Application of Vision Models to Traffic Sign Recognition

  • X.W. Gao
  • L. Podladchikova
  • D. Shaposhnikov
Conference paper

DOI: 10.1007/3-540-44989-2_131

Part of the Lecture Notes in Computer Science book series (LNCS, volume 2714)
Cite this paper as:
Gao X., Podladchikova L., Shaposhnikov D. (2003) Application of Vision Models to Traffic Sign Recognition. In: Kaynak O., Alpaydin E., Oja E., Xu L. (eds) Artificial Neural Networks and Neural Information Processing — ICANN/ICONIP 2003. Lecture Notes in Computer Science, vol 2714. Springer, Berlin, Heidelberg

Abstract

A system for traffic sign recognition has been developed. Both colour and shape information from signs are utilised for extraction of features. Colour appearance model CIECAM97 has been applied to extract colour information and to segment and classify traffic signs. Whilst shape features are extracted using FOSTS model, the extension of Behaviour Model of Visions (BMV). Recoganition rate is very high. For British traffic signs (n=98) obtained under various viewing conditions, the recognition rate is up to 0.95.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • X.W. Gao
    • 1
  • L. Podladchikova
    • 2
  • D. Shaposhnikov
    • 2
  1. 1.School of Computing ScienceMiddlesex University, Bounds GreenLondonUK
  2. 2.Laboratory of Neuroinformatics of Sensory and Motor Systems, A.B. Kogan ResearchInstitute for Neurocybernetics, Rostov State UniversityRostov-on-DonRussia

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