计算机工程与应用 ›› 2006, Vol. 42 ›› Issue (20): 19-.

• 博士论坛 • 上一篇    下一篇

图像分割中MRF与DMN方法评述与比较

曹建农、王占宏

  

  1. 长安大学 地球科学与国土资源学院
  • 收稿日期:2006-02-17 修回日期:1900-01-01 出版日期:2006-07-11 发布日期:2006-07-11
  • 通讯作者: caojiannong caojiannong

Remark on Approaches of MRF or DMN and compare with them in Segmentation of Images

JianNong Cao,   

  1. 长安大学 地球科学与国土资源学院
  • Received:2006-02-17 Revised:1900-01-01 Online:2006-07-11 Published:2006-07-11
  • Contact: JianNong Cao

摘要: 摘 要:综述马尔科夫随机场(Markov Random Field,MRF)的研究和应用历史,着重讨论了图像分割中MRF的原理和应用。分析了可分解马尔科夫网(Decomposable Markov Networks,DMN)的一般方法以及DMN在图像分割问题中的应用。比较研究了MRF和DMN的区别和联系。

关键词: 马尔科夫随机场(MRF, 可分解马尔科夫网(DMN), 图论

Abstract: Abstract:The paper summarizes (Markov Random Field) MRF’ history of research and application. The principles and applications of MRF in segmentation of Images are discussed emphatically. It analyses common method of DMN (Decomposable Markov Networks), and its applications problem in segmentation of Images. It points out their differences and connections by comparing with MRF and DMN.

Key words: Markov Random Field (MRF), Decomposable Markov Networks (DMN), Graph Theory