# Automated 3D Image Processing System for Inspection of Residential Wall Spalls
## 2 Materials and Methods
### Slam-Based Semi-Autonomous Data Acquisition
#### 2.2.1 3D Scanning Methods  
3D scanning technology has been widely used in the construction industry in recent years as a non-invasive method for monitoring structural defects, particularly for large structures such as bridges, buildings, and dams. [PERSON] et al. successfully introduced a high-quality 3D point cloud model of the test bridge using captured stereo video [23]. [PERSON] et al. proposed a UAV-based dam inspection method to obtain a 3D dam model with real-world environmental textures and scale information [24]. Compared to traditional structural assessment methods, 3D scanning technology can automatically collect data without relying on physical reference points, providing a more comprehensive and detailed structural view. This significantly reduces manual intervention and improves the accuracy of measurements related to surface irregularities, cracks, and deformations [18]. In addition, a key advantage of 3D scanning is its ability to track structural changes over time. [PERSON] et al. applied 3D laser scanning technology for tunnel deformation detection, providing a powerful tool for continuous tunnel monitoring [25]. [PERSON] et al. utilized mobile laser scanning technology to acquire point cloud data of the roadway, effectively identifying rock deformation areas in the scanned point clouds over different time periods [26]. By conducting regular scans at different time intervals, the condition of the building can be documented in detail. These data allow for the detection of gradual structural deformations, such as alignment shifts, tilting, or the appearance of new cracks. This long-term tracking capability is essential for proactive maintenance and early intervention, ensuring that issues are addressed before they escalate. The commonly used 3D scanning methods and equipment in the field of building structural health monitoring are shown in Table 1.  
To achieve low human intervention and low-cost data collection, a UGV equipped with a depth camera and LiDAR was employed for this study. The equipment parameters are listed in Table 2. As shown in Figure 4, the UGV is moved via remote device control, during which the LiDAR constructs a 2D map. The constructed map is saved in the main controller for path planning purposes. Meanwhile, the depth camera collects environmental information, which is then uniformly processed. Prior to data collection, a chessboard \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Methods** & **Equipment** & **Price** & **Technology** \\ \hline Active & FARO Focus3D scanner [20] (Lake Mary, FL, USA) & USD 54,880 & LiDAR scanning \\ Laser Scanning & Leica BLK360 [27] (Wetzlar, Germany) & USD 1372 & \\ \hline \multirow{4}{*}{\begin{tabular}{c} Passive \\ Reconstruction \\ Technique \\ \end{tabular} } & \
\begin{tabular}{c} Hivision \\ MV-CBO-10 UC [13] \\ (Hangzhou, China) \\ Realsense D435 [28] \\ (Santa Clara, CA, USA) \\ \end{tabular} & USD 547 & \\ \cline{1-1} \cline{2-4}  & Mobile platforms &
\begin{tabular}{c} UAV [29] \\ UGV [5] \\ \end{tabular} & USD 1889–13,690 & USD 547–2738 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: 3D scanning methods and equipment. Figure 3: Example of test scenario selection. pattern is used for camera calibration to obtain the intrinsic and extrinsic parameters needed for correcting images in ORB-SLAM2. Considering parameters such as the measuring range of the LiDAR and depth camera, data collection was performed at a distance of 1-1.5m from the building. Finally, visual reconstruction techniques were applied to generate 3D wall spalling data [30]. Compared to active laser scanning, this passive reconstruction technique is lower in cost and can also create accurate 3D models of concrete structures [14]. The intention of using the UGV is twofold. First, the camera placed on the UGV leverages its stabilization to generate smooth video and ensure high quality for subsequent 3D reconstruction.