Robust Vehicle Detection for Highway Surveillance via Rear-view Monitoring

Akio Yoneyama*, Chia H. Yeh, C. C. Jay Kuo

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

Abstract

Vision-based highway monitoring systems play an important role in transportation management and services owing to their powerful ability to extract a variety of information. Detection accuracy of vision-based systems is however sensitive to environmental factors such as lighting, shadow and weather conditions, and it is still a challenging problem to maintain detection robustness at all time. In this research, we present a novel method to enhance detection and tracking accuracy at the nighttime based on rear-view monitoring. In the meanwhile, a method is proposed to improve the background detection and extraction, which usually serves as the first step to moving object region detection. Finally, the effectiveness of the rear-view technique will be analyzed. We compare the tracking accuracy between the front-view and the rear-view techniques, and show that the proposed system can achieve higher detection accuracy at nighttime.

Original languageEnglish
Pages (from-to)21-32
Number of pages12
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume5203
DOIs
Publication statusPublished - 2003
Externally publishedYes
EventApplications of Digital Image Processing XXVI - San Diego, CA, United States
Duration: 2003 Aug 52003 Aug 8

Keywords

  • Background Maintenance
  • Background Subtraction
  • Nighttime Detection
  • Tracking
  • Traffic Monitoring

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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