图像分割算法
合集下载
相关主题
- 1、下载文档前请自行甄别文档内容的完整性，平台不提供额外的编辑、内容补充、找答案等附加服务。
- 2、"仅部分预览"的文档,不可在线预览部分如存在完整性等问题,可反馈申请退款(可完整预览的文档不适用该条件!)。
- 3、如文档侵犯您的权益，请联系客服反馈,我们会尽快为您处理(人工客服工作时间：9:00-18:30)。
安徽工程大学毕业设计（论文）
图像分割算法研究 摘 要
图像分割是指把图像分解成各具特性的区域并提取出感兴趣目标的技术和过程， 它 是计算机视觉领域的一个重要而且基本的问题， 分割结果的好坏将直接影响到视觉系统 的性能。因此从原理、应用和应用效果的评估上深入研究图像分割技术具有十分重要的 意义。本课题主要介绍了图像分割的基本知识，研究了图像分割的两大类算法，即基于 边缘检测的方法和基于区域生成的方法。采用 MATLAB 仿真了所有分割过程，得到了 比较理想的分割结果，并分析了各个算法的优点和不足之处,以及适用于何种图像。 基于边缘检测方法种类繁多，主要介绍基于 EDGE 函数、检测微小结构、四叉树分 解和阈值分割的方法实现对图像的边缘检测及提取。 而基于区域的图像分割方法主要包 括区域生长法和分裂-合并分割方法。通过多次的实验过后，总结出一般的图像分割处 理可以用 EDGE 函数。而特定的图像应用阈值分割、检测微小结构和四叉树分解比较简 单。 虽然近年来人们在图像分割方面做了大量的研究工作，但由于尚无通用的分割理 论，因此现已提出的分割算法大都是针对具体问题的，并没有一种适合于所有图像的通 用的分割算法，有待于进一步解决。 关键字：图像分割；边缘检测；区域生成；阈值分割
I
朱北侠：图像分割算法研究
Research of image segmentation algorithm
Biblioteka BaiduAbstract
Image Segmentation is the technique and the process to segment an image into different sub-mages with different characters and to extract the interested objects from the image. It is an important and basic procedure in the field of computer vision, the quality of image segmentation directly affects the performance of vision system. Therefore, from the theory, application and evaluation of application effect of depth of image segmentation is of great significance. This issue introduces the basics of image segmentation, image segmentation of the two major algorithms have been done, that is based on edge detection method and the method based on regional produce. Segmentation process is simulated and the results have shown perfect. Advantages and disadvantages of each algorithm are discussed at the end of the paper, and to apply to each image. Edge detection method based on a wide range of EDGE-based functions are introduced, the detection of minimal structure, quadtree decomposition and threshold segmentation method to realize the edge detection and extraction. The region-based image segmentation methods include region growing and division - combined segmentation. Through many experiments later, summed up the general image segmentation can be EDGE function. The specific application of image segmentation, the detection of minimal structure and quadtree decomposition is simple. Although a lot of image segmentation research has been done in recent years, but there is not general theory of segmentation, the proposed segmentation algorithm has been mostly issue-specific, and there is not a suitable segmentation algorithm for all common image, remains to be resolved. Keywords: Image segmentation; Edge detection; Region segmentation; Threshold segmentation
II
安徽工程大学毕业设计（论文）
目
录
引 言 ............................................................................................................................... - 1 第1章 绪 论 ................................................................................................................. - 2 1.1 基本概念 ................................................................................................................. - 2 1.1.1 图像和数字图像 ........................................................................................... - 2 1.1.2 图像分割的定义 ........................................................................................... - 2 1.2 图像分割研究的发展和意义 ................................................................................. - 3 1.2.1 图像技术的发展 ........................................................................................... - 3 1.2.2 图像分割的研究意义 ................................................................................... - 3 1.2.1 图像分割的研究现状及发展趋势 ............................................................... - 4 1.3 论文的主要工作 ..................................................................................................... - 5 第 2 章 图像分割技术的基本算法 ..................................................................................... - 6 2.1 阈值分割算法 ......................................................................................................... - 6 2.1.1 直方图阈值的双峰法 ................................................................................... - 6 2.1.2 迭代法 ........................................................................................................... - 8 2.1.3 大律法 ......................................................................................................... - 10 2.2 边缘检测算法研究 ............................................................................................... - 11 2.2.1 拉普拉斯高斯算子 ..................................................................................... - 12 2.2.2 Canny算子 .................................................................................................... - 14 2.2.3 一阶微分算子 ............................................................................................. - 16 2.3 区域分割算法研究 ............................................................................................... - 19 2.3.1 区域生长的原理和步骤 ............................................................................. - 19 2.3.2 生长准则和过程 ......................................................................................... - 20 2.3.3 分裂合并 ..................................................................................................... - 22 第 3 章 图像分割在车牌号系统识别中应用的介绍 ....................................................... - 25 3.1 车牌图像二值化算法 ........................................................................................... - 25 3.1.1 阈值的选取 ................................................................................................. - 26 3.1.2 试验及试验结果 ......................................................................................... - 27 3.2 车牌字符分割基本方法 ....................................................................................... - 27 3.2.1 投影分割 ..................................................................................................... - 28 3.2.2 基于聚类分析的字符分割 .......................................................................... - 28 3.2.3 基于模板匹配的字符分割 .......................................................................... - 28 3.2.4 直方图合并和分裂的处理 ......................................................................... - 29 总结与展望 ......................................................................................................................... - 30 致 谢 ............................................................................................................................. - 31 参考文献 ............................................................................................................................. - 32 附录A 英语引文及翻译 .................................................................................................... - 33 附录B 主要参考文献的题录及摘要 ................................................................................ - 37 -
