A Novel Method for Heat Haze-Induced Error Mitigation in Vision-Based Bridge Displacement Measurement

Area of Science:

• Structural Engineering
• Computer Vision
• Optical Measurement

Background:

• Vision-based techniques are crucial for structural displacement monitoring.
• Heat haze introduces image distortions, compromising measurement precision.
• Existing methods lack robust heat haze mitigation capabilities.

Purpose of the Study:

• To propose a vision-based bridge displacement measurement technique with heat haze mitigation.
• To evaluate the effectiveness of the proposed method in correcting heat haze-induced errors.

Main Methods:

• Image acquisition and analysis for structural displacement monitoring.
• Application of Dual-Tree Complex Wavelet Transform (DT-CWT) for heat haze mitigation.
• Utilizing Speeded-Up Robust Features (SURF) algorithm for displacement extraction.

Main Results:

• The vision system achieved high accuracy in heat haze-free conditions.
• The DT-CWT mitigation method corrected 61.05% of heat haze errors in static experiments.
• The mitigation method corrected 95.31% of heat haze errors in dynamic experiments.

Conclusions:

• The proposed vision-based technique effectively measures bridge displacement.
• The DT-CWT approach significantly enhances measurement accuracy under heat haze conditions.
• This method offers a reliable solution for structural monitoring in environments with thermal turbulence.