Version 1
: Received: 31 October 2024 / Approved: 1 November 2024 / Online: 1 November 2024 (13:49:24 CET)
How to cite:
Abdelalim, A. M.; Shalaby, Y.; Salem, M.; Al-Adwani, M.; EBRAHIM, G. A.; Badawy, M. Automated Vision-Based Crack Detection for Reinforced Concrete Bridges Using Matlab Algorithms. Preprints2024, 2024110078. https://doi.org/10.20944/preprints202411.0078.v1
Abdelalim, A. M.; Shalaby, Y.; Salem, M.; Al-Adwani, M.; EBRAHIM, G. A.; Badawy, M. Automated Vision-Based Crack Detection for Reinforced Concrete Bridges Using Matlab Algorithms. Preprints 2024, 2024110078. https://doi.org/10.20944/preprints202411.0078.v1
Abdelalim, A. M.; Shalaby, Y.; Salem, M.; Al-Adwani, M.; EBRAHIM, G. A.; Badawy, M. Automated Vision-Based Crack Detection for Reinforced Concrete Bridges Using Matlab Algorithms. Preprints2024, 2024110078. https://doi.org/10.20944/preprints202411.0078.v1
APA Style
Abdelalim, A. M., Shalaby, Y., Salem, M., Al-Adwani, M., EBRAHIM, G. A., & Badawy, M. (2024). Automated Vision-Based Crack Detection for Reinforced Concrete Bridges Using Matlab Algorithms. Preprints. https://doi.org/10.20944/preprints202411.0078.v1
Chicago/Turabian Style
Abdelalim, A. M., GAMAL A. EBRAHIM and Mohamed Badawy. 2024 "Automated Vision-Based Crack Detection for Reinforced Concrete Bridges Using Matlab Algorithms" Preprints. https://doi.org/10.20944/preprints202411.0078.v1
Abstract
Measuring the crack width is one of the important defect properties to estimate the bridge’s health. Cracks may develop into catastrophic failures with expensive consequences for both human life and the economy if they are ignored and are allowed to get worse. Nevertheless, the traditional tools to measure crack width are suffering from time-consuming and some limitations related to subjectivity and uncertainty. In view of this, this paper presented a model based on image processing techniques to measure crack width. The proposed technique relies on developing a model that is used for crack detection to be able to measure their maximum width. Two types of datasets are used in the presented models, and these images were taken from two different types of cameras. The precision and recall for the crack detection achieved 98.32% and 99.43% respectively. Accordingly, 87 concrete crack widths are measured by traditional tools and compared with model results. The comparison shows that the minimum crack width measured by the model is 0.5 mm and the mean absolute error is 0.046 mm. The model is compared with previous studies and demonstrated its effectiveness in measuring crack width. The results show the adequacy of the crack measurement method for safety bridge assessments and to avoid working in hazardous conditions for a long time.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
