• DocumentCode
    3402424
  • Title

    An improved GVF snake model and its application to linear feature extraction from SAR images

  • Author

    Deng, Xin-Ping ; He, Chu ; Sun, Hong

  • Author_Institution
    Signal Process. Lab., Wuhan Univ., Wuhan, China
  • fYear
    2010
  • fDate
    24-28 Oct. 2010
  • Firstpage
    2063
  • Lastpage
    2066
  • Abstract
    In this paper, an improved GVF snake model that allows controllable snakes is proposed. Two kinds of extern constraint forces are exploited in the model. The first one can pin specified points on the snake and determine the basic shape of a snake. The second one avoids generating ears during curve evolution. It ensures that the curves are smooth and won´t grow in a wrong direction. The improved snakes are employed to close gaps in linear feature extraction since they can fixes the connection points during the deformation and provide smooth linking curves rather than straight lines. The experimental results of ridge (and ravine) extraction and road extraction from real SAR images increase the correctness and quality of extracted results.
  • Keywords
    feature extraction; gradient methods; radar imaging; synthetic aperture radar; GVF snake model; SAR image; curve evolution; gradient vector flow; linear feature extraction; ridge extraction; road extraction; smooth linking curve; Detectors; Ear; Feature extraction; Image edge detection; Joining processes; Pixel; Roads; gradient vector flow (GVF); linear feature extraction; snake; sythetic apeture radar (SAR);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing (ICSP), 2010 IEEE 10th International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-5897-4
  • Type

    conf

  • DOI
    10.1109/ICOSP.2010.5655726
  • Filename
    5655726