When it comes to structured light 3D imaging systems, calibration is crucial. This study presents a projector calibration technique that successfully increases calibration accuracy and lowers calibration complexity for structured light 3D imaging systems. First, by projecting gray code and sinusoidal stripe patterns, the study uses phase-encoding technology to acquire absolute phase values. Second, it reduces errors brought on by the nonlinear components of the projector and camera by compensating for phase errors using the Hilbert transform. To further reduce the effect of nonlinear errors on calibration accuracy, the technique also employs a local homography matrix to translate the checkerboard corner points from the coordinate system of the camera pixels to that of the projector. Lastly, Zhang’s calibration method is used to determine the projector’s internal and external parameters. In comparison with current methods, the experimental results show that the projector calibration method suggested in this research delivers higher accuracy and a more concentrated error distribution, laying the groundwork for future high-precision 3D reconstruction jobs.