Detection and recognition of urban road markings using images

While road lane markings detection was extensively studied, in particular for intelligent vehicle applications, the detection and recognition of all kinds of markings such as arrows, crosswalks, zebras, words, pictograms, continuous and discontinuous lane markings was drastically less studied. However, it has many potential applications in the design of advanced driver assistance systems, as well as for asset management along itineraries. An algorithm is proposed which is based on the following processing steps: marking pixel extraction, detection using connected components before Inverse Perspective Mapping and recognition based on the comparison with a single pattern or with repetitive rectangular patterns. The proposed algorithm is able to detect and recognize repetitive markings (such as crosswalks) as well as single patterns (such as arrows). The authors believe that the proposed algorithm can be extended easily to solve the problem of the identification of all types of markings.

• Record URL:
  https://doi.org/10.1109/ITSC.2011.6082840
• Availability:
  • Find a library where document is available. Order URL: http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6069628
• Supplemental Notes:
  • Abstract reprinted with permission of IEEE.
• Corporate Authors:

  Institute of Electrical and Electronics Engineers (IEEE)

  3 Park Avenue, 17th Floor
  New York, NY  United States  10016-5997
• Authors:
  • Foucher, P
  • Sebsadji, Y
  • Tarel, J-P
  • Charbonnier, P
  • Nicolle, P
• Conference:
  • 14th International IEEE Conference on Intelligent Transportation Systems (ITSC 2011)
  • Location: Washington DC, United States
  • Date: 2011-10-5 to 2011-10-7
• Publication Date: 2011-10

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 1747-1752
• Monograph Title: 14th International IEEE Conference on Intelligent Transportation Systems (ITSC 2011)

Subject/Index Terms

• TRT Terms: Algorithms; Asset management; Computer vision; Detection and identification; Driver support systems; Intelligent vehicles; Road markings
• Subject Areas: Data and Information Technology; Highways; Vehicles and Equipment; I91: Vehicle Design and Safety;

Filing Info

• Accession Number: 01565959
• Record Type: Publication
• ISBN: 9781457721984
• Files: TRIS
• Created Date: Jun 6 2015 4:30PM