NSGA-II Based Auto-Calibration of Automatic Number Plate Recognition Camera for Vehicle Speed Measurement

  • Patryk Filipiak
  • Bartlomiej Golenko
  • Cezary Dolega
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9597)

Abstract

This paper introduces an auto-calibration mechanism for an Automatic Number Plate Recognition camera dedicated to a vehicle speed measurement. A calibration task is formulated as a multi-objective optimization problem and solved with Non-dominated Sorting Genetic Algorithm. For simplicity a uniform motion profile of a majority of vehicles is assumed. The proposed speed estimation method is based on tracing licence plates quadrangles recognized on video frames. The results are compared with concurrent measurements performed with piezoelectric sensors.

Keywords

Camera auto-calibration Multiobjective optimization Evalutionary approach Camera model Vehicle speed measurement 

References

  1. 1.
    Qadri, M.T.: Automatic number plate recognition system for vehicle identification using optical character recognition. In: Proceedings of International Conference on Education Technology and Computer (ICETC ), pp. 335–338 (2009)Google Scholar
  2. 2.
    Cathey, F.W., Dailey, D., J.: A novel technique to dynamically measure vehicle speed using uncalibrated roadway cameras. In: Proceedings of IEEE Intelligent Vehicles Symposium, pp. 777–782 (2005)Google Scholar
  3. 3.
    Dailey, D.J.: An algorithm to estimate mean traffic speed using uncalibrated cameras. IEEE Trans. Intell. Transp. Syst. 1(2), 98–107 (2000)CrossRefGoogle Scholar
  4. 4.
    Dailey, D.J., Li, L.: Video image processing to create a speed sensor, University of Washington, Seattle, WA, ITS Research Program, final research report (1999)Google Scholar
  5. 5.
    Grammatikopoulos, L., Karras, G., Petsa, E.: Automatic estimation of vehicle speed from uncalibrated video sequences. In: Proceedings of International Symposium on Modern Technologies, Education and Profeesional Practice in Geodesy and Related Fields, pp. 332–338 (2005)Google Scholar
  6. 6.
    Lin, H.-Y., Li, K.-J., Chang, C.-H.: Vehicle speed detection from a single motion blurred image. Image Vis. Comput. 26(10), 1327–1337 (2008)CrossRefGoogle Scholar
  7. 7.
    Schoepflinand, T.N., Dailey, D.J.: Dynamic camera calibration of roadside traffic management cameras for vehicle speed estimation. IEEE Trans. Intell. Transp. Syst. 4(2), 90–98 (2003)CrossRefGoogle Scholar
  8. 8.
    Caprile, B., Torre, V.: Using vanishing points for camera calibration. Int. J. Comput. Vision 4(2), 127–140 (1990)CrossRefGoogle Scholar
  9. 9.
    Kim, Z.W.: Geometry of vanishing points and its application to external calibration and realtime pose estimation. Reseach Report, Institute of Transportation Studies, University of California at Berkeley (2006)Google Scholar
  10. 10.
    Lenz, R.K., Tsai, R.Y.: Techniques for calibration of the scale factor and image center for high accuracy 3D machine vision metrology. IEEE Trans. Pattern Anal. Mach. Intell. 1(5), 713–720 (2000)Google Scholar
  11. 11.
    Deb, K., Pratap, A., Agarwal, S., Meyarivan, T.A.M.T.: A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans. Evol. Comput. 6(2), 182–197 (2002)CrossRefGoogle Scholar
  12. 12.
    Wang, J.: An overview of research on weigh-in-motion system. In: Proceedings of Fifth World Congress on Intelligent Control and Automation (WCICA 2004), pp. 5241–5244 (2004)Google Scholar
  13. 13.
    Hanning, T.: High precision camera calibration. Habilitation thesis. Vieweg+Teubner Verlag, University of Passau (2009)Google Scholar
  14. 14.
    Zhang, Q., Li, H.: MOEA/D: a multiobjective evolutionary algorithm based on decomposition. IEEE Trans. Evol. Comput. 11(6), 712–731 (2007)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Patryk Filipiak
    • 1
  • Bartlomiej Golenko
    • 2
  • Cezary Dolega
    • 3
  1. 1.Institute of Computer ScienceUniversity of WroclawWroclawPoland
  2. 2.Signal Theory SectionWroclaw University of TechnologyWroclawPoland
  3. 3.Neurosoft, Sp. z o.o.WroclawPoland

Personalised recommendations