Real-time lane marking detection

For autonomous navigation the real-time processing is crucial. This paper proposes a method to detect the lane markings in real-time using the advantage of parallel processing. A region of interest is constrained by the current velocity of a vehicle. The segmentation was achieved by utilizing a difference in color between lane marking and road pavement. The overall process is divided into three steps. The first is detection of lane markings based on the color probability. The second is the implementation of distance clustering analysis to define the surface course. Finally, The curve fitting was applied to assure the lane markings. The method was tested on a dataset to prove its effectiveness.