High-precision edge-preserving stereo matching for cabinet panels using Markov random fields with guided image filtering
Xiang Xiong, Yibo Li, Liying Sun, Qian Liu · Applied Optics · 2025
Quality control is critical in cabinet panel manufacturing due to the complexity of the assembly process, which requires three-dimensional measurement methods for enhanced precision and efficiency compared to conventional two-dimensional techniques. Stereo vision offers an effective solution with high accuracy, efficiency, and cost-effectiveness, yet challenges like unclear edge disparities, occlusions, and weak textures persist. To overcome these, we propose a high-precision stereo reconstruction method combining guided image filtering with Markov random fields. Simulated and real-world experiments validate our approach, demonstrating significant improvements in challenging scenarios. This work aims to advance stereo vision's practical application in manufacturing.