Pavement Crack Detection Using Sketch Token

Due to the serious threats to road safety caused by pavement distress, it has drawn much attention to seek efficient road crack detection methods for automatic pavement condition evaluation. In recent detectors, structure information of cracks has not been utilized effectively, which leads to the high sensitivity to crack-like noises. In this paper, the authors propose a novel crack detection method to recognize cracks out of noises. They verified their method in a real pavement crack dataset. Extensive experiments demonstrate the state-of-the-art results of the proposed method.

• Record URL:
  • https://doi.org/10.1016/j.procs.2018.10.231
• Record URL:
  • http://www.sciencedirect.com/science/article/pii/S1877050918319008
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/18770509
• Supplemental Notes:
  • © 2018 Fan Meng and Aihua Li. Published by Elsevier B.V. Abstract reprinted with permission of Elsevier.
• Authors:
  • Meng, Fan
  • Li, Aihua
• Publication Date: 2018

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 151-157
• Serial:
  • Procedia Computer Science
  • Volume: 139
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 1877-0509
  • Serial URL: http://www.sciencedirect.com/science/journal/18770509
• Publication flags:

  Open Access (libre)

Subject/Index Terms

• TRT Terms: Cracking; Highway safety; Pavement distress; Structural health monitoring
• Subject Areas: Construction; Highways; Pavements;

Filing Info

• Accession Number: 01687082
• Record Type: Publication
• Files: TRIS
• Created Date: Nov 27 2018 9:25AM