Versatile lane departure warning using 3D visual geometry

Din Chang Tseng, Chun Wei Lin

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


This paper presents a versatile lane departure warning (LDW) system based on three-dimensional (3D) visual geometry that would help drivers avoid unintended departure from their lane during land vehicle driving. A horizontal gradient map was first calculated by an edge operator combined with the properties of lateral inhibition and far-near adaptation so that the operation would be less influenced by bad weather conditions. The lane marks were then detected with the proposed conjugate Gaussian model on the non-thresholded gradient map to make the detection more stable and less influenced by shadow boundary, windshield wipers, and the partial occlusion of other vehicles. The detected lane marks were then verified by the 3D geometric constraints of the parallel lines on the road surface to avoid the wrong detection of non-lane marks; moreover, the constraints were also used to find the other-side lane mark from the extracted one if only one lane mark was extracted on low-quality road surfaces. This means that the lane can be detected even if only one lane mark is detected. Lastly, the lane departure distance was accurately calculated from the 3D geometry of the lane marks rather than roughly estimated from the two-dimensional relationship of the lane marks on images. Overall, the properties of the proposed system are special and unique and are not present in existing systems. Based on various images of weather conditions and road surface situations, this paper demonstrates the effect and efficiency of the proposed system and compares it with other existing systems.

Original languageEnglish
Pages (from-to)1899-1917
Number of pages19
JournalInternational Journal of Innovative Computing, Information and Control
Issue number5
StatePublished - 2013


  • Advanced safety vehicle
  • Computer vision
  • Driving assistance
  • Lane departure warning
  • Lane-mark detection


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