Classification of road traffic conditions based on texture features of traffic images using neural networks

The paper presents a method of classification of road traffic conditions based on the analysis of the content of images of the traffic flow. The view of the traffic lanes with vehicles is treated as a texture, while the change in the description of its characteristics is ascribed to the change in the density of traffic. Four classes of conditions are determined on the basis of the values of Haralick texture features. An MLP network is used for classification. Video data, which were registered by an UAV hanging over a traffic junction, are used for validation of the method.

• Record URL:
  https://doi.org/10.20858/sjsutst.2016.92.10
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/02093324
• Supplemental Notes:
  • © 2016 Teresa Pamuła.
• Authors:
  • Pamuła, Teresa
• Publication Date: 2016

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; Photos; References; Tables;
• Pagination: pp 101-109
• Serial:
  • Scientific Journal of Silesian University of Technology. Series Transport
  • Volume: 92
  • Publisher: Silesian University of Technology
  • ISSN: 0209-3324
  • EISSN: 2450-1549
  • Serial URL: https://doi.org/10.20858/sjsutst
• Publication flags:

  Open Access (libre)

Subject/Index Terms

• TRT Terms: Imagery; Neural networks; Texture; Traffic characteristics; Traffic lanes
• Subject Areas: Highways; Operations and Traffic Management;

Filing Info

• Accession Number: 01631560
• Record Type: Publication
• Files: TRIS
• Created Date: Mar 30 2017 11:48AM