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High-precision edge-preserving stereo matching for cabinet panels using Markov random fields with guided image
Applied Optics
|September 22, 2025
Summary
This study introduces a new stereo vision method for precise 3D cabinet panel measurement. The technique improves quality control in manufacturing by overcoming common stereo vision challenges.
Area of Science:
- Manufacturing Technology
- Computer Vision
- Metrology
Background:
- Quality control in cabinet panel manufacturing necessitates precise 3D measurement.
- Traditional 2D methods lack the accuracy and efficiency for complex assemblies.
- Stereo vision offers potential but faces challenges like occlusions and poor texture.
Purpose of the Study:
- To develop a high-precision stereo reconstruction method for manufacturing quality control.
- To address limitations of existing stereo vision techniques in industrial settings.
- To enhance the accuracy and efficiency of 3D measurements in cabinet panel production.
Main Methods:
- Proposed a novel stereo reconstruction approach combining guided image filtering and Markov random fields.
- Utilized simulated and real-world experimental data for validation.
- Focused on improving edge disparity, occlusion, and weak texture handling.
Main Results:
- The proposed method demonstrated significant improvements in stereo reconstruction accuracy.
- Effectiveness was validated in challenging scenarios common in manufacturing environments.
- Achieved higher precision and efficiency compared to conventional methods.
Conclusions:
- The guided filtering and Markov random field integration offers a robust solution for stereo vision challenges.
- This advanced stereo reconstruction method enhances practical applications of 3D measurement in manufacturing.
- The study contributes to improved quality control in the cabinet panel industry.
