Quarterly Report of RTRI
Online ISSN : 1880-1765
Print ISSN : 0033-9008
ISSN-L : 0033-9008
PAPERS
Tunnel Lining Crack Detection Method by Means of Deep Learning
Masato UKAI
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2019 年 60 巻 1 号 p. 33-39

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Existing image processing programs for detecting structural damage such as cracks have required the fine-tuning of numerous parameters and experience-based expertise. A method for distinguishing different types of cracks applying deep learning has been developed using tunnel lining images. A classifier was created after learning from a large volume of images in two groups - either with "presence of a crack" or "absence of a crack." The classifier successfully recognized the presence or absence of cracks in images at a rate of more than 90%. Using a color-coded pixelated image to show the position of probable cracks, this paper proposes a hybrid detection method for analyzing cracks with a focus on their location and direction of progress.

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© 2019 by Railway Technical Research Institute
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