Full metadata record
DC Field | Value | Language |
---|---|---|
dc.citation.number | 10 | - |
dc.citation.startPage | 2317 | - |
dc.citation.title | SENSORS | - |
dc.citation.volume | 17 | - |
dc.contributor.author | Lee, Junhwa | - |
dc.contributor.author | Lee, Kyoung-Chan | - |
dc.contributor.author | Cho, Soojin | - |
dc.contributor.author | Sim, Sung-Han | - |
dc.date.accessioned | 2023-12-21T21:40:30Z | - |
dc.date.available | 2023-12-21T21:40:30Z | - |
dc.date.created | 2017-12-14 | - |
dc.date.issued | 2017-10 | - |
dc.description.abstract | The displacement responses of a civil engineering structure can provide important information regarding structural behaviors that help in assessing safety and serviceability. A displacement measurement using conventional devices, such as the linear variable differential transformer (LVDT), is challenging owing to issues related to inconvenient sensor installation that often requires additional temporary structures. A promising alternative is offered by computer vision, which typically provides a low-cost and non-contact displacement measurement that converts the movement of an object, mostly an attached marker, in the captured images into structural displacement. However, there is limited research on addressing light-induced measurement error caused by the inevitable sunlight in field-testing conditions. This study presents a computer vision-based displacement measurement approach tailored to a field-testing environment with enhanced robustness to strong sunlight. An image-processing algorithm with an adaptive region-of-interest (ROI) is proposed to reliably determine a marker's location even when the marker is indistinct due to unfavorable light. The performance of the proposed system is experimentally validated in both laboratory-scale and field experiments. | - |
dc.identifier.bibliographicCitation | SENSORS, v.17, no.10, pp.2317 | - |
dc.identifier.doi | 10.3390/s17102317 | - |
dc.identifier.issn | 1424-8220 | - |
dc.identifier.scopusid | 2-s2.0-85032857576 | - |
dc.identifier.uri | https://scholarworks.unist.ac.kr/handle/201301/23100 | - |
dc.identifier.url | http://www.mdpi.com/1424-8220/17/10/2317 | - |
dc.identifier.wosid | 000414931500159 | - |
dc.language | 영어 | - |
dc.publisher | MDPI AG | - |
dc.title | Computer Vision-Based Structural Displacement Measurement Robust to Light-Induced Image Degradation for In-Service Bridges | - |
dc.type | Article | - |
dc.description.isOpenAccess | TRUE | - |
dc.relation.journalWebOfScienceCategory | Chemistry, Analytical; Engineering, Electrical & Electronic; Instruments & Instrumentation | - |
dc.relation.journalResearchArea | Chemistry; Engineering; Instruments & Instrumentation | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.subject.keywordAuthor | adaptive ROI | - |
dc.subject.keywordAuthor | computer vision | - |
dc.subject.keywordAuthor | displacement | - |
dc.subject.keywordPlus | VIRTUAL VISUAL SENSORS | - |
dc.subject.keywordPlus | MONITORING DYNAMIC-RESPONSE | - |
dc.subject.keywordPlus | CABLE-STAYED BRIDGE | - |
dc.subject.keywordPlus | DATA FUSION | - |
dc.subject.keywordPlus | MEASURED ACCELERATION | - |
dc.subject.keywordPlus | SYSTEM | - |
dc.subject.keywordPlus | IDENTIFICATION | - |
dc.subject.keywordPlus | TECHNOLOGY | - |
dc.subject.keywordPlus | BUILDINGS | - |
dc.subject.keywordPlus | STIFFNESS | - |
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