Presentation
18 April 2022 2D displacement measurement using specially designed markers and phase-based motion estimation
Author Affiliations +
Abstract
The advanced displacement measurement technique using computer vision has shown several advantages, such as high spatial resolution and no mass loading effect, compared to conventional sensing techniques. However, the accuracy and robustness of vision-based techniques are subjected to the various conditions, including uneven illumination and insufficient lighting. This study introduces an accurate 2-dimension displacement measuring technique with high robustness to the illumination change, which uses two complex Gabor filters and a specially designed marker. The linear phase can be generated around the marker by optimizing the filter parameter for accurate motion estimation. The nonlinearity caused by the complex conditions, such as low light and uneven illumination, can also be reduced by emphasizing marker features. Phase-based optical flow is further employed to extract the displacement based on the extracted phase. The measurement performance is compared with Laser Doppler Velocimetry (LDV) to validate the proposed technique under various lighting conditions and its robustness is demonstrated. The proposed technique is also applied to different structures to show the ability of measuring high-accuracy displacement signals under various conditions.
Conference Presentation
© (2022) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yinan Miao, Yeseul Kong, Jun Young Jeon, and Gyuhae Park "2D displacement measurement using specially designed markers and phase-based motion estimation", Proc. SPIE PC12046, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2022, PC1204605 (18 April 2022); https://doi.org/10.1117/12.2614147
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KEYWORDS
Motion estimation

Laser Doppler velocimetry

Light sources and illumination

Computer vision technology

Linear filtering

Machine vision

Optical filters

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