• DocumentCode
    2872993
  • Title

    Real-time traffic sign recognition based on shape and color classification

  • Author

    Caglayan, Tughan ; Ahmadzay, Habibullah ; Kofraz, Gokhan

  • Author_Institution
    Electron. & Commun. Eng. Dept., Istanbul Tech. Univ., Istanbul, Turkey
  • fYear
    2015
  • fDate
    16-19 May 2015
  • Firstpage
    1897
  • Lastpage
    1900
  • Abstract
    In this work, a system is constructed to detect and classify traffic signs, aiming to build an early warning mechanism and assists the driver in recognizing basic and important signs. Recognition of all signs is beyond the scope of this work. The operation of this study is limited to traffic signs with specific shape and color under certain environmental circumstances. In this paper, detection of red and circular or triangular signs are targeted by collecting data using a camera, mounted in front of a vehicle. Traffic signs within the collected data are extracted from each frame through several detection phases and classified using Support Vector Machine algorithm which uses Histogram of Oriented Gradients as a feature.
  • Keywords
    gradient methods; image colour analysis; shape recognition; support vector machines; traffic engineering computing; camera; color classification; driver assistance; early warning mechanism; histogram of oriented gradient; real-time traffic sign recognition; shape classification; support vector machine algorithm; vehicle; Classification algorithms; Feature extraction; Histograms; Image color analysis; Shape; Support vector machines; Wiener filters; Histogram of Oriented Gradients (HOG); Support Vector Machine (SVM); Traffic Sign Detection; Traffic Sign Recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing and Communications Applications Conference (SIU), 2015 23th
  • Conference_Location
    Malatya
  • Type

    conf

  • DOI
    10.1109/SIU.2015.7130229
  • Filename
    7130229