• DocumentCode
    2156722
  • Title

    Underwater image mosaicing using maximum a posteriori image registration

  • Author

    Guo, J. ; Cheng, S.W. ; Yinn, J.Y.

  • Author_Institution
    Dept. of Naval Archit. & Ocean Eng., Nat. Taiwan Univ., Taipei, Taiwan
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    393
  • Lastpage
    398
  • Abstract
    An underwater remotely operated vehicle (ROV) was developed to allow inspection process without the need for human divers to enter the water. The ROV has a video camera, a Doppler navigation sonar and gyroscope-based orientation sensor. Each image of the underwater scene is saved along with the video camera´s instantaneous position and orientation. The images are then patched together into a large composite picture of the structure. The method, which is based on the maximum a posteriori estimation technique, combines the least-mean-squared-error estimator and Kalman Filter. It provides smooth and robust image shift estimation. This method has been tested and shown as a practical and potentially useful underwater inspection tool
  • Keywords
    Kalman filters; automatic optical inspection; computer vision; image registration; least mean squares methods; maximum likelihood estimation; underwater vehicles; Kalman Filter; composite picture; image registration; image shift estimation; least-mean-squared-error estimator; maximum a posteriori estimation; remotely operated vehicle; underwater image mosaicing; underwater inspection; underwater scene; video camera; Cameras; Gyroscopes; Humans; Inspection; Layout; Maximum a posteriori estimation; Remotely operated vehicles; Robustness; Sonar navigation; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Underwater Technology, 2000. UT 00. Proceedings of the 2000 International Symposium on
  • Conference_Location
    Tokyo
  • Print_ISBN
    0-7803-6378-7
  • Type

    conf

  • DOI
    10.1109/UT.2000.852577
  • Filename
    852577