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
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
