• DocumentCode
    1941851
  • Title

    Traffic sign shape classification evaluation. Part II. FFT applied to the signature of blobs

  • Author

    Gil-Jiménez, P. ; Lafuente-Arroyo, S. ; Gómez-Moreno, H. ; López-Ferreras, F. ; Maldonado-Bascón, S.

  • Author_Institution
    Dept. de Teoria de la Senal y Comunicaciones, Univ. de Alcala, Alcala de Henares, Madrid, Spain
  • fYear
    2005
  • fDate
    6-8 June 2005
  • Firstpage
    607
  • Lastpage
    612
  • Abstract
    In this paper we have developed a new algorithm of artificial vision oriented to traffic sign shape classification. The classification method basically consists of a series of comparison between the FFT of the signature of a blob and the FFT of the signatures of the reference shapes used in traffic signs. The two major steps of the process are: the segmentation according to the color and the identification of the geometry of the candidate blob using its signature. The most important advances are its robustness against rotation and deformation due to camera projections.
  • Keywords
    cameras; computer vision; fast Fourier transforms; image classification; image segmentation; road traffic; FFT; artificial vision; camera projections; candidate blob signature; traffic sign shape classification evaluation; Color; Electronic mail; Geometry; Image databases; Image recognition; Image segmentation; Robustness; Shape; Testing; Traffic control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Vehicles Symposium, 2005. Proceedings. IEEE
  • Print_ISBN
    0-7803-8961-1
  • Type

    conf

  • DOI
    10.1109/IVS.2005.1505170
  • Filename
    1505170