• Title of article

    Image registration for the underwater inspection using the maximum a posteriori technique

  • Author/Authors

    Guo، Jenhwa نويسنده , , Cheng، Sheng-Wen نويسنده , , Ying، Cheng-Yang نويسنده , , Liu، Te-Chih نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2003
  • Pages
    -54
  • From page
    55
  • To page
    0
  • Abstract
    This work describes an image registration method for underwater inspection tasks. A remotely operated vehicle equipped with a video camera and a scanning sonar is used as the testbed vehicle. Each image of the underwater scene is saved along with the video cameraʹs position and orientation. The images are then combined to create a large composite picture of the underwater structure being inspected. This method is based upon a maximum a posteriori estimation technique and provides smooth and robust estimates of image shifts. Our results demonstrate the feasibility of this highly promising underwater inspection procedure.
  • Keywords
    neural-network modularity , two-hidden-layer feedforward networks (TLFNs) , Storage capacity , Learning capability
  • Journal title
    IEEE Journal of Oceanic Engineering
  • Serial Year
    2003
  • Journal title
    IEEE Journal of Oceanic Engineering
  • Record number

    78939