Pavement Crack Automatic Recognition Based on Wiener Filtering

System principle and composition including image acquisition, image processing and image interpretation for pavement crack automatic recognition based on digital image processing are presented. In order to improve crack identification rate, pavement image retrogression reasons are introduced and stochastic and complex characteristics for pavement images are analyzed. Wiener filtering theory is investigated to overcome the problem that some classical methods will weaken useful image details when restrain noise. Results show that Wiener filtering can preserve image edge information and remove some noise from non-uniform illumination, imaging systems, pavement material and grain's texture through the analysis for representative examples.

• Record URL:
  • https://doi.org/10.1061/41064(358)370
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/isbn/9780784410646
• Supplemental Notes:
  • © 2009 American Society of Civil Engineers.
• Corporate Authors:

  American Society of Civil Engineers

  1801 Alexander Bell Drive
  Reston, VA  United States  20191-4400
• Authors:
  • Zhang, J
  • Sha, A
  • Sun, Z Y
  • Gao, H G
• Conference:
  • Ninth International Conference of Chinese Transportation Professionals (ICCTP)
  • Location: Harbin China, United States
  • Date: 2009-8-5 to 2009-8-9
• Publication Date: 2009

Language

• English

Media Info

• Media Type: Web
• Pagination: pp 1-7
• Monograph Title: ICCTP 2009: Critical Issues In Transportation Systems Planning, Development, and Management

Subject/Index Terms

• TRT Terms: Detection and identification; Image processing; Pavement cracking; Structural health monitoring
• Subject Areas: Highways; Pavements;

Filing Info

• Accession Number: 01923891
• Record Type: Publication
• ISBN: 9780784410646
• Files: TRIS, ASCE
• Created Date: Jul 8 2024 5:24PM