A Robust Algorithm for the Detection of Vehicle Turn Signals and Brake Lights

Mauricio Casares, Akhan Almagambetov, Senem Velipasalar

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

33 Citations (Scopus)

Abstract

Robust and lightweight detection of alert signals of front vehicle, such as turn signals and brake lights, is extremely critical, especially in autonomous vehicle applications. Even with cars that are driven by human beings, automatic detection of these signals can aid in the prevention of otherwise deadly accidents. This paper presents a novel, robust and lightweight algorithm for detecting brake lights and turn signals both at night and during the day. The proposed method employs a Kalman filter to reduce the processing load. Much research is focused only on the detection of brake lights at night, but our algorithm is able to detect turn signals as well as brake lights under any lighting conditions with high accuracy rates.
Original languageEnglish
Title of host publication2012 IEEE Ninth International Conference on Advanced Video and Signal-Based Surveillance
Pages386-391
Number of pages6
DOIs
Publication statusPublished - Sep 1 2012

Keywords

  • Vehicles
  • Kalman filters
  • Image color analysis
  • Color
  • Signal processing algorithms
  • Turning
  • Robustness
  • Cameras
  • vehicle light detection
  • transportation
  • autonomous vehicles
  • tracking
  • Kalman filter
  • signal processing algorithms

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