Lane detection using spline model

Yue Wang, Dinggang Shen, Eam Khwang Teoh

Research output: Contribution to journalArticle

158 Citations (Scopus)

Abstract

In this paper, a Catmull-Rom spline-based lane model which describes the perspective effect of parallel lines has been proposed for generic lane boundary. Since Catmull-Rom spline can form arbitrary shapes by different sets of control points, it can describe a wider range of lane structures compared with other lane models, i.e. straight and parabolic models. Moreover, the lane detection problem has been formulated here as the problem of determining the set of control points of lane model. The proposed algorithm first detects the vanishing point (line) by using a Hough-like technique and then solves the lane detection problem by suggesting a maximum likelihood approach. Also, we have employed a multi-resolution strategy for rapidly achieving an accurate solution. This coarse-to-fine matching offers us an acceptable solution at an affordable computational cost, and thus speeds up the process of lane detection. As a result, the proposed method is robust to noise, shadows, and illumination variations in the captured road images, and is also applicable to both the marked and the unmarked roads.

Original languageEnglish
Pages (from-to)677-689
Number of pages13
JournalPattern Recognition Letters
Volume21
Issue number8
DOIs
Publication statusPublished - 2000 Jul

Keywords

  • Catmull-Rom spline
  • Intelligent vehicle
  • Lane detection
  • Lane model
  • Machine vision
  • Maximum likelihood

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

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