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The calibration of a laser profiling system for seafloor micro-topography measurements

  • Loeffler, Kathryn R. (Applied Research Laboratories, The University of Texas at Austin) ;
  • Chotiros, Nicholas P. (Applied Research Laboratories, The University of Texas at Austin)
  • Received : 2011.03.14
  • Accepted : 2011.07.14
  • Published : 2011.09.25

Abstract

A method for calibrating a laser profiling system for seafloor micro-topography measurements is described. The system consists of a digital camera and an arrangement of six red lasers that are mounted as a unit on a remotely operated vehicle (ROV). The lasers project as parallel planes onto the seafloor, creating profiles of the local topography that are interpreted from the digital camera image. The goal of the calibration was to determine the plane equations for the six lasers relative to the camera. This was accomplished in two stages. First, distortions in the digital image were corrected using an interpolation method based on a virtual pinhole camera model. Then, the laser planes were determined according to their intersections with a calibration target. The position and orientation of the target were obtained by a registration process. The selection of the target shape and size was found to be critical to a successful calibration at sea, due to the limitations in the manoeuvrability of the ROV.

Keywords

References

  1. Bodenmann, A., Thornton, B., Ura, T., Sangekar, M.N., Nakatani, T. and Sakamaki, T. (2010), "Pixel based mapping using a sheet laser and camera for generation of coloured 3D seafloor reconstructions", Proceedings of the Oceans, Sydney, Australia, May.
  2. Chotiros, N.P., Isakson, M.J., Piper, J.N. and Zampolli, M. (2007), "Seafloor roughness measurement from a ROV", Proceedings of the Proc. International Symposium on Underwater Technology, Tokyo, Japan, April.
  3. Cumani, A. and Guiducci, A. (1995), "Geometric camera calibration: the virtual camera approach", IEEE T. Consum. Electr., 8(6), 375-384.
  4. Gupta, M., Agrawal, A., Veeraraghavan, A. and Narashimhan, S.G. (2011), "Structured light 3D scanning in the presence of global illumination", Proceedings of the Proc. 24th IEEE Conference on Computer Vision and Pattern Recognition, Colorado Springs, USA, June.
  5. Jaffe, J.S. (2005), "Performance bounds on synchronous laser line scan systems", Proceedings of the Oceans05 Europe, Brest, France, June.
  6. Kondo, H., Maki, T., Ura, T., Nose, Y., Sakamaki, T. and Inaishu, M. (2004), "Relative navigation of a autonomous underwater vehicle using a light-section profile system", Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, Sendai, Japan, 28 September - 2 October.
  7. Lyons, A.P., Fox, W.L.J., Hasiotis, T. and Pouliquen, E. (2002), "Characterization of the two-dimensional roughness of wave-rippled sea floors using digital photogrammetry", IEEE J. Oceanic Eng., 27(3), 515-524. https://doi.org/10.1109/JOE.2002.1040935
  8. Quan, X. and Fry, E.S. (1995), "Empirical equation for the index of refraction of seawater", Appl. Optics, 34(18), 3477-3480. https://doi.org/10.1364/AO.34.003477
  9. Salvi, J., Pages, J. and Batlle, J. (2004), "Pattern codification strategies in structured light systems", Pattern Recog., 37(4), 827-849. https://doi.org/10.1016/j.patcog.2003.10.002
  10. Sangekar, M.N., Thornton, B., Nakatani, T. and Ura, T. (2010), "Development of a landing algorithm for autonomous underwater vehicles using laser profiling", Proceedings of the Oceans, Sydney, Australia, May.
  11. Tsai, R.Y. (1987), "A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses", IEEE T. Robot. Auto., 3(4), 323-344. https://doi.org/10.1109/JRA.1987.1087109
  12. Varghese, S.M. and Isakson, M.J. (2005), "The calibration of a laser light line scan method for determining local interface roughness of the ocean floor", IEEE J. Oceanic Eng., 30(2), 463-467. https://doi.org/10.1109/JOE.2004.837140
  13. Wang, C.C. and Cheng, M.S. (2007), "Nonmetric camera calibration for underwater laser scanning system", IEEE J. Oceanic Eng., 32(2), 383-399. https://doi.org/10.1109/JOE.2006.880391
  14. Wang, C.C. and Tang, D. (2009), "Seafloor roughness measured by a laser line scanner and a conductivity probe", IEEE J. Oceanic Eng., 34(4), 459-465. https://doi.org/10.1109/JOE.2009.2026986
  15. Wang, C.C., Hefner, B.T. and Tang, D. (2009), "Evaluation of laser scanning and stereo photography roughness measurement systems using a realistic model seabed surface", IEEE J. Oceanic Eng., 34(4), 466-475. https://doi.org/10.1109/JOE.2009.2015162
  16. Weng, J., Cohen, P. and Herniou, M. (1992), "Camera calibration with distortion models and accuracy evaluation", IEEE T. Pattern Anal., 14(10), 965-980. https://doi.org/10.1109/34.159901
  17. Yu, W. (2003), "An embedded camera lens distortion correction method for mobile computing applications", IEEE T. Consum. Electr., 49(4), 894-901. https://doi.org/10.1109/TCE.2003.1261171