Vision-Based Road Detection by Adaptive Region Segmentation and Edge Constraint

A novel vision-based road detection method was proposed in this paper to realize visual guiding navigation for ground mobile vehicles in outdoor environments. The road region was first segmented from the jumbled backgrounds by using an adaptive threshold segmentation algorithm named OTSU. Subsequently, the Canny edges extracted in grey images would be filtered in the road region so that the road boundary could be recognized accurately by reducing the unnecessary disturbances from the useless edge existed in background By combining the detection algorithm of both road region and road boundary, the road detection method proposed in this paper was robust against strong shadows, surface dilapidation and illumination variations. It has been tested on real ground mobile vehicle and performed well in real road environments.