Application of Morphological Segmentation to Leaking Defect Detection in Sewer Pipelines
As one of major underground pipelines, sewerage is an important infrastructure in any modern city. The most common problem occurring in sewerage is leaking, whose position and failure level is typically identified through closed circuit television (CCTV) inspection in order to facilitate rehabilitat...
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| Format: | Article |
| Language: | English |
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MDPI AG
2014-05-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1424-8220/14/5/8686 |
| _version_ | 1828358942076436480 |
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| author | Tung-Ching Su Ming-Der Yang |
| author_facet | Tung-Ching Su Ming-Der Yang |
| author_sort | Tung-Ching Su |
| collection | DOAJ |
| description | As one of major underground pipelines, sewerage is an important infrastructure in any modern city. The most common problem occurring in sewerage is leaking, whose position and failure level is typically identified through closed circuit television (CCTV) inspection in order to facilitate rehabilitation process. This paper proposes a novel method of computer vision, morphological segmentation based on edge detection (MSED), to assist inspectors in detecting pipeline defects in CCTV inspection images. In addition to MSED, other mathematical morphology-based image segmentation methods, including opening top-hat operation (OTHO) and closing bottom-hat operation (CBHO), were also applied to the defect detection in vitrified clay sewer pipelines. The CCTV inspection images of the sewer system in the 9th district, Taichung City, Taiwan were selected as the experimental materials. The segmentation results demonstrate that MSED and OTHO are useful for the detection of cracks and open joints, respectively, which are the typical leakage defects found in sewer pipelines. |
| first_indexed | 2024-04-14T03:35:32Z |
| format | Article |
| id | doaj.art-44258b0ed9aa4e0d8bcbd11d46831f03 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-14T03:35:32Z |
| publishDate | 2014-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-44258b0ed9aa4e0d8bcbd11d46831f032022-12-22T02:14:47ZengMDPI AGSensors1424-82202014-05-011458686870410.3390/s140508686s140508686Application of Morphological Segmentation to Leaking Defect Detection in Sewer PipelinesTung-Ching Su0Ming-Der Yang1Department of Civil Engineering and Engineering Management, National Quemoy University, Da Xue Rd. 1, Kinmen 892, TaiwanDepartment of Civil Engineering, National Chung Hsing University, Taichung 402, TaiwanAs one of major underground pipelines, sewerage is an important infrastructure in any modern city. The most common problem occurring in sewerage is leaking, whose position and failure level is typically identified through closed circuit television (CCTV) inspection in order to facilitate rehabilitation process. This paper proposes a novel method of computer vision, morphological segmentation based on edge detection (MSED), to assist inspectors in detecting pipeline defects in CCTV inspection images. In addition to MSED, other mathematical morphology-based image segmentation methods, including opening top-hat operation (OTHO) and closing bottom-hat operation (CBHO), were also applied to the defect detection in vitrified clay sewer pipelines. The CCTV inspection images of the sewer system in the 9th district, Taichung City, Taiwan were selected as the experimental materials. The segmentation results demonstrate that MSED and OTHO are useful for the detection of cracks and open joints, respectively, which are the typical leakage defects found in sewer pipelines.http://www.mdpi.com/1424-8220/14/5/8686leakingsewer pipelinecomputer visiondefect detectionmorphology |
| spellingShingle | Tung-Ching Su Ming-Der Yang Application of Morphological Segmentation to Leaking Defect Detection in Sewer Pipelines Sensors leaking sewer pipeline computer vision defect detection morphology |
| title | Application of Morphological Segmentation to Leaking Defect Detection in Sewer Pipelines |
| title_full | Application of Morphological Segmentation to Leaking Defect Detection in Sewer Pipelines |
| title_fullStr | Application of Morphological Segmentation to Leaking Defect Detection in Sewer Pipelines |
| title_full_unstemmed | Application of Morphological Segmentation to Leaking Defect Detection in Sewer Pipelines |
| title_short | Application of Morphological Segmentation to Leaking Defect Detection in Sewer Pipelines |
| title_sort | application of morphological segmentation to leaking defect detection in sewer pipelines |
| topic | leaking sewer pipeline computer vision defect detection morphology |
| url | http://www.mdpi.com/1424-8220/14/5/8686 |
| work_keys_str_mv | AT tungchingsu applicationofmorphologicalsegmentationtoleakingdefectdetectioninsewerpipelines AT mingderyang applicationofmorphologicalsegmentationtoleakingdefectdetectioninsewerpipelines |