. How to find out the picture we need in huge amounts of image data became a research focus. Therefore content-based image retrieval technology appeared. It is different from traditional text-based search. It is actually a fuzzy inquiry. By extracting certain features of the image it finds out similar images in feature space.The texture-based image retrieval technology is deeply studied in this paper. Firstly, the basic theory and frame of content-based image retrieval technology are introduced. Then the extraction of texture feature is studied deeply, focusing on the research of Gray Level Co-occurrence Matrix and the 3D Co-occurrence Matrix which including color information. Afterwards, the research of key technologies on content-based image retrieval system is done, including similarity measure and relevance feedback. Finally, designs and implements a texture-based image retrieval system and evaluates the system’s performance and proposes future research directions.In the part of system implementation, the paper used a method to sort result images based on similarity as calculating. And a relevance feedback mechanism is added to the system, by adjusting the weight to search again then sort and show images using the new rules. Through the experiments of Corel image library, the results showed that by combine 3D Co-occurrence Matrix method and the relevance feedback mechanism designed in this paper can make the search results more meet users’ needs.

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