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Real Time Traffic Sign Detection and Recognition using Adaptive Neuro Fuzzy Inference System

Mustain Billah, Sajjad Waheed, Kawsar Ahmed, Abu Hanifa. Published in Fuzzy Systems.

Communications on Applied Electronics
Year of Publication: 2015
Publisher: Foundation of Computer Science (FCS), NY, USA
Authors: Mustain Billah, Sajjad Waheed, Kawsar Ahmed, Abu Hanifa
10.5120/cae2015651877

Mustain Billah, Sajjad Waheed, Kawsar Ahmed and Abu Hanifa. Article: Real Time Traffic Sign Detection and Recognition using Adaptive Neuro Fuzzy Inference System. Communications on Applied Electronics 3(2):1-5, October 2015. Published by Foundation of Computer Science (FCS), NY, USA. BibTeX

@article{key:article,
	author = {Mustain Billah and Sajjad Waheed and Kawsar Ahmed and Abu Hanifa},
	title = {Article: Real Time Traffic Sign Detection and Recognition using Adaptive Neuro Fuzzy Inference System},
	journal = {Communications on Applied Electronics},
	year = {2015},
	volume = {3},
	number = {2},
	pages = {1-5},
	month = {October},
	note = {Published by Foundation of Computer Science (FCS), NY, USA}
}

Abstract

Traffic sign recognition is a major part of an automated intelligent driving vehicle or driver assistance systems.Perfect recognition of traffic sign helps an intelligent driving system giving valuable information about road signs,warnings, prohibitions thus increasing driving speed, security and decreasing risk of accident. Many techniques have been used for recognising traffic signs such as backpropagation neural network,support vector machines, convolutional neural network etc on different shaped signs. Fuzzy inference system has not been used in deep for this purpose. In this paper, we have tried to find out the capability of adaptive neuro fuzzy inference system(ANFIS) for traffic sign recognition. We have used video and image processing for detecting circular shaped signs and used ANFIS for recognizing detected signs.

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Keywords

Image processing, ANFIS, Traffic sign recognition, Intelligent driving, sign detection