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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