Vehicle Type Recognition Based on Harris Corner Detector

With the development of computer technology in recent years, video-based detection technology in the intelligent transportation system has been widely used, this article uses a identification method based on the Harris corner detection for rapid and accurate identification. First of all, extract moving goal vehicles of the video, and then extract its Harris corners in gray image, and select the Harris corner of cars, buses and lorries as standard samples. Then the Hausdorff distance are calculated of Harris corner between the standard types and the swatches which need to be recognized. The two whose Hausdorff distance is smallest can be judged as the same type. Experiment results show that the method is accurate, effective and better real-time.

• Record URL:
  https://doi.org/10.1061/41039(345)547
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/isbn/9780784410394
• Supplemental Notes:
  • © 2009 American Society of Civil Engineers.
• Corporate Authors:

  American Society of Civil Engineers

  1801 Alexander Bell Drive
  Reston, VA  United States  20191-4400
• Authors:
  • Li, Jian
  • Zhao, Wangzi
  • Guo, Hui
• Conference:
  • Second International Conference on Transportation Engineering
  • Location: Chengdu , China
  • Date: 2009-7-25 to 2009-7-27
• Publication Date: 2009-7

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References; Tables;
• Pagination: pp 3320-3325
• Monograph Title: International Conference on Transportation Engineering 2009

Subject/Index Terms

• TRT Terms: Automatic vehicle detection and identification systems; Computer vision; Image analysis; Intelligent transportation systems; Pattern recognition systems; Vehicle detectors; Video imaging detectors
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; Vehicles and Equipment; I72: Traffic and Transport Planning; I90: Vehicles;

Filing Info

• Accession Number: 01534561
• Record Type: Publication
• ISBN: 9780784410394
• Files: TRIS, ASCE
• Created Date: Nov 12 2013 1:43PM