A novel disparity transformation algorithm for road segmentation

• Published in: Information processing letters Vol. 140; pp. 18 - 24
• Main Authors: Fan, Rui, Bocus, Mohammud Junaid, Dahnoun, Naim
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.12.2018
• Subjects: Computational complexity; Disparity transformation; Dynamic programming; Golden section search; Otsu's thresholding; Roll angle; Golden section search; Otsu's thresholding; Disparity transformation; Dynamic programming; Computational complexity; Roll angle
• ISSN: 0020-0190; 1872-6119
• DOI: 10.1016/j.ipl.2018.08.001

The disparity information provided by stereo cameras has enabled advanced driver assistance systems to estimate road area more accurately and effectively. In this paper, a novel disparity transformation algorithm is proposed to extract road areas from dense disparity maps by making the disparity value of the road pixels become similar. The transformation is achieved using two parameters: roll angle γ and fitted disparity value d with respect to each row. To achieve a better processing efficiency, golden section search and dynamic programming are utilised to estimate γ and d, respectively. By performing a rotation around γ, the disparity distribution of each row becomes very compact. This further improves the accuracy of the road model estimation, as demonstrated by the various experimental results in this paper. Finally, the Otsu's thresholding method is applied to the transformed disparity map and the roads can be accurately segmented at pixel level. •A novel disparity transformation algorithm acting on the disparity maps for road segmentation.•The proposed algorithm can estimate the roll angle for vehicles accurately and efficiently.•To improve the processing efficiency, the algorithm is optimised using golden section search and dynamic programming.