Version 1
: Received: 16 January 2021 / Approved: 18 January 2021 / Online: 18 January 2021 (14:26:38 CET)
How to cite:
Son, B.J.; Cho, T. Modified Crack Detection of Sewer Conduit with Low Resolution Images. Preprints2021, 2021010345. https://doi.org/10.20944/preprints202101.0345.v1
Son, B.J.; Cho, T. Modified Crack Detection of Sewer Conduit with Low Resolution Images. Preprints 2021, 2021010345. https://doi.org/10.20944/preprints202101.0345.v1
Son, B.J.; Cho, T. Modified Crack Detection of Sewer Conduit with Low Resolution Images. Preprints2021, 2021010345. https://doi.org/10.20944/preprints202101.0345.v1
APA Style
Son, B.J., & Cho, T. (2021). Modified Crack Detection of Sewer Conduit with Low Resolution Images. Preprints. https://doi.org/10.20944/preprints202101.0345.v1
Chicago/Turabian Style
Son, B.J. and Taejun Cho. 2021 "Modified Crack Detection of Sewer Conduit with Low Resolution Images" Preprints. https://doi.org/10.20944/preprints202101.0345.v1
Abstract
Abstract: 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. P articular ly , devices of less than 100,000 pixels are still widely used, and the environment for image processing is very bitter . Since the sewage conduit image s covered in this study ha ve a very low resolution (240 × 320 = 76,800 pixels), it is very difficult to detect cracks. Because most of the resolution of the sewe r conduit images are very low in Korea, this problem of low resolution was selected as the subject of 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. Desp ite the very low resolution, the cracked image s showed 96.4% accuracy of detection, and the non cracked image s showed 94.5% accuracy . Moreover, the analysis was excellent in quality , also . It is believed that the findings of this study can be effectively u sed for crack detection with low resolution images.
Keywords
image processing; low resolution image; crack detection; user algorithm
Subject
Computer Science and Mathematics, Computer Science
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
