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International Conference on Artificial Neural Networks

International Conference on Neural Information Processing

ICANN 2003, ICONIP 2003: Artificial Neural Networks and Neural Information Processing — ICANN/ICONIP 2003 pp 1100–1105Cite as

Application of Vision Models to Traffic Sign Recognition

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2714))

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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Author information

Authors and Affiliations

  1. School of Computing Science, Middlesex University, Bounds Green, London, N11 2NQ, UK

    X.W. Gao

  2. Laboratory of Neuroinformatics of Sensory and Motor Systems, A.B. Kogan Research, Institute for Neurocybernetics, Rostov State University, Rostov-on-Don, Russia

    L. Podladchikova & D. Shaposhnikov

Authors
  1. X.W. Gao
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  2. L. Podladchikova
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  3. D. Shaposhnikov
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Editor information

Editors and Affiliations

  1. Bogazici University, Bebek, 34342, Istanbul, Turkey

    Okyay Kaynak  & Ethem Alpaydin  & 

  2. Laboratory of Computer and Information Science, Helsinki University of Technology, P.O.B. 5400, 02015, Finland

    Erkki Oja

  3. Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong

    Lei Xu

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© 2003 Springer-Verlag Berlin Heidelberg

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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. ICANN ICONIP 2003 2003. Lecture Notes in Computer Science, vol 2714. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44989-2_131

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  • DOI: https://doi.org/10.1007/3-540-44989-2_131

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40408-8

  • Online ISBN: 978-3-540-44989-8

  • eBook Packages: Springer Book Archive

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