• DocumentCode
    142616
  • Title

    Ship detection in South African oceans using SAR, CFAR and a Haar-like feature classifier

  • Author

    Schwegmann, C.P. ; Kleynhans, W. ; Salmon, B.P.

  • Author_Institution
    Dept. of Electr., Electron. & Comput. Eng., Univ. of Pretoria, Pretoria, South Africa
  • fYear
    2014
  • fDate
    13-18 July 2014
  • Firstpage
    557
  • Lastpage
    560
  • Abstract
    Synthetic Aperture Radar images is a proven technology that can be used to detect ships at sea which have no active transponders (commonly referred to as dark targets). Various methods have been proposed that process SAR images to monitor these targets. In this paper, we propose a novel ship detection method for Advanced Synthetic Aperture Radar imagery that combines a Constant False Alarm Rate ship pre-screening method with a Haar-like feature cascade classifier. Experimental results indicate that this configuration provides a ship detection accuracy above 88% and half the False Alarm Rate of the traditional Constant False Alarm Rate method.
  • Keywords
    image classification; radar imaging; ships; synthetic aperture radar; CFAR; Haar-like feature cascade classifier; SAR; SAR images; South African oceans; advanced synthetic aperture radar imagery; constant false alarm rate ship prescreening method; ship detection accuracy; Accuracy; Feature extraction; Marine vehicles; Monitoring; Oceans; Sea measurements; Synthetic aperture radar;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International
  • Conference_Location
    Quebec City, QC
  • Type

    conf

  • DOI
    10.1109/IGARSS.2014.6946483
  • Filename
    6946483