Using Fourier Descriptors and Spatial Models for Traffic Sign Recognition

  • Fredrik Larsson
  • Michael Felsberg
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6688)


Traffic sign recognition is important for the development of driver assistance systems and fully autonomous vehicles. Even though GPS navigator systems works well for most of the time, there will always be situations when they fail. In these cases, robust vision based systems are required. Traffic signs are designed to have distinct colored fields separated by sharp boundaries. We propose to use locally segmented contours combined with an implicit star-shaped object model as prototypes for the different sign classes. The contours are described by Fourier descriptors. Matching of a query image to the sign prototype database is done by exhaustive search. This is done efficiently by using the correlation based matching scheme for Fourier descriptors and a fast cascaded matching scheme for enforcing the spatial requirements. We demonstrated on a publicly available database state of the art performance.


Traffic sign recognition Fourier descriptors spatial models traffic sign dataset 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Fredrik Larsson
    • 1
  • Michael Felsberg
    • 1
  1. 1.Computer Vision LaboratoryLinköping UniversityLinköpingSweden

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