彩色图像分割

彩色图像分割

论文摘要

在图像处理和计算机视觉里,图像分割是一个十分基础而且很重要的部分,决定了最终分析结果的好坏。本论文关于图像分割主要做了三方面的工作:1)学习和总结图像分割算法;2)设计一个图像分割工具包;3)提出一个新的分割算法。首先回顾了一下经典的分割算法,包括灰度图像分割算法和彩色图像分割算法,同时也介绍了一下常用的颜色空间。接着我们详细介绍了图像分割工具包的设计,工具包由两大部分组成:全自动分割和有监督分割。在全自动分割里,又分成两个步骤:粗分步和调整步。有时粗分步可能就已经满足要求,而且分成两步可以加快分割的速度。在粗分步里,Watershed和Mean Shift算法被采用,通常会有过分割现象。所以在第二步里,Graph Cut和k-means被用来修正上一步的过分割结果。在有监督分割这部分里:两种最基本的分割方法被采用:基于边界和基于区域的分割方法。在基于边界分割方法中,用动态规划来寻找图像里的真边界。在基于区域分割方法中,将分割问题简化为一个二次函数优化问题。同时我们提出了一种新的分割算法,该算法结合了边界信息和区域信息,并且得到的是解析解。最后该算法还有将用户输入的信息扩散传播到没有定义的区域的能力,使其产生的结果更合理。实验结果证明我们的新算法比前面介绍的分割算法更稳定更合理。

论文目录

  • 摘要
  • ABSTRACT
  • ACKNOWLEDGEMENTS
  • CHAPTER 1 INTRODUCTION
  • 1.1 Background
  • 1.2 Image Segmentation Survey
  • 1.3 Goal and Objectives
  • 1.4 Thesis Overview
  • CHAPTER 2 COLOR FEATURE
  • 2.1 Introduction
  • 2.2 Linear Transformation
  • 2.3 Nonlinear Transformation
  • 2.4 Summary
  • CHAPTER 3 IMAGE SEGMENTATION METHODS
  • 3.1 Introduction
  • 3.2 Histogram thresholding and color space clustering
  • 3.3 Region-based Approaches
  • 3.4 Edge detection
  • 3.5 Fuzzy techniques
  • 3.6 Physics based approaches
  • 3.7 Neural networks approaches
  • 3.8 Summary
  • CHAPTER 4 AUTOMATIC SEGMENTATION
  • 4.1 Introduction
  • 4.2 Coarse Step
  • 4.2 Finer Step
  • 4.3 Summary
  • CHAPTER 5 INTERACTIVE SEGMENTATION
  • 5.1 Introduction
  • 5.2 Edge-based Method
  • 5.3 Region-based Method
  • 5.4 A New Algorithm
  • 5.5 Summary
  • CHAPTER 6 CONCLUSION AND FUTURE WORK
  • 6.1 Conclusion
  • 6.2 Future Work
  • REFERENCES
  • APPENDIX
  • PUBLICATION
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    彩色图像分割
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