Image-Based Concrete Crack Detection Using Convolutional Neural Network and Exhaustive Search Technique
Joint Authors
Source
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-04-30
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
Crack detection is important for the inspection and evaluation during the maintenance of concrete structures.
However, conventional image-based methods need extract crack features using complex image preprocessing techniques, so it can lead to challenges when concrete surface contains various types of noise due to extensively varying real-world situations such as thin cracks, rough surface, shadows, etc.
To overcome these challenges, this paper proposes an image-based crack detection method using a deep convolutional neural network (CNN).
A CNN is designed through modifying AlexNet and then trained and validated using a built database with 60000 images.
Through comparing validation accuracy under different base learning rates, 0.01 was chosen as the best base learning rate with the highest validation accuracy of 99.06%, and its training result is used in the following testing process.
The robustness and adaptability of the trained CNN are tested on 205 images with 3120 × 4160 pixel resolutions which were not used for training and validation.
The trained CNN is integrated into a smartphone application to mobile more public to detect cracks in practice.
The results confirm that the proposed method can indeed detect cracks in images from real concrete surfaces.
American Psychological Association (APA)
Li, Shengyuan& Zhao, Xue-Feng. 2019. Image-Based Concrete Crack Detection Using Convolutional Neural Network and Exhaustive Search Technique. Advances in Civil Engineering،Vol. 2019, no. 2019, pp.1-12.
https://search.emarefa.net/detail/BIM-1116757
Modern Language Association (MLA)
Li, Shengyuan& Zhao, Xue-Feng. Image-Based Concrete Crack Detection Using Convolutional Neural Network and Exhaustive Search Technique. Advances in Civil Engineering No. 2019 (2019), pp.1-12.
https://search.emarefa.net/detail/BIM-1116757
American Medical Association (AMA)
Li, Shengyuan& Zhao, Xue-Feng. Image-Based Concrete Crack Detection Using Convolutional Neural Network and Exhaustive Search Technique. Advances in Civil Engineering. 2019. Vol. 2019, no. 2019, pp.1-12.
https://search.emarefa.net/detail/BIM-1116757
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1116757