A robust lane detection method based on vanishing point estimation using the relevance of line segments

Ju Han Yoo, Seong Whan Lee, Sung Kee Park, Dong Hwan Kim

Research output: Contribution to journalArticle

40 Citations (Scopus)

Abstract

In this paper, a robust lane detection method based on vanishing point estimation is proposed. Estimating a vanishing point can be helpful in detecting lanes, because parallel lines converge on the vanishing point in a projected 2-D image. However, it is not easy to estimate the vanishing point correctly in an image with a complex background. Thus, a robust vanishing point estimation method is proposed that uses a probabilistic voting procedure based on intersection points of line segments extracted from an input image. The proposed voting function is defined with line segment strength that represents relevance of the extracted line segments. Next, candidate line segments for lanes are selected by considering geometric constraints. Finally, the host lane is detected by using the proposed score function, which is designed to remove outliers in the candidate line segments. Also, the detected host lane is refined by using inter-frame similarity that considers location consistency of the detected host lane and the estimated vanishing point in consecutive frames. Furthermore, in order to reduce computational costs in the vanishing point estimation process, a method using a lookup table is proposed. Experimental results show that the proposed method efficiently estimates the vanishing point and detects lanes in various environments.

Original languageEnglish
Article number7888516
Pages (from-to)3254-3266
Number of pages13
JournalIEEE Transactions on Intelligent Transportation Systems
Volume18
Issue number12
DOIs
Publication statusPublished - 2017 Dec 1

Keywords

  • lane departure warning (LDW) system
  • Lane detection
  • line segment
  • probabilistic voting
  • vanishing point estimation

ASJC Scopus subject areas

  • Automotive Engineering
  • Mechanical Engineering
  • Computer Science Applications

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