Quality Assessment of High-Speed Motion Blur Images for Mobile Automated Tunnel Inspection

Area of Science:

• Image processing and analysis
• Optical engineering
• Transportation infrastructure inspection

Background:

• Motion blur is a critical factor affecting image quality in mobile scanning systems.
• Accurate assessment of tunnel conditions relies on high-resolution imagery.
• Existing methods may not adequately capture the impact of dynamic motion on image quality.

Purpose of the Study:

• To quantitatively evaluate the impact of motion blur on image quality in a mobile tunnel scanning system (MTSS).
• To assess the effectiveness of blurred edge width (BEW) and spatial frequency response at 50% contrast (MTF50) as image quality metrics.
• To investigate the influence of motion speed, shutter speed, and illumination on image quality.

Main Methods:

• Simulated high-speed translational motion (up to 70 km/h) using a specialized panel.
• Image acquisition under ISO 12233 compliant conditions.
• Quantitative image quality assessment using BEW and MTF50 metrics.
• Statistical analysis including two-way ANOVA and t-tests.
• Field validation in actual tunnel environments.

Main Results:

• Increased motion speed led to higher BEW and lower MTF50, indicating intensified blur and reduced sharpness.
• Shutter speed and motion speed were confirmed as significant factors affecting image quality.
• Higher illumination levels offered partial improvement but could also decrease sharpness.
• BEW and MTF50 effectively captured blur variations related to scanning direction during field validation.

Conclusions:

• BEW and MTF50 are reliable indicators for quantifying motion blur in tunnel inspection imagery.
• The findings can optimize MTSS operation for enhanced image acquisition.
• Improved motion blur quantification can increase the accuracy of automated defect detection in tunnels.