Real-time multiple-vehicle detection and tracking system in complex environment with automatic lane detection and reducing shadow effects

Bing-Fei Wu*, Jhy Hong Juang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

In this study, an real-time multiple-vehicle detection and tracking system in complex environments with automatic lane detection and reducing shadow effects is proposed. First, lane marks can be automatically detected, and this automation makes the proposed system more possible to deploy in the practical traffic conditions. Second, Histogram Extension (HE) addresses how to remove the effects of weather and light impact. Next, vehicle detection with Merge Boundary Rectangle Rule (MBRR) is utilized to merge fractions of moving objects which may be candidates of detected vehicles. Finally, traffic parameters are built based on a proper tracking procedure with reducing shadow effects. Experimental results show that the proposed methods are robust, accurate, and powerful to overcome complex weather conditions and traffic jams.

Original languageEnglish
Title of host publicationProceedings - 1st International Conference on Robot, Vision and Signal Processing, RVSP 2011
Pages23-26
Number of pages4
DOIs
StatePublished - 1 Dec 2011
Event1st International Conference on Robot, Vision and Signal Processing, RVSP 2011 - Kaohsiung, Taiwan
Duration: 21 Nov 201123 Nov 2011

Publication series

NameProceedings - 1st International Conference on Robot, Vision and Signal Processing, RVSP 2011

Conference

Conference1st International Conference on Robot, Vision and Signal Processing, RVSP 2011
Country/TerritoryTaiwan
CityKaohsiung
Period21/11/1123/11/11

Keywords

  • Queue
  • Shadow
  • Tracking
  • Traffic jam
  • Vehicle detection

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