• DocumentCode
    2894540
  • Title

    On Improving Image Segmentation

  • Author

    Khan, Asmar A. ; Xydeas, Costas ; Ahmed, Hassan

  • Author_Institution
    Sch. of Comput. & Commun., Lancaster Univ., Lancaster, UK
  • fYear
    2011
  • fDate
    Nov. 28 2011-Dec. 1 2011
  • Firstpage
    213
  • Lastpage
    217
  • Abstract
    The proposed scheme is an approach which can be used to improve the performance of traditional image segmentation systems. The scheme is based on a framework that employs the output of an existing image segmentation process together with hierarchical clustering using an information theoretic similarity measure. Experimental results clearly show that when the scheme operates in conjunction with a state of the art image segmentation algorithm, it yields significantly superior performance over a wide spectrum of natural images. These results are based on informal subjective evaluation tests as well as on objective measurements obtained from processing the Berkeley BSDS 300 image dataset.
  • Keywords
    image segmentation; natural scenes; pattern clustering; visual databases; Berkeley BSDS 300 image dataset; hierarchical clustering; image processing; image segmentation algorithm; information theoretic similarity measures; natural images; Computer vision; Image edge detection; Image segmentation; Pattern recognition; Q measurement; System performance; Training;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal-Image Technology and Internet-Based Systems (SITIS), 2011 Seventh International Conference on
  • Conference_Location
    Dijon
  • Print_ISBN
    978-1-4673-0431-3
  • Type

    conf

  • DOI
    10.1109/SITIS.2011.48
  • Filename
    6120652