• DocumentCode
    2233802
  • Title

    Image segmentation using watersheds guided by edge tracing

  • Author

    Ma, Lei ; Si, Jennie ; Abousleman, Glen P.

  • Author_Institution
    Dept. of Electr. Eng., Arizona State Univ., Tempe, AZ, USA
  • Volume
    3
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    372
  • Abstract
    We present two image segmentation algorithms. The proposed algorithms are the integrated watershed and adjacent region merging (IWARM) algorithm and the self-guided watershed and ARM (SGWARM) algorithm. Due to the integration of noise reduction and watersheds, IWARM saves up to 25 percent processing time over existing leading algorithms such as seeded region merging (SRM) algorithm and region adjacency graph (RAG) algorithm on a variety of test images. The IWARM algorithm also provides better segmentation accuracy over the two mentioned algorithms. SGWARM was developed to improve processing speed by eliminating any "out-of-interest" regions before they are provided to IWARM for further processing. Both algorithms have been tested extensively and are shown to provide excellent performance using aerial and MRI imagery
  • Keywords
    edge detection; gradient methods; image segmentation; interference suppression; MRI imagery; adjacent region merging; aerial imagery; edge extraction; edge tracing; fast gradient watershed; image segmentation; integrated watershed; noise reduction; region adjacency graph; regions of interest; seeded region merging; self-guided watershed; Image processing; Image segmentation; Information systems; Layout; Magnetic resonance imaging; Merging; Noise reduction; Pixel; Reluctance motors; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Info-tech and Info-net, 2001. Proceedings. ICII 2001 - Beijing. 2001 International Conferences on
  • Conference_Location
    Beijing
  • Print_ISBN
    0-7803-7010-4
  • Type

    conf

  • DOI
    10.1109/ICII.2001.983085
  • Filename
    983085