• DocumentCode
    1740790
  • Title

    Color segmentation and figure-ground segregation of natural images

  • Author

    Wong, Swee-Seong ; Leow, Wee Kheng

  • Author_Institution
    Sch. of Comput., Nat. Univ. of Singapore, Singapore
  • Volume
    2
  • fYear
    2000
  • fDate
    10-13 Sept. 2000
  • Firstpage
    120
  • Abstract
    To recognize the objects in an image and to understand the image content, a computer system has to first separate the foreground objects from the background. Image segmentation and figure-ground segregation are, therefore, essential for computer image understanding. This paper describes a system called OLAG (Object-LAyer Grouping) for image segmentation and figure-ground segregation. OLAG consists of several incremental refinement steps which use colour and other visual cues such as size and compactness for grouping the image pixels. It produces, as an end result, a set of layers each containing an object or object part. Figure and ground relationships among the objects are inferred, giving their relative depths. It is shown that interesting and useful segmentation results can be obtained from the system.
  • Keywords
    image colour analysis; image segmentation; object recognition; OLAG system; color segmentation; computer image understanding; figure-ground segregation; foreground objects; image pixels grouping; image segmentation; incremental refinement steps; natural images; object recognition; object-layer grouping; Colored noise; Computer vision; Drives; Humans; Image recognition; Image segmentation; Mathematical model; Merging; Neural networks; Pixel;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing, 2000. Proceedings. 2000 International Conference on
  • Conference_Location
    Vancouver, BC, Canada
  • ISSN
    1522-4880
  • Print_ISBN
    0-7803-6297-7
  • Type

    conf

  • DOI
    10.1109/ICIP.2000.899242
  • Filename
    899242