• DocumentCode
    2923745
  • Title

    Improving the Graph-Based Image Segmentation Method

  • Author

    Zhang, Ming ; Alhajj, Reda

  • Author_Institution
    Dept. of Comput. Sci., Calgary Univ., Alta.
  • fYear
    2006
  • fDate
    Nov. 2006
  • Firstpage
    617
  • Lastpage
    624
  • Abstract
    Sensor devices are widely used for monitoring purposes. Image mining techniques are commonly employed to extract useful knowledge from the image sequences taken by sensor devices. Image segmentation is the first step of image mining. Due to the limited resources of the sensor devices, we need time and space efficient methods of image segmentation. In this paper, we propose an improvement to the graph-based image segmentation method already described in the literature and considered as the most effective method with satisfactory segmentation results. This is the preprocessing step of our online image mining approach. We contribute to the method by re-defining the internal difference used to define the property of the components and the threshold function, which is the key element to determine the size of the components. The conducted experiments demonstrate the efficiency and effectiveness of the adjusted method
  • Keywords
    data mining; graph theory; image segmentation; graph-based image segmentation; image mining; knowledge extraction; sensor devices; Computer science; Data mining; Image analysis; Image segmentation; Image sensors; Image sequences; Merging; Monitoring; Pixel; Size control; image mining; image segmentation; sensor devices;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Tools with Artificial Intelligence, 2006. ICTAI '06. 18th IEEE International Conference on
  • Conference_Location
    Arlington, VA
  • ISSN
    1082-3409
  • Print_ISBN
    0-7695-2728-0
  • Type

    conf

  • DOI
    10.1109/ICTAI.2006.66
  • Filename
    4031952