• DocumentCode
    3390268
  • Title

    Automatic contact detection in side-scan sonar data

  • Author

    Quintal, Rebecca T. ; Kiernan, John E. ; Shannon, Julia ; Dysart, Paul S.

  • Author_Institution
    Marine Sci. & Technol. Div., Sci. Applic. Int. Corp., Newport, RI, USA
  • fYear
    2010
  • fDate
    8-10 Nov. 2010
  • Firstpage
    270
  • Lastpage
    275
  • Abstract
    Side-scan sonar is a proven tool for detection of underwater objects, particularly those objects that project above the seafloor. Rapid assessment of side-scan imagery for object detection is critical for port security needs. However, current side-scan data processing techniques are largely manual, highly time-consuming, and prone to operator error. Availability of well-trained analysts is also a challenge. This article describes a research and development effort at Science Applications International Corporation to automate side-scan sonar contact detection for safety of navigation surveys. Included in the development effort are innovative image processing and machine learning techniques designed to reduce the number of false alarms. These automated techniques are directly applicable to port security operations.
  • Keywords
    object detection; sonar imaging; automatic contact detection; innovative image processing; machine learning technique; navigation survey; object detection; operator error; port security needs; port security operation; rapid assessment; side-scan data processing technique; side-scan imagery; side-scan sonar data; well-trained analyst; Artificial neural networks; Book reviews; Clutter; Software; Sonar detection; Sonar navigation; automatic contact detection; automatic detection; neural networks; side-scan sonar; sonar imagery;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Technologies for Homeland Security (HST), 2010 IEEE International Conference on
  • Conference_Location
    Waltham, MA
  • Print_ISBN
    978-1-4244-6047-2
  • Type

    conf

  • DOI
    10.1109/THS.2010.5655043
  • Filename
    5655043