Fast Detection and Tracking of Worn Lane Markings

A fast method for lanes detection is proposed to deal with worn lane markings. Lanes are detected based on regional pixels rather than edge points in this paper by concerning that the worn or faded lane markings lead to disruption to edge extraction. After pixels have voted, the local maximum is searched and a peak region is defined in the Hough space. The voting of a column in the peak region is considered as a stochastic variable, and the statistical characteristics are computed. The statistical variances are used to fit a quadratic function. The direction parameter of the lane marking is determined by the minimization of the fitted quadratic function. The statistical means are used to fit a linear function. The position parameter of the lane marking is computed using the interpolation technique. Lane tracking is implemented with lower computation cost by defining the peak region based on the lane parameters detected in previous frame. The experimental results show that the proposed method can detect effectively the lane markings even in presence of seriously worn roads. The computation time is less than 2ms for a road image.