A novel vision-based road detection method was proposed in this paper to realize visual guiding navigation for ground
mobile vehicles (GMV). The original image captured by single camera was first segmented into the road region and nonroad
region 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
among those disturbances caused by other edges existed in the image. In order to improve the performance of road
detection, the dynamics of GMV and the Hidden Markov Model (HMM) was taken into account to associate the possible
road boundary at different time step. The method proposed in this paper was robust against strong shadows, surface
dilapidation and illumination variations. It has been tested on real GMV and performed well in real road environments.
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