Adaptive road crack detection system by pavement classification

A road distress detection system involving the phases needed to properly deal with fully automatic road distress assessment is presented in this paper. A vehicle equipped with line scan cameras, laser illumination and acquisition HW-SW is used to store the digital images that will be further processed to identify road cracks. Pre-processing is first carried out to smooth the texture and enhance the linear features. Non-crack features detection is then applied to mask areas of the images with joints, sealed cracks and white paint, features that usually generate false positive cracking. A seed-based approach is proposed to deal with road crack detection, combining Multiple Directional Non-Minimum Suppression (MDNMS) with a symmetry check. Seeds are linked by computing the paths with the lowest cost that meet the symmetry restrictions. The whole detection process involves the use of several parameters. A correct setting becomes essential to get optimal results without manual intervention. A fully automatic approach by means of a linear SVM-based classifier ensemble able to distinguish between up to 10 different types of pavement that appear in Spanish roads is proposed. The optimal feature vector includes different texture-based features. The parameters are then tuned depending on the output provided by the classifier. Regarding non-crack features detection, results show that the introduction of such module reduces the impact of false positives due to non-crack features up to a factor of 2. In addition, the observed performance of the crack detection system is significantly boosted by adapting the parameters to the type of pavement.

• Record URL:
  http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3231249/?tool=pubmed
• Record URL:
  http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3231249/pdf/sensors-11-09628.pdf
• 
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/14248220
• Authors:
  • Gavilan, Miguel
  • Balcones, David
  • Marcos, Oscar
  • Llorca, David F
  • Sotelo, Miguel A
  • Parra, Ignacio
  • Ocana, Manuel
  • Aliseda, Pedro
  • Yarza, Pedro
  • Amirola, Alejandro
• Publication Date: 2011

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References; Tables;
• Pagination: pp 9628-9657
• Serial:
  • Sensors
  • Volume: 11
  • Issue Number: 10
  • Publisher: MDPI AG
  • ISSN: 1424-8220
  • Serial URL: http://www.mdpi.com/journal/sensors
• Publication flags:

  Open Access (libre)

Subject/Index Terms

• TRT Terms: Condition surveys; Flaw detection; Image analysis; Pavement cracking; Pavement distress; Pavement management systems; Structural health monitoring
• Geographic Terms: Spain
• Subject Areas: Highways; Maintenance and Preservation; Pavements; I61: Equipment and Maintenance Methods;

Filing Info

• Accession Number: 01372713
• Record Type: Publication
• Files: TRIS
• Created Date: Jun 15 2012 4:03PM