## 1 Introduction
Although the number of data points met the calibration requirements in the above method, the error points could not be eliminated, and the accuracy of the results of calibration could be affected. [PERSON] [17] proposed a method for multi-line structured light calibration. This method used the geometric relationship of multiple structured line lights to screen the data points, and the plane parameter was obtained by the filtered data points. However, this method requires a high manufacturing precision of the laser, and the application range of multi-line structured light is relatively small. [PERSON] [18] proposed a self-calibrating line laser scanning system for underwater environments, which could recover depth information using geometric constraints, such as coplanarity. This method is affordable and can be performed using a single camera and a freely movable cross-line laser projector. [PERSON] [19] used a single circle as the calibration body for the calibration plane. This method could solve the camera parameters, distortion coefficients, and parameters of the light plane equation in a single unit, significantly reducing the calibration cost of the line-structured light system and simplifying the calibration process. However, this method did not optimize the process of solving the parameters of the light plane equation, and there were errors in the data points used to calculate the light plane. The calibration accuracy obtained by this method was 0.0451 mm. [PERSON] [20] used a cross-line structured light method to assist in the calibration process of line-structured light, optimizing the equation of the light plane using the perpendicular relationship. However, this method requires the use of a pair of perpendicular light planes to optimize the line-structured light, and the vertical relationship between the two light planes needs to be ensured by the laser's manufacturing accuracy, which increases the hardware cost of the line-structured light measurement. Although line-structured light visual measurement technology is a measurement algorithm with good noise immunity, the calibration of line-structured is the key limitation of measurement accuracy. This is because the light plane equation needed to be obtained through the center points of the light stripe on the image. The coordinates of the center points could be obtained by the center point detection algorithm of the light stripe and the camera calibration algorithm. In the process of detecting the center point of the light stripe, the detection algorithm could be influenced by the grayscale of the image and the quality of the light stripe, and the center points of the light stripe also had errors. Due to the influence of the algorithm and the calibration environment, the camera's internal parameters and the distortion coefficients obtained by the calibration also had errors. The above two factors may cause errors in the solution of the spatial coordinates of the center point of the light bar. Many existing line-structured light calibration algorithms mainly simplify the calibration process and reduce the calibration cost of line-structured light by using different calibration bodies. However, they do not solve the error problem at the center point of the light stripe, which is a key factor affecting calibration accuracy. In this paper, two geometrical constraints were used to optimize the line-structured light calibration process. The error points in the center point of the light stripe were filtered on the basis of the distance between the center point and the light plane. The method of solving the light plane was further optimized by moving the light plane to obtain multiple parallel light planes. The sum of the algebraic error of the light plane equation was used as the objective function to optimize the parameters of the light plane.