基于LBP纹理特征的图像检索系统

题目：基于LBP纹理特征的图像检索系统

院（系）计算机科学与技术学院

专业软件工程

届别2008届

学号0825121037

姓名

指导老师

指导老师职称副教授

华侨大学教务处印制

2012年5 月

摘要

随着计算机网络的飞速发展和多媒体编码技术的进步，网络上的资源日益丰富，尤其是直观的形象的多媒体信息备受人们的亲睐基于内容的图像检索，即（CBIR）。CBIR的核心是使用图像的可视特征对图像进行检索。纹理分类与分割是图像处理领域一个经久不衰的热点研究领域,纹理特征提取作为纹理分类与分割的首要问题,一直是人们关注的焦点,各种纹理特征提取方法层出不穷。

局部二元模式（LBP）是一种灰度范围内的纹理描述方式，它从一种纹理局部近邻定义中衍生出来。本文实现了恒定的基础局域二值模式和旋转不变的局域二值模式两种纹理特征提取方式。通过LBP纹理图生成灰度直方图，计算灰度直方图之间的欧式距离以完成图像检索比对。本文采用VC++6.0环境下MFC项目导入OpenCV图像处理函数库设计了检索系统实现基于LBP纹理特征的图像检索。在(加利福尼亚理工学院256类图像数据库)及（Queensland大学分类的brodatz自然纹理图像库）下进行测试并对结果进行分析与讨论。

关键字： CBIR；LBP特征提取；图像识别

ABSTRACT

Along with the rapid development of the computer network and multimedia code technology progress, the network resources are increasingly rich, particularly intuitive image of the multimedia information is people's pro-gaze content-based image retrieval, namely (CBIR). The core of the image is used CBIR the visual features to do image retrieval. Texture classification and segmentation image processing area is a hot research field of enduring, texture feature extraction and segmentation texture classification as a priority, and has been the focus of attention, all kinds of texture feature extraction method are endless.

Local Binary Patterns is a gray within the scope of the texture description way, it from a different texture Local neighbors in the definition of derivatives. This paper realized the constant based Local Binary Patterns and rotation invariant of Local Binary Patterns two texture feature extraction method. Through the LBP texture map generating gray-level histogram, calculation of gray histogram Euclidean distance between to complete than image retrieval. This paper using vc + + 6.0 environment MFC project launch OpenCV image processing function library design the retrieval system based on texture feature LBP image retrieval. In (the California institute of technology 256 kinds of image database) and (Queensland university of classification brodatz natural texture images library) test and the results are analyzed and discussed. keyword: CBIR, LBP feature extraction, image recognition

目录

摘要................................................... I ABSTRACT ............................................. II 1 绪论.. (1)

1.1 研究背景 (1)

1.2 基于内容的图像检索 (1)

1.2.1 基于内容的图像检索概述 (1)

1.2.2 基于内容的图像检索体系结构 (2)

1.2.3 基于内容的图像检索的特点 (4)

1.2.4 基于内容的图像检索性能评价 (5)

1.3 图像检索的国内外研究现状......... 错误!未定义书签。

1.4 图像检索的优缺点级展望 (8)

1.5 本论文结构 (9)

2 基于纹理的图像检索 (9)

2.1 基于纹理的图像检索 (9)

2.2.1 发展与现状 (9)

2.2.2 纹理的定义 (11)

2.2 局域二值模式 (12)

2.3 基本LBP (13)

2.4 旋转不变LBP (14)