## 3 Results
### Visual Inspection Performed by UAV and IR Camera  
In general, the recognition model of any object could be expressed with the following procedure steps:  
* Image Acquisition
* Preprocessing
* Segmentation
* Feature Extraction
* Classification and Recognition
* Post Processing  
An image can be defined as a 2D function _f(x,y)_ where _(x,y)_ is the coordinate in two-dimensional space and f is the intensity of that coordinate. Each coordinate position is called a pixel [30,31]. In case of dynamic imaging, the image could be expressed as a 3D function of three variables _f(x,y,z)_. Since the limited dimensions in the image are assumed, the domain of the image function could be expressed as a Cartesian product from the domain of real numbers that defines the range of the image:  
\[f:(<x_{min},x_{max}>x<y_{min},y_{max}>)\to H. \tag{13}\]  
The images are generated by the combination of an illumination source and the reflection or absorption of the energy by the elements of the scene being imaged. Illumination may be originated by radar, an infrared energy source, computer generated energy pattern, ultrasound energy source, X-ray energy source, etc. To sense the image, we use a sensor according to the nature of illumination. The process of image sense is called image acquisition [32]. The range of values H of the image function forms a set of values of brightness or colors of the image, which can be expressed by a set of real numbers R or Rn depending on the representation of color information, where n expresses the number of channels, i.e., the color samples used. The computer usually works with a digital image, which is represented by a matrix (grid, raster):  
\[f(x,y)=\left( \begin{array}{cccc}f(0,0)&\cdots&f(0,n-1)\\ f(1,0)&\cdots&f(1,n-1)\\ \vdots&\ddots&\vdots\\ f(m-1,0)&\cdots&f(m-1,n-1)\end{array} \right) \tag{14}\]where a right-hand side of this matrix defines the digital image. The element of the matrix represents a pixel. The conversion of an optical image (Real-World Data) into an array of numerical data is essential for the later manipulation with the data in a computer environment; thus, before any video or image processing can commence, an image must be captured by a camera and converted into a manageable entity. This conversion process is the general aim of Image Acquisition [33]. An experiment aimed at the use of UAVs with a regular camera as a form of pre-flight visual inspection of surface damage to a trainer aircraft was carried out at the maintenance center of an approved training organization. According to [PERSON] and [PERSON], in order to perform this type of experimental inspection, it is essential to meet the following conditions:  
* Reduce dust particles as much as possible in an inspection environment. * Identify the movement of the UAV, the position of personnel with respect to safety (equipped with obstacle anti-collision sensors). * Secure the UAV and the aircraft against collisions (propeller protection, definition of the aircraft protection zone according to [30; 34]). Used UAV and Camera Type:  
DJI Mavic 2, equipped with an optical sensor FC220, color profile RGB IE61966-2.1, and lens 26.3 mm f/2.2, was chosen for our experiment under UNIZA conditions. The MATLAB MatWorks tool \"Deep Learning and Machine Learning for Computer Vision\" was used for image processing. It is vital to have clean, sharp, and properly labeled images before the segmentation process, which is the part of the preprocessing algorithm in deep learning. Thanks to the segmentation process, the points of interests such as rivets or screws shown in images could be identified considering their amount, position, and orientation. Thus, after the postprocessing, the analyst (or operator) is aware whether the final number or quantity of said elements coincides with their correct number, in short, whether any screw or rivet is missing or not. This variant of UAV was chosen due to the fact that it represents the dominant type on the market with the support of libraries in MATLAB application [30].