Modified Crack Detection of Sewer Conduit with Low-Resolution Images

Imaging devices of less than 300,000 pixels are mostly used for sewage conduit exploration due to the petty nature of the survey industry in Korea. Particularly, devices of less than 100,000 pixels are still widely used, and the environment for image processing is very dim. Since the sewage conduit...

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Main Authors: Byung Jik Son, Taejun Cho
Format: Article
Language:English
Published: MDPI AG 2021-03-01
Series:Applied Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3417/11/5/2263
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spelling doaj-e99f619ecadd4e3e8ccb29e4a4cbc11d2021-03-05T00:02:03ZengMDPI AGApplied Sciences2076-34172021-03-01112263226310.3390/app11052263Modified Crack Detection of Sewer Conduit with Low-Resolution ImagesByung Jik Son0Taejun Cho1Department of Disaster Safety & Fire, Konyang University, Nonsan 32992, KoreaDepartment of Civil engineering, Daejin University, Pocheon 11159, KoreaImaging devices of less than 300,000 pixels are mostly used for sewage conduit exploration due to the petty nature of the survey industry in Korea. Particularly, devices of less than 100,000 pixels are still widely used, and the environment for image processing is very dim. Since the sewage conduit images covered in this study have a very low resolution (240 × 320 = 76,800 pixels), it is very difficult to detect cracks. Because most of the resolutions of the sewer conduit images are very low in Korea, this problem of low resolution was selected as the subject of this study. Cracks were detected through a total of six steps of improving the crack in Step 2, finding the optimal threshold value in Step 3, and applying an algorithm to detect cracks in Step 5. Cracks were effectively detected by the optimal parameters in Steps 2 and 3 and the user algorithm in Step 5. Despite the very low resolution, the cracked images showed a 96.4% accuracy of detection, and the non-cracked images showed 94.5% accuracy. Moreover, the analysis was excellent in quality. It is believed that the findings of this study can be effectively used for crack detection with low-resolution images.https://www.mdpi.com/2076-3417/11/5/2263image processinglow resolution imagecrack detectionuser algorithm
collection DOAJ
language English
format Article
sources DOAJ
author Byung Jik Son
Taejun Cho
spellingShingle Byung Jik Son
Taejun Cho
Modified Crack Detection of Sewer Conduit with Low-Resolution Images
Applied Sciences
image processing
low resolution image
crack detection
user algorithm
author_facet Byung Jik Son
Taejun Cho
author_sort Byung Jik Son
title Modified Crack Detection of Sewer Conduit with Low-Resolution Images
title_short Modified Crack Detection of Sewer Conduit with Low-Resolution Images
title_full Modified Crack Detection of Sewer Conduit with Low-Resolution Images
title_fullStr Modified Crack Detection of Sewer Conduit with Low-Resolution Images
title_full_unstemmed Modified Crack Detection of Sewer Conduit with Low-Resolution Images
title_sort modified crack detection of sewer conduit with low-resolution images
publisher MDPI AG
series Applied Sciences
issn 2076-3417
publishDate 2021-03-01
description Imaging devices of less than 300,000 pixels are mostly used for sewage conduit exploration due to the petty nature of the survey industry in Korea. Particularly, devices of less than 100,000 pixels are still widely used, and the environment for image processing is very dim. Since the sewage conduit images covered in this study have a very low resolution (240 × 320 = 76,800 pixels), it is very difficult to detect cracks. Because most of the resolutions of the sewer conduit images are very low in Korea, this problem of low resolution was selected as the subject of this study. Cracks were detected through a total of six steps of improving the crack in Step 2, finding the optimal threshold value in Step 3, and applying an algorithm to detect cracks in Step 5. Cracks were effectively detected by the optimal parameters in Steps 2 and 3 and the user algorithm in Step 5. Despite the very low resolution, the cracked images showed a 96.4% accuracy of detection, and the non-cracked images showed 94.5% accuracy. Moreover, the analysis was excellent in quality. It is believed that the findings of this study can be effectively used for crack detection with low-resolution images.
topic image processing
low resolution image
crack detection
user algorithm
url https://www.mdpi.com/2076-3417/11/5/2263
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