To address the limitations of traditional calibration methods in non-contact 3D reconstruction—specifically the frequent need for manual intervention, significant error accumulation caused by multi-step calibration, and low levels of automation— this paper proposes an automatic synchronous calibration method based on cross-structured light. By utilizing the geometric invariance of the intersection points of dual laser beams, a spatial geometric model of the cross-structured light is constructed. An algorithm is then derived to synchronously solve the camera intrinsic parameters, extrinsic parameters, and light plane parameters using a single set of images. This process eliminates the reliance on repeated target repositioning required by traditional methods and achieves parameter unification directly through the geometric transformation of feature point clouds, realizing the integration of calibration and measurement. Validated through scanning experiments on standard aluminum oxide plates and non-standard aluminum alloy components, the results demonstrate that under standard industrial conditions, the system’s dimensional measurement error is controlled within ±0.5 mm, the average 3D reconstruction accuracy reaches ±0.25 mm, and the peak error rate is below 2.67%. The proposed method effectively overcomes the reliance on manual assistance, significantly reducing operational complexity and improving inspection efficiency while ensuring high precision. It provides an efficient, low-cost, and fully automated solution for industrial measurement, reverse engineering, and surface morphology analysis.