Traffic Sign Detection Under Foggy Environment Using Machine Learning

Traffic Sign Detection Under Foggy Environment Using Machine Learning

Mr.Vishal Sonar,Mrs.Manisha Darak,Mr.Sujit Tatugade, Mr.Mandar Todkar,Ms.Vaishnavi Mugale

Dept. of Computer Science(RMDSSOE)
Savitribai Phule Pune University
Pune, India

Abstract –

Road signs are important to ensure smooth traffic flow without bottle necks or mishaps. Road symbols are the pictorial representations having different necessary information required to be understood by driver. Road signs in front of the vehicle are ignored by the drivers and this can lead to catastrophic accidents. This paper presents an overview of the traffic sign board detection and recognition and implements a procedure to extract the road sign from a natural complex image, processes it and alerts the driver using voice command It is implemented in such a way that it acts as a boon to drivers to make easy decisions. Traffic sign recognition is a critical component of modern intelligent transportation systems, contributing to road safety and efficient traffic management. This paper presents a novel approach to traffic sign recognition based on Convolutional Neural Networks (CNNs).

Key Words:  CNN, Pre-processing, Feature Extraction.