Improvement of Driver Visibility at Night by Ego Vehicle Headlight Control

H. A. Harindu, J. R. Kithsiri, Chinthaka Premachandra

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

For drivers it is significant to have an appropriate intensity level of light for proper visibility of the road. But, driving a vehicle at night is very difficult task due to the direct headlights from vehicles which drives in opposite directions and uncontrollable light sources from outside. Moreover, when the headlights are dim, the intensity level of the light is not sufficient for the drivers which causes to increase the accidents rate rapidly specially in urban areas. This is mainly due to manual lightening systems. Therefore this research is focus on developing an efficient image processing based algorithm to ensure the sufficient intensity level of the lights to the ego-vehicle driver while providing the least intensity level for the opposite drivers automatically. A pixel-based image segmentation method was used to implement the proposal. Testing the algorithm was done in a simulated environment to verify the accuracy of the algorithm.

Original languageEnglish
Title of host publicationProceedings of International Conference on Image Processing and Robotics, ICIPRoB 2020
EditorsB. H. Sudantha
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728165417
DOIs
Publication statusPublished - 2020 Mar 6
Event1st International Conference on Image Processing and Robotics, ICIPRoB 2020 - Negombo, Sri Lanka
Duration: 2020 Mar 62020 Mar 8

Publication series

NameProceedings of International Conference on Image Processing and Robotics, ICIPRoB 2020

Conference

Conference1st International Conference on Image Processing and Robotics, ICIPRoB 2020
CountrySri Lanka
CityNegombo
Period20/3/620/3/8

Keywords

  • Image Processing
  • Image segmentation
  • Light Intensity
  • Matlab
  • RaspberryPi

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Decision Sciences (miscellaneous)
  • Control and Optimization

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