• DocumentCode
    2640810
  • Title

    Image Segmentation Based on Inhomogeneous Markov Random Field and Dirichlet Process Mixture

  • Author

    Chen, Xiaobo ; Cheng, Xianyi ; Liang, Jun

  • Author_Institution
    Sch. of Comput. Sci. & Telecommun. Eng., Jiangsu Univ., Jiangsu
  • fYear
    2008
  • fDate
    18-20 June 2008
  • Firstpage
    540
  • Lastpage
    540
  • Abstract
    A novel graphical model based on inhomogeneous Markov random field and Dirichlet process mixture is proposed to address the problems encountered by hidden Markov random field. It incorporates the local and global scale information. A sampling method is also devised based on Gibbs sampler. The model is investigated in the context of image segmentation and the performance is evaluated.
  • Keywords
    Markov processes; image sampling; image segmentation; Dirichlet process mixture; Gibbs sampler; global scale information; hidden Markov random field; image segmentation; inhomogeneous Markov random field mixture; Bayesian methods; Computer science; Computer vision; Context modeling; Graphical models; Hidden Markov models; Image segmentation; Markov random fields; Pixel; Sampling methods;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Innovative Computing Information and Control, 2008. ICICIC '08. 3rd International Conference on
  • Conference_Location
    Dalian, Liaoning
  • Print_ISBN
    978-0-7695-3161-8
  • Electronic_ISBN
    978-0-7695-3161-8
  • Type

    conf

  • DOI
    10.1109/ICICIC.2008.311
  • Filename
    4603729
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2640810