Real-Time Myanmar Traffic Sign Recognition System using HOG and SVM

Thida Lwin; Myint Tun

Title:
Real-Time Myanmar Traffic Sign Recognition System using HOG and SVM

Authors:
Myint Tun | Thida Lwin

Cite This Article :

Myint Tun | Thida Lwin "Real-Time Myanmar Traffic Sign Recognition System using HOG and SVM" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5, August 2019, pp.2367-2371, URL: https://www.ijtsrd.com/papers/ijtsrd27929.pdf

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Abstract :
Traffic sign recognition is one of the most important research topics for enabling autonomous vehicle driving systems. In order to be deployed in driving environments, intelligent transport system must be able to recognize and respond to exceptional road conditions such as traffic signs, highway work zones and imminent road works automatically. In this paper, Real-time Myanmar Traffic Sign Recognition System (RMTSRS) is proposed. The incoming video stream is fed into computer vision. Then each incoming frames are segmented using color threshold method for traffic sign detection. A Histogram of Oriented Gradients (HOG) technique is used to extract the features from the segmented traffic sign and then RMTSRS classifies traffic sign types using Support Vector Machine (SVM). The system achieves classification accuracy up to 98%.

Keywords :
Traffic sign recognition, intelligent transport system, computer vision, color Threshold, HOG and SVM

Publication Details:

Unique Identification Number : IJTSRD27929

Published In : Volume-3 | Issue-5, August 2019

Page Number(s) : 2367-2371

Publisher Name : IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470

Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

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