• DocumentCode
    3494433
  • Title

    Minimum Spanning Tree and Color Image Segmentation

  • Author

    Zhang, Xue-xi ; Yang, Yi-Min

  • Author_Institution
    Guangdong Univ. of Technol., Guangzhou
  • fYear
    2008
  • fDate
    6-8 April 2008
  • Firstpage
    900
  • Lastpage
    904
  • Abstract
    Image segmentation based on graph theory is mainly used for gray image now, and thresholding of segmentation should be predefined. Combining with maximum between -and- within -class in statistics theory, this paper suggests an unsupervised method for color image segmentation. The image is mapped into an weighted undirected graph, the pixels are considered as nodes, and minimum spanning tree is constructed by Kruskal algorithm .The best thresholding is obtained by maximum objective function to realize unsupervised segmentation. Experiment results show that the new algorithm ensures the color image segmentation excellent disturbance attenuation performance and better separability.
  • Keywords
    image colour analysis; image segmentation; statistical analysis; trees (mathematics); Kruskal algorithm; color image segmentation; graph theory; gray image; image thresholding; maximum objective function; minimum spanning tree; statistics theory; weighted undirected graph; Automation; Clustering algorithms; Clustering methods; Color; Educational institutions; Graph theory; Image segmentation; Pixel; Statistics; Tree graphs;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Networking, Sensing and Control, 2008. ICNSC 2008. IEEE International Conference on
  • Conference_Location
    Sanya
  • Print_ISBN
    978-1-4244-1685-1
  • Electronic_ISBN
    978-1-4244-1686-8
  • Type

    conf

  • DOI
    10.1109/ICNSC.2008.4525344
  • Filename
    4525344