Vehicle Segmentation from Video Using Color and Edges

Intelligent transportation systems or ITS play a very important role in traffic management. Traffic congestion is widespread in big cities. The key success factor of traffic management is accurate traffic data collection. Traffic video processing is a widely used technique in traffic data collection. However, the changes in environment where traffic video is collected can adversely affect the reliability of the traffic video processing results. In this paper, a robust vehicle segmentation approach is presented. An improvement to color-based statistical background subtraction is proposed. It is shown that improvement in reliability and robustness to lighting changes in different camera views can be achieved when compared to results from conventional techniques.

• Corporate Authors:

  ITS Japan

  Tokyo,   Japan 

  ITS America

  1100 17th Street, NW, 12th Floor
  Washington, DC  United States  20036

  ERTICO

  326 Avenue Louis
  Brussels,   Belgium  B-1050
• Authors:
  • Siricharoen, Punnarai
  • Aramvith, Supavadee
  • Siddhichai, Supakorn
  • Chalidabhongse, Thanarat
• Conference:
  • 17th ITS World Congress
  • Location: Busan , Korea, South
  • Date: 2010-10-25 to 2010-10-29
• Publication Date: 2010

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References; Tables;
• Pagination: 12p
• Monograph Title: 17th ITS World Congress, Busan, 2010: Proceedings

Subject/Index Terms

• TRT Terms: Algorithms; Color; Data collection; Edge detection; Intelligent transportation systems; Traffic data; Video cameras
• Subject Areas: Data and Information Technology; Highways; I90: Vehicles;

Filing Info

• Accession Number: 01352734
• Record Type: Publication
• Files: TRIS
• Created Date: Sep 28 2011 9:20AM