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Paper lc3-2017-165:
Comparing Feature Matching Algorithms for Measuring In-Plane Strains on Civil Infrastructures

Facilitated by the SciX project

Youyi Feng, Fei Dai and Jiaqing Zhao

Comparing Feature Matching Algorithms for Measuring In-Plane Strains on Civil Infrastructures

Abstract: Maintaining structural integrity of civil infrastructures such as bridges and tunnels is always an essential task for civil engineers. Collapse or damage of these infrastructures may lead to a tremendous amount of painful injuries, casualties, and societal losses. This paper reported the work on evaluating optimal feature matching algorithms for development of visual sensing-based techniques to measure in-plane deflections and strains in order to facilitate monitoring and evaluation of integrity of civil infrastructures in a cost-effective way. A series of experiments were conducted in which three algorithms Digital Image Correlation (DIC), Scale-Invariant Feature Transform (SIFT) and Speeded-Up Robust Features (SURF) were compared. The result indicated that DIC has superiority among the three algorithms. To further assess the accuracy of DIC, a high-speed industrial camera was then used to capture a series of continuous image frames of deformed real-world scenarios. The DIC algorithm was adopted in the feature detection and tracking process, and in-plane displacement and strains were calculated and compared with the ground truth. The result indicated that the DIC-based method can achieve highly accurate performance in measuring in-plane deflections and strains for civil infrastructures and holds potential to the development of visual sensing enabled structural health monitoring.

Keywords: Image-Based Methods, Structural Health Monitoring, Visual Sensing, Non-Contact Measurements, Comparative Study

DOI: https://doi.org/10.24928/JC3-2017/0165

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