Combining dark channel prior and color cues for road following in outdoor environments

This paper proposes a road following method in outdoor environments based on dark channel prior and color cues, which integrates the atmospheric transmission estimation, mean shift filtering and graph cuts algorithm together. The main idea is fusing scene depth cue with color information in six-dimensional feature space for road image following. Specifically, the dark channel prior based transmission estimation is firstly employed to recover depth cue. Then the mean shift filtering in the weighted color-depth space is proposed. Finally, graph cuts algorithm is applied to achieve the final road detection. Experimental results indicate the proposed method has excellent performance in complex outdoor environments.