Low-cost Driver Assistance System for drivers suffering from Dyslexia or Color-blindness using Machine Learning

Lowcost Driver Assistance System for drivers suffering from Dyslexia or Colorblindness using Machine Learning
  IJETT-book-cover           
  
© 2021 by IJETT Journal
Volume-69 Issue-12
Year of Publication : 2021
Authors : Shikher Srivastava, Ayush Nigam, Dr. Madiajagan Muthaiyan
DOI :  10.14445/22315381/IJETT-V69I12P207

How to Cite?

Shikher Srivastava, Ayush Nigam, Dr. Madiajagan Muthaiyan, "Lowcost Driver Assistance System for drivers suffering from Dyslexia or Colorblindness using Machine Learning," International Journal of Engineering Trends and Technology, vol. 69, no. 12, pp. 47-55, 2021. Crossref, https://doi.org/10.14445/22315381/IJETT-V69I12P207

Abstract
This paper proposes a Driver Assistance System with the capability of Traffic Sign and Traffic Light Detection from complex background images in a real-time environment with high efficiency. The proposed methodology aims to design an intelligent and self-sufficient model to extract the traffic sign and traffic light from a complex natural image using a camera with the help of Image Processing and Machine Learning. To make the traffic sign recognition perform efficiently in a real-time environment, a Machine Learning Model is trained with actual traffic sign data, i.e., images of real-life traffic signs. Traffic Lights are detected using color and shape differentiation techniques to extract a traffic post from the background and then extract the light from the post. This model can easily be installed in any vehicle with a mounted camera on the front or be a part of a more sophisticated vehicle controlling system. It will recognize traffic lights and road signs and then accordingly instruct the required actions to the driving agent, especially helpful for drivers suffering from color-blindness or dyslexia.

Keywords
Driver Assistance System, Iterative End-Point Fit Algorithm, Traffic Sign Recognition, Traffic Light Recognition, Support Vector Machine (SVM)

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