Using Wavelet Technology for Pavement Crack Detection

Edge detection is an alternative method in the process for identifying and classifying pavement cracks for automated pavement management systems. This paper presents a new approach in automation for crack detection on pavement surface images using wavelet technology. Firstly, a separable two dimensional (2D) continuous wavelet transform for several scales is performed. Secondly, wavelet coefficients maximal values are searched through scales. Thirdly, in order to analyze wavelet coefficients maximal values in a window, cracks edges are detected and background noise is deleted. In addition, the paper invents an evolution of edge detection arithmetic to obtain better detection effect. Finally, a simple threshold is employed to indicate the presence of cracks on the pavement surface image. The results of experiments on images demonstrate the validity and effectiveness of this method for edge detection of pavement surface distresses.

• Record URL:
  https://doi.org/10.1061/41139(387)346
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/isbn/9780784411391
• Supplemental Notes:
  • © 2010 American Society of Civil Engineers.
• Corporate Authors:

  American Society of Civil Engineers

  1801 Alexander Bell Drive
  Reston, VA  United States  20191-4400
• Authors:
  • Liang, Shiqing
  • Sun, Bocheng
• Conference:
  • International Conference of Logistics Engineering and Management (ICLEM) 2010
  • Location: Chengdu , China
  • Date: 2010-10-8 to 2010-10-10
• Publication Date: 2010-9

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 2479-2484
• Monograph Title: ICLEM 2010: Logistics For Sustained Economic Development: Infrastructure, Information, Integration

Subject/Index Terms

• TRT Terms: Cracking; Edge detection; Noise; Pavement distress; Pavement management systems; Ride quality; Texture; Wavelets
• Subject Areas: Highways; Maintenance and Preservation; Pavements; I60: Maintenance;

Filing Info

• Accession Number: 01525596
• Record Type: Publication
• ISBN: 9780784411391
• Files: TRIS, ASCE
• Created Date: Nov 12 2013 1:51PM