# Influence of Material on the Density of a Point Cloud Created Using a Structured-Light 3D Scanner
## 4 Results
### Materials with Very Fine Elements  
The overall rating of materials with very fine elements is shown in Table 2. The characteristic evaluation row shows how far from the view of the very fine elements containment is from the ideal material. A total of three materials were included in this category: hairy substance, woven carpet, and need. From the description of the ideal material, it can be assumed that they could be problematic for scanning. When these materials with raw surface were scanned, no acquired point cloud reached the required density, as we can see from the percentage of measurements below 2200 points/cm\({}^{2}\) values in Table 2. None of the materials managed to scan the entire sample area without further treatments. This can be seen in Figure 7. \begin{table}
\begin{tabular}{c c c c c c} \hline  & **Material** & **Glazed Roof Tile** & **Full Burnt Brick** & **Wooden Parquets** & **Marlstone** \\ \hline \multirow{4}{*}{Point cloud density—raw} & Average & 275,405 & 297,529 & 231,108 & 291,284 \\ \cline{2-6}  & Coefficient of variation [\%] & 3.63 & 1.93 & 5.39 & 4.93 \\ \cline{2-6}  & Measurements below & & & & \\ \cline{1-1}  & 2200 points/cm\({}^{2}\) [\%] & 0 & 0 & 20 & 0 \\ \hline \end{tabular}
\end{table} 
Table 1: Well-scannable materials’ point clouds. Figure 6: Meshes from point clouds—glazed roof tile (**a**), full burnt brick (**b**), wooden parquets (**c**), marlstone (**d**). In all of them, a higher concentration of points can be observed, especially along the edges of the samples, suggesting that adjacent materials with different properties may appear to interact with each other. This phenomenon is most visible on the need point cloud, where the density of points in the area is very low, and at the same time it has the lowest average point cloud density/sample area of all materials. On the contrary, in the center of the sample, there are places where no data on the sample surface could be obtained. At these places, the point cloud density per unit area is zero or significantly lower than at the edges of the sample. This means that it is not possible to create a polygon network in its entire area from these point clouds. We carried out the surface treatment on the hairy substance, woven carpet, and reed, which could theoretically improve the density of the point cloud. Therefore, a second series of measurements was performed on each of these materials. The hairy substance and the woven carpet were smoothed to form a uniform surface, thus eliminating the undesired effect of individual fine elements. A similar example could be, for example, human hair when scanning a human head, where, based on previous experience [32], hair which is, for example, pulled into a braid, is better scanned than dissolved and tousled hair. In this case, the treatment of the sample greatly helped to increase the overall average density of the point cloud. Woven carpet's average point cloud density improved by more than 57% in the measured area, and the hairy substance improved by even more than 230% in the measured area. All point clouds acquired from the scanning of these materials after treatment reached the required density of 2200 points/cm\({}^{2}\), as can be seen in Table 2. Furthermore, the coefficient of variation decreased significantly. The fact that the hairy substance is slightly shiny was not a problem either; on the contrary, it belongs among the materials that had the highest point cloud density when measured. A comparison of the formed meshes can be seen in Figure 8