Self-made texture and clustering based road recognition for UGV

Three hierarchical algorithms are proposed to get the passable driving road detection for unmanned ground vehicle (UGV). The innovation of this paper is the self-made directional texture which will be produced if the inverse homography transform is exerted on the image. This self-made texture is firstly used to remove the image corresponding to the objects above road. In order to avoid the influence of other color object, the k-means clustering is used to get the seed for region growing. Finally, the directional texture is secondly used to judge whether the image holes after region growing are the road or not. The final experimental results show the proposed algorithm can remove the non-road objects, can and fill the stained color region and can get the rational driving road.