• DocumentCode
    2686868
  • Title

    Detecting Curved Underground Tunnels using Partial Radon Transforms

  • Author

    Gurbuz, A.C. ; McClellan, James H. ; Scott, Waymond R.

  • Author_Institution
    Georgia Inst. of Technol., Atlanta, GA, USA
  • Volume
    1
  • fYear
    2007
  • fDate
    15-20 April 2007
  • Abstract
    The Radon transform (RT) is known to be effective in detecting lines in noisy images, but it is not capable of detecting curves unless the curve parametrization is given. In this paper, partial Radon transforms (PRT) are investigated as a tool to detect curved features such as underground tunnels in ground penetrating radar (GPR) images. The algorithm applies the Radon transform to small batches of the total image and updates the tunnel position parameters as new batches are used. Missing data, as well as finding the ends of tunnels can be handled with the proposed algorithm. Performance analysis is given for various signal-to-noise ratios (SNR) and batch sizes. The effect of the curvature level on the performance is also analyzed.
  • Keywords
    Radon transforms; object detection; GPR images; curve parametrization; curved underground tunnel detection; ground penetrating radar; partial Radon transforms; signal-to-noise ratios; Algorithm design and analysis; Buried object detection; Computer vision; Ground penetrating radar; Performance analysis; Radar detection; Reflection; Shape; Signal analysis; Signal to noise ratio; Radon transforms; curve estimation; partial Radon Transform; tunnel detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing, 2007. ICASSP 2007. IEEE International Conference on
  • Conference_Location
    Honolulu, HI
  • ISSN
    1520-6149
  • Print_ISBN
    1-4244-0727-3
  • Type

    conf

  • DOI
    10.1109/ICASSP.2007.365965
  • Filename
    4217137