Vision-based traffic sign compliance evaluation using convolutional neural network

Vision-based traffic sign compliance evaluation using convolutional neural network

Manual monitoring of road signs compliance procedures are adapted by developing countries. As effective as this method is, the amount of time and funds needed to cover a large area is quite alarming. Thus, a need for a vision - based traffic sign detection and recognition system. However, while a ma...

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Bibliographic Details
Main Authors: Roxas, Edison A., Acilo, Joshua N., Vicerra, Ryan Rhay P., Dadios, Elmer P., Bandala, Argel A.
Format: text
Published: Animo Repository 2018
Subjects:
Traffic monitoring
Computer vision
Traffic signs and signals—Control systems
Electrical and Computer Engineering
Electrical and Electronics
Systems and Communications
Online Access:https://animorepository.dlsu.edu.ph/faculty_research/1552
https://animorepository.dlsu.edu.ph/context/faculty_research/article/2551/type/native/viewcontent
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Institution: De La Salle University
Description
Summary:Manual monitoring of road signs compliance procedures are adapted by developing countries. As effective as this method is, the amount of time and funds needed to cover a large area is quite alarming. Thus, a need for a vision - based traffic sign detection and recognition system. However, while a majority of researches using machine vision focuses on the development of a robust real - time traffic sign recognition system, researches addressing the issue of the sign compliance and standardization is lacking. © 2018 IEEE.

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