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Utilisation of the light polarization to increase the working range of the video vehicle tracking systems

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Języki publikacji
EN
Abstrakty
EN
Most of the vehicles, which can be observed by the cameras used in the Intelligent Transport Systems, are coated with reflective layers which, like car windows, are characterized by the effect of light polarisation. Utilising this effect by using a camera designed for the Intelligent Transportation System along with the linear polarizer it is possible to improve the extraction of the vehicles from the surrounding. The article presents the methods of using the polarised light for increasing the operating range of the video systems along with an illustration of the possibilities and limitations of this technique. Some experimental results obtained by the fusion of data recorded for the standard video sequences and the use of linear polarisers are also presented.
Rocznik
Strony
9--13
Opis fizyczny
Bibliogr. 17 poz.
Twórcy
autor
autor
  • Faculty of Motor Transport, Higher School of Technology and Economics in Szczecin, Klonowica 14, 71-244 Szczecin, Poland, okarma@wste.szczecin.pl
Bibliografia
  • [1] KLEIN L.A., Sensor Technologies and Data Requirements for ITS. Artech House ITS library, Norwood,Massachusetts 2001.
  • [2] KLEIN L.A., MILLS M.K., GIBSON R.P., Traffic Detector Handbook: Third Edition, FHWA, FHWA-HRT-06-108, 2006.
  • [3] IRANI M., PELEG S., Improving Resolution by Image Registration. Graphical Models and Image Processing, vol. 53, p. 231-239, 1991.
  • [4] IRANI M., PELEG S.: Super Resolution from Image Sequences. Proceedings of the 10th International Conference on Pattern Recognition, p. 115-120, June 1990.
  • [5] KEREN D., PELEG S., BRADA R., Image Sequence Enhancement Using Sub-Pixel Displacement. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, p. 742-746, June 1988.
  • [6] LUCCHESE L., CORTELAZZO G. M., A Noise-Robust Frequency Domain Technique for Estimating Planar Roto-Translations. IEEE Transactions on Signal Processing, vol. 48, no. 6, p. 1769-1786, June 2000.
  • [7] ZOMET A., RAV-ACHA A., PELEG S., Robust Super-Resolution. Proceedings of the International Conference on Computer Vision and Pattern Recognition (CVPR), vol. 1, p. 645-650, 2001.
  • [8] OKARMA K., The Influence of the Sampling Filter Function in the Super-Resolution Methods on the Accuracy of the Register Plates Recognition and the Visual Image Quality”. Logistyka no. 6/2009 (CD-ROM).
  • [9] OKARMA K., MAZUREK P., Automatic Image Quality Assessment of the Super-Resolution Images for the Register Plate Number Recognition. Logistyka no. 2/2010 p. 283-290 (in Polish).
  • [10] OKARMA K., MAZUREK P., The Analysis of the Super-Resolution Techniques for the Automatic Vertical Road Signs Recognition Systems. Logistyka no. 6/2009 (CD-ROM).
  • [11] FEYNMAN R.P., LEIGHTON R.B, SANDS M., The Feynman Lectures on Physics, vol. 1-2, 2nd edition, Addison Wesley Longman, 2005
  • [12] GUENTHER R.D., Modern Optics, Wiley 1990
  • [13] BENNETT J.M., Polarization, in: Handbook of Optics, vol. I Fundamentals, Techniques, and Design (ed. BASS M., et.al.), McGraw-Hill, 1995
  • [14] PYE D., Polarised Light in Science and Nature, Institute of Physics Publishing, 2001.
  • [15] BRADSKI G., KAEHLER A., Learning OpenCV. Computer Vision with the OpenCV Library, O’Reilly Media, 2008.
  • [16] HARTLEY R.I., ZISSERMAN A., Multiple View Geometry in Computer Vision, Cambridge University Press, 2000.
  • [17] BLACKMAN S., POPULI R., Design and Analysis of Modern Tracking Systems. Artech House, 1999.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BSL8-0044-0014
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