CNN and Keras based Road Safety Traffic Signs Recognition System

Authors

  • M. Mohsina Kousar  Research Scholar, Department of CSE, Ashoka women's engineering College, Kurnool, India
  • Dr. S. Shoeb Peer  Professor, Department of CSE, Ashoka women's engineering College, Kurnool, India

DOI:

https://doi.org/10.32628/IJSRST52310429

Keywords:

Road Accidents, Traffic Sign Recognition, Convolution Neural Network, Feature Extraction

Abstract

Accident rates increased due to non-compliance with traffic signs and non-compliance with traffic rules. By using synthetic training data from images of train signs, we can overcome the problem of analysis of traffic data, which varies by country and region. This method is used to create files containing synthetic images to detect traffic signs from different perspectives. With this knowledge and a well-designed Convolutional Neural Network (CNN), we can create a data-driven train recognition and detection system that has accurate detection accuracy and still has action. This article presents the process of recognizing and classifying road signs and traffic signs to create their inventory to help great engineers replace and maintain them. It uses images captured by a camera from a moving car. The system is based on three main stages: color segmentation, recognition and classification. Many researchers in the world of artificial intelligence and technology and Tesla, Uber, Google, Mercedes-Benz, Toyota, Ford, Audi etc. big companies like self-driving cars and self-driving cars. Therefore, in order for this technology to be used correctly, vehicles must be able to interpret traffic signs and make decisions accordingly. This reduces accidents and also helps drivers concentrate on driving rather than looking at every traffic card. The purpose of this document is to provide an effective way of discovering and recognizing traffic signs in India.

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International Journal of Scientific Research in Science and Technology

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Published

2023-08-30

Issue

Volume 10, Issue 4, July-August-2023

Section

Research Articles

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How to Cite

[1]
M. Mohsina Kousar, Dr. S. Shoeb Peer "CNN and Keras based Road Safety Traffic Signs Recognition System" International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011,Volume 10, Issue 4, pp.368-374, July-August-2023. Available at doi : https://doi.org/10.32628/IJSRST52310429