A novel disparity transformation algorithm for road segmentation

Rui Fan*, Mohammud Junaid Bocus, Naim Dahnoun

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

23 Citations (Scopus)
55 Downloads (Pure)


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.

Original languageEnglish
Pages (from-to)18-24
Number of pages7
JournalInformation Processing Letters
Early online date9 Aug 2018
Publication statusPublished - 1 Dec 2018

Structured keywords

  • Engineering Education Research Group
  • Photonics and Quantum


  • Computational complexity
  • Disparity transformation
  • Dynamic programming
  • Golden section search
  • Otsu's thresholding
  • Roll angle


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