KEYWORDS: 3D modeling, Point clouds, Mirrors, Field programmable gate arrays, Calibration, Modulation, Microelectromechanical systems, Cameras, Data modeling, Phase shifts
Three-dimensional reconstruction technology based on fringe projection profilometry is widely used in industrial measurement, defect detection, and other fields. The lateral and longitudinal resolution of 3D reconstruction is mainly determined by the camera's resolution, while the axial resolution along the z-axis is primarily determined by the accuracy of phase retrieval. In industrial component inspection, the 3D measurement system's ability to distinguish the small height differences is crucial. In this paper, we propose a method to evaluate the system's axial resolution based on plane fitting. Firstly, the proposed method employs a multi-frequency 12-step phase-shifting method to generate the point cloud of a step-like standard part. Then, we generate an image mask by setting the threshold of the modulation intensity to filter out abnormal point clouds. To address the multi-plane extraction problem, we propose a multi-plane fitting method based on the RANSAC framework. This method constructs a model score using orthogonal distances and sequentially extracts planes from the point cloud using the least squares method. Finally, our method determines the system's axial resolution by calculating the distances between planes. Given the importance of axial resolution in industrial inspection, our proposed method has significant practical application value for any given structured light system.
Projector calibration is crucial for the structured light three-dimensional measurement system. However, the projector is unable to capture images like a camera, thus the accuracy of projector calibration is determined by the mapping relationship between the pixel coordinate system of a camera and that of a projector. The goal of optimizing projector calibration is to find a more accurate mapping relationship. We propose a sub-pixel mapping method based on blob detection to find the corresponding projector pixel coordinates of the marker points of a calibration target and then realize sub-pixel level projector calibration. This method can reduce eccentric error and is also suitable for the projectors with different pixel arrangements. Besides, it is independent of the results of camera calibration. Experimental results demonstrate that our proposed mapping method can achieve good projector calibration performance: its re-projection error is about 10% less than the existing methods and the accuracy of measurement with the calibrated results is also higher.
A new method based on single shot using color coded image sequence for 3D reconstruction is proposed. The previous spatial neighborhood coding methods often need to determine the center of the pattern, but inaccurate positioning of pattern feature points will bring errors to 3D reconstruction. In this paper, a color-coded pattern is designed as two opposite triangular patterns to directly establish the center point of the pattern, thus avoiding the error caused by the inaccurate positioning of the center point after the pattern distortion. We designed a corner detector for our feature point detection, it is efficient and accurate. The pattern is coded in four colors of red, blue, green and pale yellow. We use a quaternary sixth order primitive polynomial to generate the pseudorandom sequence, which is then regenerated into the M-array. The final size of the code pattern is 65×63, and the unique code window size is 2×3. Experiments show that the 3D reconstruction owns high measurement precision and the decoding has strong robustness.
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