Various Lane Marking Detection and Classification for Vision-based Navigation System

A vision-based car navigation system (CNS) gives drivers more precise and realistic traffic data than a traditional 2D-CNS. As part of the vision-based CNS, the ability to detect lane markings can provide significant warnings which increase traffic safety and convenience. Meanwhile, accurate lane classification results can indicate the current/approaching road conditions in this system. This paper concentrates on two kernels: lane marking detection and lane type identification. The lane detection part uses IPM and histogram sampling and the lane marking type classification step utilizes spatial and frequency sampling for different types of lane markings.