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A Robust Vision-Based Method for Displacement Measurement under Adverse Environmental Factors Using Spatio-Temporal

Chuan-Zhi Dong1, Ozan Celik1, F Necati Catbas2

  • 1Department of Civil, Environmental, and Construction Engineering, University of Central Florida, 12800 Pegasus Drive, Suite 211, Orlando, FL 32816, USA.

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This study introduces a robust vision-based displacement measurement method that maintains accuracy despite illumination changes and fog interference. The novel approach achieves subpixel sensitivity, outperforming existing methods in adverse conditions.

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Taylor approximationcomputer visiondisplacement measurementenvironmental factorsnon-contactspatio-temporal contextstructural health monitoring

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Area of Science:

  • Engineering
  • Computer Vision
  • Structural Health Monitoring

Background:

  • Vision-based measurement systems typically require ideal environmental conditions for optimal performance.
  • Adverse factors like illumination changes and fog significantly degrade the accuracy of conventional vision-based measurement techniques.
  • Existing methods struggle to maintain precision when faced with common environmental interferences.

Purpose of the Study:

  • To develop a robust vision-based displacement measurement method capable of overcoming illumination variations and fog interference.
  • To achieve high-sensitivity measurements at the subpixel level under challenging environmental conditions.
  • To enhance the reliability and applicability of vision-based systems in real-world scenarios.

Main Methods:

  • Developed a novel vision-based displacement measurement technique utilizing high-resolution imaging.
  • Incorporated spatial and temporal contextual information to improve measurement robustness.
  • Validated the method through laboratory experiments simulating illumination changes and fog on a bridge model.

Main Results:

  • The proposed method demonstrated superior performance compared to conventional displacement sensors and existing vision-based techniques.
  • Accurate subpixel-level displacement measurements were achieved even under simulated adverse conditions.
  • Experimental results confirmed the feasibility, stability, and robustness of the developed approach.

Conclusions:

  • The developed vision-based method offers a robust solution for displacement measurement in the presence of illumination changes and fog.
  • The technique provides enhanced accuracy and reliability, expanding the practical applications of vision-based monitoring systems.
  • This advancement contributes to more dependable structural health monitoring and measurement in challenging environments.