2D line filters for vision-based lane detection and tracking

In this work a vision-based lane detection system is presented. The main contribution is the application of 2D line filters for lane detection which suppress noise in the near distance without destroying lines in the fare distance. Line pairs are decided to belong to lane markings by means of parallelism is world coordinates and reasonable constraints concerning the road width. The polygon constructed from the detected lane markings is then tracked over time via a Kalman filter. Results of the approach are presented in terms of the detection accuracy on a labeled video sequence.