## 2 Methods and Materials
### Non-Destructive Testing (NDT) Techniques
Below are the key benefits of using photogrammetry compared to laser and LiDAR scanning:  
* Cost-Effectiveness: A good-quality camera and image-processing software are the two essential tools required to scan and reconstruct the 3D model compared to expensive specialised laser and LiDAR equipment [61];
* Detailed Texture Information: A critical advantage of photogrammetry is its ability to acquire high-resolution texture and colour information, which is especially important in the field of maintenance inspection where detailed textures and geometric information are so important [62];
* Versatility and Large-Area Coverage: Photogrammetry can be used for both large-scale and small-scale objects without concerns about geometry, texture, distance from the camera, or the speed of image capture. The use of drones for photogrammetry can be a great combination to capture large areas for mapping efficiently [63]. On the other hand, photogrammetry loses precision compared to laser and LiDAR technologies, particularly with fine geometries [62]. Moreover, photogrammetry relies on \begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Aspect** & **Laser Scanning** & **LiDAR Scanning** \\ \hline Purpose & High-precision scanning of objects or structures to create detailed 3D models & Large-scale mapping and environmental scanning using distance measurement \\ \hline Method & Uses a laser beam to measure reflected light and capture an object’s shape and dimensions & It uses pulsed laser beams to measure the time it takes for light to reflect and return, creating 3D maps \\ \hline Best For & Capturing small to medium-sized objects in great detail & Mapping large areas and scanning complex environments \\ \hline Typical Applications & Manufacturing, architecture, reverse engineering, 3D modelling of surfaces & Topography, forestry, urban planning, autonomous vehicles \\ \hline Range & Short to medium range (up to several metres) & Long range (hundreds of metres to kilometres) \\ \hline Accuracy & Extremely high, capturing fine surface details & High, but typically less detailed than laser scanning \\ \hline Data Output & Point clouds representing detailed object surfaces & Point clouds representing wide-area 3D maps \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Critical differences between laser scanning and LiDAR scanning [59; 60]. environmental conditions such as weather and lighting, contrasting with LiDAR, which can operate in low light or darkness [63]. Photogrammetry has already been successfully used in fields like forensic science [64], civil infrastructure [65], and archaeology [66]. To the best of my knowledge, no specific study has directly explored the application of photogrammetry for aircraft defect inspection. A notable example of this technology comes from NASA [67], where photogrammetry was combined with small, unmanned aircraft systems (sUAS) to inspect both the interior and exterior of the AEDC National Full-Scale Aerodynamics Complex (NFAC) wind tunnel facilities at NASA Ames Research Centre. The primary objective of this system was to detect both existing and missing fasteners, as well as to precisely determine their real-world locations in 3D space. This methodology involved object detection algorithms to identify and highlight fasteners and missing fasteners using bounding boxes and photogrammetry to map the detected objects and establish the 3D locations of these defects. Deep learning methods and, more specifically, convolutional neural networks (ResNet18 Mask R-CNN) were the preferred computer vision approaches to detect image defects. A big challenge was the size of the objects to be detected, as most were smaller than 128 \(\times\) 128 pixels. On the other hand, Pix4D was used to process the set of 2D images to generate the 3D point cloud. In terms of 3D localisation, the researchers used the following algorithm:  
1. Creation of a 3D Point Cloud: A 3D point cloud was generated to represent the spatial structure of the environment or objects. 2.