Rectangular Traffic Sign Recognition

  • Roberto Ballerini
  • Luigi Cinque
  • Luca Lombardi
  • Roberto Marmo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3617)

Abstract

In this research the problem of the automatic detection and classification of rectangular road sign has been faced. The first step concerns the robust identification of the rectangular sign, through the search of gray level discontinuity on the image and Hough transform. Due to variety of rectangular road signs, we first recognize the guide sign and then we consider advertising the other rectangular signs. The classification is based on analysis of surface color and arrows direction of the sign. We have faced different problems, primarily: shape alterations of the sign owed to the perspective, shades, different light conditions, occlusion. The obtained results show the feasibility of the system.

Keywords

Sign Recognition Intelligent Transportation System Black Pixel Road Sign Arrow Direction 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Azami, S., Katahara, S., Aoki, M.: Route guidance sign identification using 2-d structural description. In: Proceedings IEEE Int. Conf. Intelligent Transportation Systems, pp. 153–158 (1996)Google Scholar
  2. 2.
    Chen, X., Yang, J., Zhang, J., Waibel, A.: Automatic detection and recognition of signs from natural scenes. IEEE Trans. Image Processing 13, 87–99 (2004)CrossRefGoogle Scholar
  3. 3.
    De La Escalera, A., Armingol, J.M., Pastor, J.M., Rodriguez, F.J.: Visual sign information extraction and identification by deformable models for intelligent vehicles. IEEE Trans. Intelligent Transportation Systems 5, 57–68 (2004)CrossRefGoogle Scholar
  4. 4.
    Franke, U., Gavrila, D., Gorzig, S., Lindner, F., Paetzold, F., Wohler, C.: Autonomous driving approaches downtown. IEEE Trans. Intelligent Transportation Systems 13, 40–48 (1999)Google Scholar
  5. 5.
  6. 6.
    Kato, T., Kobayasi, A., Hase, H., Yoneda, M.: An experimental consideration for road guide sign understanding. In: Proc. IEEE Int. Conf. Intelligent Transportation Systems, pp. 268–273 (2002)Google Scholar
  7. 7.
    Lee, J., Jo, K.: Traffic Sign Recognition by division of Characters and Symbols Regions. In: Proc. 7th Korea-Russia International Symposium, pp. 324–328 (2003)Google Scholar
  8. 8.
    Miura, J., Kanda, T., Shirai, Y.: An active vision system for real-time traffic sign recognition. In: Proc. IEEE Int. Conf. Intelligent Transportation Systems, pp. 52–57 (2000)Google Scholar
  9. 9.
    Priese, L., Lakmann, R., Rehrmann, V.: Ideogram Identification in a Realtime Traffic Sign Recognition System. In: Proc. IEEE Int. Conf. Intelligent Transportation Systems, pp. 310–314 (1995)Google Scholar
  10. 10.
    Salgian, G., Ballard, D.H.: Visual routines for autonomous driving. In: Proc. 6th Int. Conf. Computer Vision, pp. 876–882 (1998)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Roberto Ballerini
    • 1
  • Luigi Cinque
    • 2
  • Luca Lombardi
    • 1
  • Roberto Marmo
    • 1
  1. 1.Dipartimento di Informatica e SistemisticaUniversity of PaviaPaviaItaly
  2. 2.Dipartimento di Informatica ”La Sapienza”University of RomaItaly

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