Background segmentation and its application to traffic monitoring using modified histogram

Jen Chao Tai*, Kai-Tai Song

*Corresponding author for this work

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

15 Scopus citations

Abstract

This paper presents a novel algorithm for background extraction and its application to vision-based traffic monitoring. A modified histogram algorithm is proposed to obtain reliable pixel intensity of background image. After background removal, moving objects can be segmented from the current image via a robust threshold operation. The threshold value is assigned through a measure of illumination variation. We applied the proposed method to a vision-based traffic monitoring system to segment moving vehicles from traffic image sequences. Given degraded on-line traffic images from compressed image transmission, vehicles are successfully segmented from the image frame. We employed a detection window, which behaves like loop detectors, to count the vehicles at a multi-lane intersection. Experimental results demonstrate that traffic flow can be obtained in real time.

Original languageEnglish
Title of host publicationConference Proceedings - 2004 IEEE International Conference on Networking, Sensing and Control
Pages13-18
Number of pages6
DOIs
StatePublished - 28 Jun 2004
EventConference Proceeding - 2004 IEEE International Conference on Networking, Sensing and Control - Taipei, Taiwan
Duration: 21 Mar 200423 Mar 2004

Publication series

NameConference Proceeding - IEEE International Conference on Networking, Sensing and Control
Volume1

Conference

ConferenceConference Proceeding - 2004 IEEE International Conference on Networking, Sensing and Control
CountryTaiwan
CityTaipei
Period21/03/0423/03/04

Keywords

  • Background extraction
  • Detection window
  • Modified histogram
  • Traffic monitoring
  • Traffic parameters

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