Abstract
Control of the source and analysis of the polarization properties of the reflected light in a laser rangefinder based on triangulation offer a potential solution to the problem of distinguishing the primary laser stripe from unwanted inter-reflections caused by holes and concavities on metal surfaces. In this paper, the established polarization theory of first and subsequent inter-reflections from metallic surfaces is reviewed. This provides a point of comparison for ellipsometric measurements which verify the particular applicability of the microfacet surface model in our context. We demonstrate how a conventional laser rangefinder can be modified to discriminate between primary and secondary reflections. However, our experiments on third and subsequent reflections show that more complex models are required to provide complete resolution of the problem. Furthermore, error analysis demonstrates the requirement for very precise control of the source and receiving optoelectronics. We conclude by demonstrating the acquisition of a depth image with and without polarization optics and discuss the significance of our results for laser depth measurement.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.References
Besl, P.J. 1988. Active, optical range imaging sensors. Machine Vision and Applications, 1(2):127–152.
Born, M. and Wolf, E. 1993. Principles of Optics. Pergamon Press.
Bouguer, P. 1961. Gradation of Light (Traite d'optique sur la gradation de la lumiere). Toronto Press. English translation of the original posthumous publication in 1760.
Boult, T.E. and Wolff, L.B. 1991. Physically based edge labelling. In Proc. of IEEE Conf. on Computer Vision and Pattern Recognition, pp. 656–662.
Chen, H. and Wolff, L.B. 1998. Polarization phase-based method for material classification in computer vision. International Journal of Computer Vision, 28(1):73–83.
Clark, J., Trucco, E., and Wolff, L. 1997. Using light polarization in laser scanning. Image and Vision Computing, 15:107–117.
Clark, J., Zhang, G., and Wallace, A.M. 1995. Image acquisition using fixed and variable triangulation. In Proc. of IEE Int. Conf. on Image Processing, pp. 539–543.
Collett, E. 1993. Polarized Light: Fundamentals and Applications. Marcell Dekker.
Fryer, R.J. and Miller, J. 1991. Imaging polarimetry for industrial applications. In Proc. of British Machine Vision Conference, Glasgow, pp. 347–350.
Jones, B.F. and Fairney, P.T. 1989. Recognition of shiny objects by analysing the polarization of reflected light. Image and Vision Computing, 7(4):253–258.
Kligar, D.S., Lewis, J.W., and Randall, C.E. 1990. Polarized Light in Optics and Spectroscopy. Academic Press.
Koshikawa, K. 1979. A polarimetric approach to shape understanding of glossy objects. In Proc. of 7th Int. Conf. on Applications of Artificial Intelligence, pp. 493–495.
Koshikawa, K. and Shirai, Y. 1987. Model based recognition of glossy objects using their polarimetric properties. Advances in Robotics, 2(2):137–147.
Mendeleev, V.Y. 1995. Limits of applicability of the Bouguer model for analyzing the optical reflective characteristics of rough metal surfaces. Journal of Optical Technology, 62(2):88–91.
Mersch, S.H. 1984. Polarized lighting for machine vision applications. In Proc. of Conf. on Robot Vision and Sensory Perception, pp. 440–454.
Muller, V. 1996. Elimination of specular surface reflectance using polarized and unpolarized light. In Proc. of 4th European Conf. on Computer Vision. Cambridge.
Nayar, S.K., Fang, X.-S., and Boult, T. 1997. Separation of reflection components using colour and polarization. International Journal of Computer Vision, 21:163–186.
Nitzan, D. 1988. Three-dimensional vision structure for robot applications. IEEE Trans. PAMI, 10(3):291–309.
Pezzaniti, J.L. 1993. Mueller Matrix Imaging Polarimetry. Ph.D. Dissertation, The University of Alabama.
Pezzaniti, J.L. and Chipman, R.A. 1990. Imaging polarimeters for optical metrology. In Proceedings of the SPIE Conf. on Polarimetry: Radar, Infrared, Visible, Ultraviolet and X-Ray.
Torrance, K.E. and Sparrow, E.M. 1967. Theory for off-specular reflection from roughened surfaces. Journal of Optical Society of America, 57(9):1105–1114.
Tourre, D. 1997. The polarization of scattered light from a dielectric material for a 3d scanning application. In M.Sc. Dissertation in Optoelectronics and Laser Devices. St. Andrews University.
Trucco, E., Fisher, R.B., Fitzgibbon, A.W., and Naidu, D.K. 1998. Calibration, data consistency and model acquisition with a 3d laser striper. International Journal of Computer Integrated Manufacturing, 11(4):292–310.
Videen, G., Hsu, J.-Y., Bickel, W.S., and Wolfe, W.L. 1992. Polarized light scattered from rough surfaces. Journal of Optical Society of America A, 9(7):1111–1118.
Wolff, L.B. 1987. Surface orientation from polarization images. Proc. of SPIE Conf. on Optics, Illumination and Image Sensing for Machine Vision, 850:110–121.
Wolff, L.B. 1989. Using polarization to separate reflection components. In Proc. IEEE Int. Conf. on Computer Vision and Pattern Recognition, San Diego (CA).
Wolff, L.B. 1990. Polarization Methods in Computer Vision. Ph.D Thesis, Columbia University.
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Wallace, A., Liang, B., Trucco, E. et al. Improving Depth Image Acquisition Using Polarized Light. International Journal of Computer Vision 32, 87–109 (1999). https://doi.org/10.1023/A:1008154415349
Issue Date:
DOI: https://doi.org/10.1023/A:1008154415349