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Automated Vision-Based Detection of Cracks on Concrete Surfaces Using a Deep Learning Technique

Department of Civil Engineering, University of Seoul, Seoul 02504, Korea
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Sensors 2018, 18(10), 3452; https://doi.org/10.3390/s18103452
Received: 17 September 2018 / Revised: 10 October 2018 / Accepted: 11 October 2018 / Published: 14 October 2018
(This article belongs to the Section Physical Sensors)
At present, a number of computer vision-based crack detection techniques have been developed to efficiently inspect and manage a large number of structures. However, these techniques have not replaced visual inspection, as they have been developed under near-ideal conditions and not in an on-site environment. This article proposes an automated detection technique for crack morphology on concrete surface under an on-site environment based on convolutional neural networks (CNNs). A well-known CNN, AlexNet is trained for crack detection with images scraped from the Internet. The training set is divided into five classes involving cracks, intact surfaces, two types of similar patterns of cracks, and plants. A comparative study evaluates the successfulness of the detailed surface categorization. A probability map is developed using a softmax layer value to add robustness to sliding window detection and a parametric study was carried out to determine its threshold. The applicability of the proposed method is evaluated on images taken from the field and real-time video frames taken using an unmanned aerial vehicle. The evaluation results confirm the high adoptability of the proposed method for crack inspection in an on-site environment. View Full-Text
Keywords: crack; deep learning; convolutional neural networks; AlexNet; unmanned aerial vehicle crack; deep learning; convolutional neural networks; AlexNet; unmanned aerial vehicle
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MDPI and ACS Style

Kim, B.; Cho, S. Automated Vision-Based Detection of Cracks on Concrete Surfaces Using a Deep Learning Technique. Sensors 2018, 18, 3452. https://doi.org/10.3390/s18103452

AMA Style

Kim B, Cho S. Automated Vision-Based Detection of Cracks on Concrete Surfaces Using a Deep Learning Technique. Sensors. 2018; 18(10):3452. https://doi.org/10.3390/s18103452

Chicago/Turabian Style

Kim, Byunghyun, and Soojin Cho. 2018. "Automated Vision-Based Detection of Cracks on Concrete Surfaces Using a Deep Learning Technique" Sensors 18, no. 10: 3452. https://doi.org/10.3390/s18103452

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