Concrete Crack Width Measurement Using a Laser Beam and Image Processing Algorithms

Mthabisi Nyathi, Jiping Bai*, Ian Wilson

*Corresponding author for this work

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Abstract

The presence of concrete cracks in structures indicates possible structural deterioration, but it is quite difficult to measure crack width accurately. While much research has been conducted on crack detection using image processing, there is a gap in the accurate quantification of crack width in millimeters. Current methods either measure in pixels or require the attachment of scales or markers onto a measured surface, which can pose safety hazards in hard-to-reach areas. This paper addresses these issues by proposing a novel image-based method for measuring concrete crack width in millimeters using a laser beam and image processing. The proposed method was validated in the laboratory by capturing images of concrete cracks with two cameras of different resolutions, each attached with lasers. The lasers projected a circular laser beam onto the surface of the concrete under inspection. The images were then pre-processed, segmented, and skeletonized for crack width measurement in pixels. The relationship between the laser diameter and camera distance from the surface was used to convert the measured crack width from pixels to millimeters. The method was performed with high accuracy, as indicated by the absolute error. The largest absolute error was 0.57 mm, while the smallest absolute error was 0.02 mm. The proposed method allows real-world interpretation of results in millimeters. As a result, measured crack widths can easily be compared to allowable limits in international standards, which are typically expressed in metric or SI units. The proposed method can also promote safer inspections in areas of low accessibility by attaching the laser to devices such as drones.
Original languageEnglish
Article number4981
Number of pages13
JournalApplied Sciences
Volume13
Issue number8
DOIs
Publication statusPublished - 15 Apr 2023

Keywords

  • crack detection
  • crack width measurement
  • laser beam
  • image processing

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  • Road Defect Detection Using Deep Learning

    Nyathi, M., Bai, J. & Wilson, I., 5 Sept 2024, Proceedings of the Twelfth International Conference on Engineering Computational Technology. Iványi, P., Kruis, J. & Topping, B. H. V. (eds.). Edinburgh: Civil-Comp Press, Vol. 8. 7 p. 4.4. (Civil-Comp Conferences; vol. 8).

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