• Title of article

    A Real Time Traffic Sign Detection and Recognition Algorithm based on Super Fuzzy Set

  • Author/Authors

    Khodayari, A Associate Professor - Mechanical Engineering Department - Pardis Branch - Islamic Azad University, Tehran , Ghaffari, A Mechanical Engineering Department - K.N.Toosi University of Technology, Tehran , Fanni, E Mechatronics Engineering Department - South Tehran Branch - Islamic Azad University, Tehran

  • Pages
    10
  • From page
    2346
  • To page
    2355
  • Abstract
    Advanced Driver Assistance Systems (ADAS) benefit from current infrastructure to discern environmental information. Traffic signs are global guidelines which inform drivers from near characteristics of paths ahead. Traffic Sign Recognition (TSR) system is an ADAS that recognize traffic signs in images captured from road and show information as an adviser or transmit them to other ADASs. In this paper presents a novel machine vision algorithm for traffic sign recognition based on fuzzy sets. This algorithm is a pipeline consists of multiple fuzzy set that create a fuzzy space here called Super Fuzzy Set (SFS). SFS helped to design a flexible and fast algorithm for recognizing traffic signs in a real-time application. Designed algorithm was implemented in computer-based system and checked on a test car in real urban environment. 83.34% accuracy rate was obtained in real-time test.
  • Keywords
    Advanced Driver Assistance Systems , Traffic Sign Recognition , Super Fuzzy Set , Vision Algorithm
  • Journal title
    Astroparticle Physics
  • Serial Year
    2017
  • Record number

    2467482