Defect inspection for underwater structures based on line-structured light and binocular vision.

Area of Science:

• Engineering
• Computer Vision
• Robotics

Background:

• Underwater structure inspection is critical for safety and maintenance.
• Passive vision methods lack the required accuracy for detailed surface defect analysis.
• Accurate defect detection is essential for preventing structural failures.

Purpose of the Study:

• To develop a more accurate method for underwater surface defect inspection.
• To improve the reliability of defect detection using structured light imaging.
• To enable precise localization and measurement of surface defects.

Main Methods:

• A two-stage approach utilizing structured light images.
• Extraction of light stripes using HSV and gray space analysis.
• Application of a hole-filling algorithm for stripe integrity.
• Calculation of depth information to create a depth map.
• Segmentation of the depth map for defect analysis.

Main Results:

• Successful extraction and integrity of light stripes.
• Generation of a detailed depth map from structured light data.
• Accurate defect localization and measurement demonstrated.
• Feasibility and effectiveness of the proposed method validated.

Conclusions:

• The proposed two-stage structured light method significantly improves underwater defect inspection accuracy.
• This technique offers a viable alternative to traditional passive vision systems.
• The method is effective for precise defect localization and measurement in underwater environments.