Volume 7, Issue 1 (3-2017)                   ASE 2017, 7(1): 2346-2355 | Back to browse issues page


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Khodayari A, Ghaffari A, Fanni F. A Real Time Traffic Sign Detection and Recognition Algorithm based on Super Fuzzy Set. ASE 2017; 7 (1) :2346-2355
URL: http://www.iust.ac.ir/ijae/article-1-393-en.html
Abstract:   (17145 Views)

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.

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