图像分割算法研究 摘 要
图像分割是指把图像分解成各具特性的区域并提取出感兴趣目标的技术和过程， 它 是计算机视觉领域的一个重要而且基本的问题， 分割结果的好坏将直接影响到视觉系统 的性能。因此从原理、应用和应用效果的评估上深入研究图像分割技术具有十分重要的 意义。本课题主要介绍了图像分割的基本知识，研究了图像分割的两大类算法，即基于 边缘检测的方法和基于区域生成的方法。采用 MATLAB 仿真了所有分割过程，得到了 比较理想的分割结果，并分析了各个算法的优点和不足之处,以及适用于何种图像。 基于边缘检测方法种类繁多，主要介绍基于 EDGE 函数、检测微小结构、四叉树分 解和阈值分割的方法实现对图像的边缘检测及提取。 而基于区域的图像分割方法主要包 括区域生长法和分裂-合并分割方法。通过多次的实验过后，总结出一般的图像分割处 理可以用 EDGE 函数。而特定的图像应用阈值分割、检测微小结构和四叉树分解比较简 单。 虽然近年来人们在图像分割方面做了大量的研究工作，但由于尚无通用的分割理 论，因此现已提出的分割算法大都是针对具体问题的，并没有一种适合于所有图像的通 用的分割算法，有待于进一步解决。 关键字：图像分割；边缘检测；区域生成；阈值分割
I
朱北侠：图像分割算法研究
Research of image segmentation algorithm
Biblioteka BaiduAbstract
Image Segmentation is the technique and the process to segment an image into different sub-mages with different characters and to extract the interested objects from the image. It is an important and basic procedure in the field of computer vision, the quality of image segmentation directly affects the performance of vision system. Therefore, from the theory, application and evaluation of application effect of depth of image segmentation is of great significance. This issue introduces the basics of image segmentation, image segmentation of the two major algorithms have been done, that is based on edge detection method and the method based on regional produce. Segmentation process is simulated and the results have shown perfect. Advantages and disadvantages of each algorithm are discussed at the end of the paper, and to apply to each image. Edge detection method based on a wide range of EDGE-based functions are introduced, the detection of minimal structure, quadtree decomposition and threshold segmentation method to realize the edge detection and extraction. The region-based image segmentation methods include region growing and division - combined segmentation. Through many experiments later, summed up the general image segmentation can be EDGE function. The specific application of image segmentation, the detection of minimal structure and quadtree decomposition is simple. Although a lot of image segmentation research has been done in recent years, but there is not general theory of segmentation, the proposed segmentation algorithm has been mostly issue-specific, and there is not a suitable segmentation algorithm for all common image, remains to be resolved. Keywords: Image segmentation; Edge detection; Region segmentation; Threshold segmentation
II
安徽工程大学毕业设计（论文）
目
录
引 言 ............................................................................................................................... - 1 第1章 绪 论 ................................................................................................................. - 2 1.1 基本概念 ................................................................................................................. - 2 1.1.1 图像和数字图像 ........................................................................................... - 2 1.1.2 图像分割的定义 ........................................................................................... - 2 1.2 图像分割研究的发展和意义 ................................................................................. - 3 1.2.1 图像技术的发展 ........................................................................................... - 3 1.2.2 图像分割的研究意义 ................................................................................... - 3 1.2.1 图像分割的研究现状及发展趋势 ............................................................... - 4 1.3 论文的主要工作 ..................................................................................................... - 5 第 2 章 图像分割技术的基本算法 ..................................................................................... - 6 2.1 阈值分割算法 ......................................................................................................... - 6 2.1.1 直方图阈值的双峰法 ................................................................................... - 6 2.1.2 迭代法 ........................................................................................................... - 8 2.1.3 大律法 ......................................................................................................... - 10 2.2 边缘检测算法研究 ............................................................................................... - 11 2.2.1 拉普拉斯高斯算子 ..................................................................................... - 12 2.2.2 Canny算子 .................................................................................................... - 14 2.2.3 一阶微分算子 ............................................................................................. - 16 2.3 区域分割算法研究 ............................................................................................... - 19 2.3.1 区域生长的原理和步骤 ............................................................................. - 19 2.3.2 生长准则和过程 ......................................................................................... - 20 2.3.3 分裂合并 ..................................................................................................... - 22 第 3 章 图像分割在车牌号系统识别中应用的介绍 ....................................................... - 25 3.1 车牌图像二值化算法 ........................................................................................... - 25 3.1.1 阈值的选取 ................................................................................................. - 26 3.1.2 试验及试验结果 ......................................................................................... - 27 3.2 车牌字符分割基本方法 ....................................................................................... - 27 3.2.1 投影分割 ..................................................................................................... - 28 3.2.2 基于聚类分析的字符分割 .......................................................................... - 28 3.2.3 基于模板匹配的字符分割 .......................................................................... - 28 3.2.4 直方图合并和分裂的处理 ......................................................................... - 29 总结与展望 ......................................................................................................................... - 30 致 谢 ............................................................................................................................. - 31 参考文献 ............................................................................................................................. - 32 附录A 英语引文及翻译 .................................................................................................... - 33 附录B 主要参考文献的题录及摘要 ................................................................................ - 37 -