毕业设计——图像检索系统.doc

摘 要 基于文本的图像检索技术存在两个缺点。首先标注每个图像是比较困难的；再次主观性和图像注释的不精确性在检索过程中可能引起适应性问题。基于内容的图像检索技术克服了传统的图像检索技术的缺点。基于内容的图像检索技术分为特征提取和查询两个部分。本文主要介绍基于颜色特征的图像检索技术颜色特征是图像的基本特征也是最为直观的特征之一。着重探讨了颜色空间的选取颜色特征的提取和表达颜色的相似度以及现有的图像的检索系统和存在的问题。在这里颜色空间的选取有RGB颜色模式HSV颜色模型。颜色提取的基本思想是用颜色直方图来统计每种颜色出现的概率。目前相关的系统有QBIC系统、Photo book系统 、CORE系统等等。 关键词：基于内容的图像检索技术特征提取特征表达颜色直方图Abstract Traditional text-based image retrieval techniques have two shortcomings: First, it has been difficulties to note each image. Second, the subjectivity and no precision of image annotation may lead to the adaptation in the retrieval process. CBIR overcome the shortcomings of the traditional text-based image retrieval .Content-based image retrieval can divide into two parts, that is feature extraction and query. In this paper, based Color Image Retrieval is mainly introduced. Color features are the basic characteristics of the image as well as are one of the most intuitive features. Here we focused on the selection of color space, color feature extraction and expression, color similarity, and the existing image retrieval systems and problems. There are many color models to express color such as the RGB color model, the HSV color model. The basic idea to extract color is to use color histogram to calculate the probability statistics of each color .Currently there are some related systems QBIC system related system, Photo book system, CORE system and so on. Keywords: Content-based image retrieval; Feather extraction; Feather presentation; color histogram; 目 录 1 绪论 1 1.1 图像检索技术的发展 1 1.2 图像检索技术的特点和应用 1 1.3 图像检索系统的关键技术 2 1.4 基于内容图像检索的典型系统 3 1.4.1 QBIC系统 3 1.4.2 Virage系统 3 1.4.3 Photobook系统 3 1.4.4 VisualSEEK和WebSEEK系统 3 1.4.5 Netra系统 4 2 颜色空间 5 2.1 RGB 颜色空间 5 2.2 HSI颜色空间 7 3 颜色特征的表达 9 3.1 颜色直方图 9 3.2 全局直方图 10 3.3 累积直方图 11 3.4 局部累加直方图 11 4 颜色特征的相似性度量 12 4.1 距离度量方法 12 4.2 直方图的交集的方法 12 4.3 欧氏距离法 12 4.4 模糊理论 13 5 系统的设计与实现 15 5.1 系统的设计 15 5.1.1 系统名称 15 5.1.2 系统的开发环境 15 5.1.3 系统的结构 15 5.1.4 系统的实现算法描述 17 5.1.5 系统中