Visual reconstruction of milling workpiece surface topography based on phase shifting and complementary gray code

When the surface texture of a workpiece is extremely fine, cameras struggle to accurately capture depth information, making conventional machine vision methods insufficient for achieving micrometer-scale three-dimensional surface reconstructions. To overcome this limitation, the study focuses on high-precision 3D reconstruction of the surface morphology of milled workpieces. Given the smoothness of milled surfaces, their susceptibility to overexposure, and the difficulty in extracting depth information from two-dimensional image pixels, the paper proposes a novel method that combines phase-shifting with complementary Gray code to achieve micrometer-level surface reconstruction. The superiority of this method over traditional phase-shifting techniques is demonstrated through comparisons of overall morphology, two-dimensional power spectral density (2D PSD), and the average deviations of sampled surfaces. Results show that the proposed method reduces the average relative error in surface deviations by 25.89% compared to traditional techniques. Furthermore, cross-sectional analyses reveal that the reconstructed point cloud surface more closely mirrors the actual peak-to-valley characteristics of the real surface. Experimental results confirm that this method effectively captures the surface features of milled workpieces, indicating broad potential for applications in precision manufacturing.