• DocumentCode
    1788191
  • Title

    Affiliation possibility map filtering for image segmentation improvement

  • Author

    Mozdren, Karel ; Sojka, Eduard ; Surkala, Milan ; Fusek, Radovan

  • Author_Institution
    FEECS, VrB-Tech. Univ. of Ostrava, Ostrava, Czech Republic
  • fYear
    2014
  • fDate
    14-17 Oct. 2014
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Image segmentation is an important task in computer vision. The task of image segmentation is to portion image into segments, thus provide more meaningful information of the image contents. Many methods have been developed for numerous application. The common problems of most of the segmentation techniques are scattered segmentation lines, too much details, small or thin segments, and noisy segmentation. In this paper, we propose a novel method for image segmentation improvement. We present state-of-the-art methods, our proposed method and experiments, showing performance over segmentations from classical image segmentation methods and also over segmentations from background subtraction methods.
  • Keywords
    computer vision; image filtering; image segmentation; affiliation possibility map filtering; background subtraction method; computer vision; image segmentation; Computer vision; Educational institutions; Equations; Image edge detection; Image segmentation; Noise; Noise measurement; affiliation map; background subtraction; filter; image segmentation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing Theory, Tools and Applications (IPTA), 2014 4th International Conference on
  • Conference_Location
    Paris
  • Print_ISBN
    978-1-4799-6462-8
  • Type

    conf

  • DOI
    10.1109/IPTA.2014.7001933
  • Filename
    7001933