• DocumentCode
    2844546
  • Title

    Performance Assessment of a Mathematical Morphology Ship Detection Algorithm for SAR Images through Comparison with AIS Data

  • Author

    Grasso, R. ; Mirra, S. ; Baldacci, A. ; Horstmann, J. ; Coffin, M. ; Jarvis, M.

  • Author_Institution
    NATO Undersea Res. Centre, La Spezia, Italy
  • fYear
    2009
  • fDate
    Nov. 30 2009-Dec. 2 2009
  • Firstpage
    602
  • Lastpage
    607
  • Abstract
    This paper describes a procedure to evaluate the performance of ship detection algorithms for synthetic aperture radar (SAR) using real SAR images and automatic identification system (AIS) data as ground truth. Accurate AIS-SAR data association is achieved by correcting the AIS data for the SAR induced position errors by exploiting SAR acquisition parameters and vessel state information (speed and course) provided by AIS tracks. The methodology has been tested on a ship detection algorithm based on mathematical morphology which is described in this paper. The evaluation has been carried out on a RADARSAT-2 data set including images at different acquisition modes which was collected in the Mediterranean Sea. Estimates for the detection and the false alarm probability, and the contact position error are provided.
  • Keywords
    marine engineering; mathematical morphology; object detection; radar imaging; ships; synthetic aperture radar; AIS data; Mediterranean Sea; RADARSAT-2; SAR images; automatic identification system; mathematical morphology ship detection algorithm; performance assessment; synthetic aperture radar; Detection algorithms; Detectors; Error correction; Intelligent systems; Marine vehicles; Morphology; Radar detection; Radar tracking; Synthetic aperture radar; Synthetic aperture sonar;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Systems Design and Applications, 2009. ISDA '09. Ninth International Conference on
  • Conference_Location
    Pisa
  • Print_ISBN
    978-1-4244-4735-0
  • Electronic_ISBN
    978-0-7695-3872-3
  • Type

    conf

  • DOI
    10.1109/ISDA.2009.99
  • Filename
    5365001