模板匹配定位研究与实现

文档编号:DZXX309  文档字数:8341,页数:15

摘要
 模板匹配是数字图像处理中的重要内容，它的作用是在原图像中找到于模板图像最相近的部分。
 本文对模板匹配进行学习和研究，主要介绍了一种快速的匹配算法——SSDA(Sequential Similarity Detection Algorithms)算法。SSDA算法是将模板在原图上平移比较，平移到最后找出相似度最大的一个部位，就是我们需要找的。在SSDA算法中用了三个不同形式的公式进行编程，通过对不同图像的处理，各个公式对图像处理的时间和精确度进行比较。
 在Microsoft Windows XP平台上Visual C++ 6.0开发环境下，采用上述方法编制了模板匹配的软件。实验证明，该软件对于尺寸不大的清晰图片基本能够正确定位，并进行识别，典型耗时为0～3秒钟。
 最后，本文探讨了SSDA算法的方法的优缺点，提出了进一步工作的方向。

 关键字：图像匹配  序列相似性  SSDA算法  图像模板  VC++　

Abstract  
 The template match is an important content in the digital picture processing; its function lies in finding the part which is closest to the template picture from the original map.
 The template match has been studied and researched in this paper, and the emphasis has been put on the SSDA (Sequential Similarity Detection Algorithms) algorithm, which is one kind of fast match algorithm. The SSDA algorithm is to translate and compare the template in the original map, to finally discover the spot which has most greatly similar. Three different forms formulas in the SSDA algorithm have been carried on the programming, and each formula carried on the comparison to the picture processing time and the precision.
  In the platform of Microsoft Windows XP and the development environment of Visual C++ 6.0, the software about the template match has been compiled using the above method. The experiment proved that, this software can correctly locate and recognize these kind of pictures which are not big in size but clear with the model time consuming at 0 ~3 seconds in usual.
 Finally, the good and bad points of the SSDA algorithm method have been discussed, and the further direction of research has been proposed in this paper.
 Key words: Picture match   Similar of sequence   SSDA algorithm   Picture template   VC++

目录
摘要 ii
Abstract ii
目录 iii
第一章 绪论 1
1.1、前言 1
1.2、课题背影 1
1.3、模板匹配的应用 2
1.4、研究现状 2
1.5、文本组织 3
第二章 系统开发工具简介 4
2.1、Visual C++ 6.0简介 4
2.2、Visual C++ 6.0的优点 4
2.3、Visual C++ 6.0 MFC类库 4
2.4、本章小节 5
第三章  模板匹配算法SSDA算法 6
3.1、SSDA的基本原理 6
3.2、SSDA的基本算法 6
3.3、SSDA的算法步骤与实现 6
3.4、SSDA三种算法 7
3.4.1、三种算法的共同优点 7
3.4.2、三种算法的不同之处 7
3.4.3、结果分析 8
3.4.4、三种算法的缺点 9
3.5、本章小节 9
第四章  总结与展望 9
4.1、总结 9
4.1.1、全文总结 9
4.2、存在的不足 10
4.2.2、自身的不足 10
4.1.3、项目的不足 10
4.2、展望 10
第五章　致谢 10
第六章　参考文献 12
附录1 13

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