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Crack Detection Method on Surface of Tunnel Lining
- Authors
- Han, Jeong hoon; Cho, Yong chae; Lee, Ho gyeng; Yang, Hyeon seok; Jeong, Woo jin; Moon, Young shik
- Issue Date
- Jun-2019
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Keywords
- Concrete Inspection; Convolutional Neural Network; Crack Detection; Tunnel Inspection
- Citation
- 34th International Technical Conference on Circuits/Systems, Computers and Communications, ITC-CSCC 2019, pp 134 - 136
- Pages
- 3
- Indexed
- OTHER
- Journal Title
- 34th International Technical Conference on Circuits/Systems, Computers and Communications, ITC-CSCC 2019
- Start Page
- 134
- End Page
- 136
- Abstract
- Crack detection on surface of tunnel lining is one of the most important tasks in concrete structure inspection field. Naked eye inspection method is widely used in general but it needs huge resources. To solve the issue, many methods have been proposed based on convolutional neural network but they show disconnected crack results with thin or blurred crack image. To overcome this problem, we propose a multiscale feature fusion method for crack detection. Experientially, results show that performance of our method was improved over the previous methods. © 2019 IEEE.
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