# Point Cloud Measurement of Rubber Tread Dimension Based on RGB-Depth Camera
## 2 Related Work  
The main components of the system's hardware platform include the light source and camera. Considering the production line site environment, factors such as light source intensity and continuous light uniformity were comprehensively evaluated. A white-bar LED light source, model OPT-LI14030, was used for visual inspection in the field. The image acquisition equipment chosen was the Astra Pro RGB-D depth camera from OPT-LI, which features both RGB and IR lens modules [14]. This camera allows real-time image previews and video playback, connecting to the computer via USB and utilizing a driver-free UVC method for video transmission. The program calls interfaces in PyCharm based on the Open NI framework [15], enabling real-time video transmission; high-resolution, high-precision image acquisition; and image calibration. The structure of the vision measurement system is shown in Figure 1. The tread size data in this study were obtained using this vision measurement system. Astra series cameras are recognized for their high accuracy, low power consumption, fast response, stability, and reliability [16]. Therefore, an Astra series depth camera from ObiZoomOptics was selected for close-up photography to acquire the tread image data. The Astra camera offers several models, including short-range, long-range, and high-resolution RGB video cameras. The configuration of the Astra camera parameters is shown in Table 1.  
RGB-D camera calibration is a necessary prerequisite for color depth alignment, point cloud data unification, and target identification, and is the process of solving for the camera's external references \(R\), \(T\), and internal references \(u_{0}\), \(v_{0}\), \(f_{x}\), and \(f_{y}\) through a set of three-dimensional spatial points and the corresponding image pixel coordinate pairs [17]. Common calibration methods include traditional camera calibration, active vision calibration, and camera self-calibration, among others [18]. However, the traditional method only accounts for radial distortion and is inadequate when distortion is significant. Active vision calibration requires controlling the camera to perform specific movements, making it unsuitable for industrial environments. The self-calibration method often exhibits poor robustness, limiting its practical applications [19]. Given the field of view of the camera and the constraints of installation positions in an actual industrial production line, this paper adopts the planar tessellated grid camera calibration method proposed by Professor [PERSON] [20]. This method necessitates precise knowledge of the geometric structure of the checkerboard grid. In this section, the black and white checkerboard printed on A3 paper is used, and the calibration plate size is \(252\times 360\) mm, which consists of several squares, each of which has a size of \(36\times 36\) mm, as shown in Figure 2. \begin{table}
\begin{tabular}{c c c c} \hline \hline  & **Parameters** & & **Parameters** \\ \hline Baseline (mm) & 75 & data transmission & USB 2.0 \\ Depth distance (m) & 0.6–8.0 & video interface & UVC \\ Maximum power consumption (W) & 2.50 & operating system & Windows 10 \\ Accurate (mm) & \(\pm 3\) & Working temperature (\({}^{\circ}\)) & 10–40 \\ Depth FOV (\({}^{\circ}\)) & H58.4, V45.5 & Depth map resolution & \(1280\times 1024\)@7 FPs \\ Color FOV (\({}^{\circ}\)) & H66.1, V40.2 & Color map resolution & \(1280\times 720\)@7 FPs \\ Delay (ms) & 30–45 & Dimension (mm) & \(164.85\times 30.00\times 48.25\) \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Astra Pro camera parameters. Figure 1: Structural diagram of visual measurement system. This calibration experiment utilizes the reprojection error as the technical index to evaluate the camera's calibration performance [21]. The reprojection error is defined as the difference between the actual projection pixel of a 3D spatial point on the image plane and the virtual projection pixel obtained through calibration calculations.