• DocumentCode
    1791334
  • Title

    Fast joint optimization in MRF-MAP-based segmentation of color images

  • Author

    Zhao Qiyang ; Li Weibo

  • Author_Institution
    State Key Lab. of Software, Beihang Univ., Beijing, China
  • fYear
    2014
  • fDate
    14-16 Oct. 2014
  • Firstpage
    387
  • Lastpage
    391
  • Abstract
    Color image segmentation is an important topic in the image processing field. In most segmentation methods based on MRF-MAP, the segmentation quality is far behind requirement due to the absence of appearance models, and it is often suffering from the low computational efficiency of iterated calculations. To address these problems, the paper proposes a new segmentation method for color images based on MRF-MAP, which is solved approximately in an efficient non-iterated way, with the help of a slightly tuned Lanczos eigensolver. The experiments demonstrate that the new method achieves competitive performance compared with the groundtruths or other state-of-the-art methods.
  • Keywords
    Markov processes; eigenvalues and eigenfunctions; image colour analysis; image segmentation; maximum likelihood estimation; optimisation; Lanczos eigensolver; MRF-MAP; color image segmentation method; fast joint optimization; image processing; iterated calculation; maximum a posteriori on Markov random field; segmentation quality; Approximation methods; Color; Computational modeling; Computer vision; Image color analysis; Image segmentation; Markov processes;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image and Signal Processing (CISP), 2014 7th International Congress on
  • Conference_Location
    Dalian
  • Type

    conf

  • DOI
    10.1109/CISP.2014.7003811
  • Filename
    7003811