Lane Detection and Kalman-Based Linear-Parabolic Lane Tracking

This paper presents a lane detection and linear-parabolic lane tracking system using Kalman filtering method. First, the image horizon is detected in a traffic scene to split the sky and road region. Road region is further analyzed with entropy method to remove the road pixels. Lane boundaries are then extracted from the region using lane markings detection. These detected boundaries are tracked in consecutive video frames with a linear-parabolic tracking model. The model parameters are updated with Kalman filtering method. Error-checking is performed iteratively to ensure the performance of the lane estimation model. Simulation results demonstrate good performance of the proposed Kalman-based linear-parabolic lane tracking system with fine parameters update.