Image processing techniques for lane-related information extraction and multi-vehicle detection in intelligent highway vehicles

Y. J. Wu, F. L. Lian, C. P. Huang, T. H. Chang

Research output: Contribution to journalArticle

6 Scopus citations

Abstract

In this paper, we propose an approach to identify the driving environment for intelligent highway vehicles by means of image processing and computer vision techniques. The proposed approach mainly consists of two consecutive computational steps. The first step is the lane marking detection, which is used to identify the location of the host vehicle and road geometry. In this step, related standard image processing techniques are adapted for lane-related information. In the second step, by using the output from the first step, a four-stage algorithm for vehicle detection is proposed to provide information on the relative position and speed between the host vehicle and each preceding vehicle. The proposed approach has been validated in several real-world scenarios. Herein, experimental results indicate low false alarm and low false dismissal and have demonstrated the robustness of the proposed detection approach.

Original languageEnglish (US)
Pages (from-to)513-520
Number of pages8
JournalInternational Journal of Automotive Technology
Volume8
Issue number4
StatePublished - Aug 1 2007
Externally publishedYes

Keywords

  • Computer vision
  • Driving environment identification
  • Image processing
  • Lane-related information
  • Vehicle detection and tracking

ASJC Scopus subject areas

  • Automotive Engineering

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