Lane detection using color-based segmentation

Lane boundary detection is the problem of estimating the geometric structure of the lane boundaries of a road on the images captured by a camera. To be an intelligent vehicle, lane boundary is necessary information, so the system and the algorithm should be as simple and fast as possible. In this paper, we propose a new method based on color information and this method is applicable in complex environment. In this system, we first choose a region of interest to find out a threshold using statistical method in a color image. The threshold then will be used to distinguish possible lane boundary from the road. We use color-based segmentation to find out the lane boundary and use a quadratic function to approach it. This system demands low computational power and memory requirements, and is robust in the presence of noise, shadows, pavement, and obstacles such like cars, motorcycles and pedestrians conditions. The result images can be used as pre-processed images for lane tracking, road following or obstacle detection.