## 1 Introduction  
Structured light vision measurement is an active vision measurement technology, and the profile information of the measured object can be obtained by the characteristic light beam projected onto the surface. Compared with binocular vision technology, structured light vision measurement technology [1, 2, 3, 4] is often used for non-contact measurement in complex environments with better robustness. Visual measurement based on linear structured light involves projecting a plane beam onto the surface of the measured object, and the measurement results can be obtained by the coordinate of the characteristic point on the transversal line between the plane beam and the surface of the measured object. In order to solve the three-dimensional coordinates of the characteristic points, the space plane parameters corresponding to the light plane need to be calculated. This process is known as structured light calibration, which establishes the spatial connection between the light plane and the camera. In the active vision measurement system based on structured light, camera parameters from the camera calibration [5, 6, 7, 8] and light plane parameters determine the spatial location of feature points on the measured object. Therefore, structured light calibration has been widely studied. There are various calibration methods for different types of line-structured light projection systems. For multi-line structured light projection, [PERSON] [9] proposed a calibration method based on ray tracing, which simplified the calibration process by tracing horizontal light rays. [PERSON] [10] proposed a calibration method using a one-way multi-line displacement profile measurement method that established a lookup table by correcting polynomial mapping coefficients to avoid lens distortion. This method also had the advantage of flexible operation. The hardware cost of multi-line structured light vision is high, and it is easily affected by the external lighting environment. In order to solve the above problems, structured light vision technology based on laser projection has been extensively studied. In the early days, light plane equations were obtained by the invariant cross ratio method. [PERSON] [11] proposed a calibration method using two planes perpendicular to each other. Calibration parameters were computed according to three non-collinear reference points in the target. In this method, the calibration accuracy was limited by the number of data points. [PERSON] [12] used double cross ratio invariance to solve visual system parameters. Compared with the above method, the solution accuracy of the parameters can be improved by having enough data points. Both methods have the disadvantage that it is difficult to manufacture the target. In order to reduce the manufacturing difficulty and cost of the target, [PERSON] [13; 14] made a plane target with the co-plane of the calibration plate plane and the target plane. In this method, the coordinates of the points were obtained by the parameters of the target, and the spatial feature points were obtained by moving the plane target several times to solve the optical plane equation. This method has simple operation, low hardware cost, and a high practical value. [PERSON] [15] designed a special plane target containing several calibration areas and obtained the parameters of the light plane equation of different regions. This method reduced the influence of lens distortion on calibration accuracy. However, the production of the calibration object and the algorithm were complicated. [PERSON] [16] used a ball to calculate the light plane parameters. Due to the geometric characteristics of the spherical calibration volume, image acquisition was independent of the placement position of the calibration volume. It was easy to obtain a better-quality target, and the calibration accuracy was improved. However, the manufacturing cost of the spherical calibration target in this method was much higher than that of the plane calibration board.