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Sensors 2017, 17(10), 2317;

Computer Vision-Based Structural Displacement Measurement Robust to Light-Induced Image Degradation for In-Service Bridges

School of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Korea
Korea Railroad Research Institute, Uiwang 16105, Korea
Department of Civil and Environmental Engineering, University of Seoul, Seoul 02504, Korea
Authors to whom correspondence should be addressed.
Received: 2 July 2017 / Revised: 3 October 2017 / Accepted: 9 October 2017 / Published: 11 October 2017
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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. View Full-Text
Keywords: adaptive ROI; computer vision; displacement adaptive ROI; computer vision; displacement

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Lee, J.; Lee, K.-C.; Cho, S.; Sim, S.-H. Computer Vision-Based Structural Displacement Measurement Robust to Light-Induced Image Degradation for In-Service Bridges. Sensors 2017, 17, 2317.

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