Automated Headlight Intensity Controller and Speed Control in Vehicles

Authors

  • S. Angeline Jenipher Student, Department of Electronics and Communication Engineering, Nandha College of Technology, Erode, Tamil Nadu
  • P. Aswin Student, Department of Electronics and Communication Engineering, Nandha College of Technology, Erode, Tamil Nadu
  • S. Gowsalya Student, Department of Electronics and Communication Engineering, Nandha College of Technology, Erode, Tamil Nadu
  • C. Manjula Devi Student, Department of Electronics and Communication Engineering, Nandha College of Technology, Erode, Tamil Nadu
  • D. Baskaran Assistant Professor, Department of Electronics and Communication Engineering, Nandha College of Technology, Erode, Tamil Nadu

Keywords:

Computer vision, driver assistance, tail-lamp detection, vehicle detection, video processing.

Abstract

Abstract

Headlight intensity of vehicles poses a great danger during night travel. The drivers of most vehicles use high bright beam while driving at night. This causes inconvenience for the person travelling from the opposite direction. Person experiences a sudden blaze for a short duration. When these headlights shine brightly, they cause a temporary blindness to a person, resulting in road accident during night. To avoid such incidents, we are designing a prototype of automatic headlight intensity control system. The obstacle alerting system helps the driver parking the vehicle during day and night time without colliding the vehicle with obstacles. Automated detection of vehicles in front is an integral component of many advanced driver-assistance systems (ADAS), such as collision mitigation, automatic cruise control (ACC), and automatic headlamp dimming. We present a novel image processing system to detect and track vehicle rear-lamp pairs in forward-facing color video. A standard low-cost camera with a complementary metal–oxide semiconductor (CMOS) sensor and Bayer red–green–blue (RGB) color filter is used and could be utilized for full-color image display or other color image processing applications. A tracking-based detection stage is introduced to improve robustness and to deal with distortions caused by other light sources and perspective distortion, which are common in automotive environments. Results that demonstrate the system’s high detection rates, operating distance, and robustness to different lighting conditions and road environments are presented.

 

Keywords: Computer vision, driver assistance, tail-lamp detection, vehicle detection, video processing.

Cite this Article

S. Angeline Jenipher, P. Aswin, S.Gowsalya, C. Manjula Devi, D. Baskaran. Automated Headlight Intensity Controller and Speed Control in Vehicles. Journal of Network Security. 2019; 7(2): 1–5p.

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Published

2019-09-13

Issue

Vol. 7 No. 2 (2019)

Section

Research Articles

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