Real-time Road Congestion Detection Based on Image Texture Analysis

Proposed is a fast detection algorithm for urban road traffic congestion based on image processing technology. Firstly, to speed up the processing and to freely select the interesting area, the human-computer interaction vehicle area detection was put forward. Then, by using the difference of texture features between congestion image and unobstructed image, vehicle density estimation based on texture analysis is proposed. Through image grayscale relegation, gray level co-occurrence matrix calculation and feature extraction, the energy and entropy features that could reflect vehicle density were obtained from vehicle area. After features training, the decision threshold could be obtained and traffic congestion was carried out. Experimental results showed that the accuracy of the algorithm was as high as 99%, and the processing speed could satisfy the real-time requirement in engineering.

• Record URL:
  https://doi.org/10.1016/j.proeng.2016.01.250
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S1877705816002630
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/18777058
• Supplemental Notes:
  • © 2016 Li Wei and Dai Hong-ying. Published by Elsevier Ltd.
• Authors:
  • Wei, Li
  • Hong-ying, Dai
• Conference:
  • 6th International Conference on Green Intelligent Transportation System and Safety (GITSS2015)
  • Location: Beijing , China
  • Date: 2015-7-2 to 2015-7-4
• Publication Date: 2016

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; Photos; References;
• Pagination: pp 196-201
• Serial:
  • Procedia Engineering
  • Volume: 137
  • Publisher: Elsevier
  • ISSN: 1877-7058
  • Serial URL: http://www.sciencedirect.com/science/journal/18777058
• Publication flags:

  Open Access (libre)

Subject/Index Terms

• TRT Terms: Algorithms; Detection and identification; Image processing; Real time data processing; Traffic congestion; Traffic density; Traffic surveillance; Video cameras; Visual texture recognition
• Uncontrolled Terms: Grayscale
• Subject Areas: Highways; Operations and Traffic Management;

Filing Info

• Accession Number: 01607507
• Record Type: Publication
• Files: TRIS
• Created Date: Jul 5 2016 2:41PM