# _Skin Imaging_: A Digital Twin for Geometric Deviations on Manufactured Surfaces
## 5 Experimental Results and Discussion
### Skin Image Analyzing
The magnitude is the average intensity of detected defect's pixels on the _skin image_ that is a representative of the deviation and can be used directly for surface investigation without returning to the PC's information. \begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Defect**} & \multirow{2}{*}{**Magnitude**} & **Out of Cylindricity (mm)** & **Out of Cylindricity (mm)** \\  & & **(Average)** & **(Maximum)** \\ \hline
1 & 91 & 0.3320 & 0.6501 \\
2 & 33 & 0.1381 & 0.2321 \\
3 & 27 & 0.1574 & 0.1808 \\
4 & 47 & 0.17 & 0.34 \\
5 & 47 & 0.1566 & 0.3532 \\
6 & 27 & 0.1757 & 0.1931 \\
7 & 87 & 0.2631 & 0.5126 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Out of cylindricity of the defective gudgeon pin. Figure 22: Detected defects on gudgeon pin, **(a)** on _skin image_, **(b)** on DCS **(c)** on \(\mathcal{\text{X}}_{\text{DCS}}\text{-Y}_{\text{DCS}}\) plane (**d**) on the 3D surface (All the labels correspond to the number of defects illustrated in Figure 13). For the ball joint displayed in Figure 18, the extracted defective regions are shown on the _skin images_ of its hemispheres in Figure 23a. Six defects are located on upper hemisphere and one of them on the down hemisphere. The defective parts are shown with their labels on the _skin images_, and also are illustrated in red color on the PC in DCS frame, both in non-uniform and uniform scale of the axes for better visualization. Since the lower half includes a small defective area its corresponding _skin image_ is almost dark and the defect, which is labeled as 6, has been appeared in a small lighter object with respect to the background. For more clarification, the maximum DOP of this defect is marked on DCS frame together with two healthy points of the surface (Figure 23a). According to Table 2, this region (label 6) has the minimum out of sphericity error among other defective regions on the ball joint. Both defect 2 and defect 6 are shallow dens on the surface and have approximately the same out of sphericity, in terms of maximum value in Table 2, but the average out of sphericity for defect 2 is higher than defect 6. This means that defect 2 has more deviated points than the ones in defect 6 which leads to its slightly wider bright area on the _skin image_ such that the magnitude of defect 2 and defect 6 are reported as 40 and 23 in the Table 2, respectively, which is also obvious on the final inspected surface in Figure 23b. Figure 23: Detected defects on ball joint, (**a**) from left to right: on _skin image_, on DCS with non-uniform scale of axes, on X\({}_{\text{DCS}}\)–Y\({}_{\text{DCS}}\) plane, on DCS with uniform scale of axes, (**b**) on the 3D surface in scanner frame (All the labels correspond to the number of defects illustrated in Figure 18). Although the accuracy and efficiency of the proposed methodology have been comprehensively discussed in the previous paper, here, a virtual defective cylindrical surface is investigated in order to reaffirm the methodology's precision. Figure 24 shows this surface and the PC acquired from it. Generating the surface's _skin image_ (Figure 25a), the defective region is detected on it (Figure 25b). As it was mentioned before, thanks to the traceability of the system, all the analyzed data on any _skin image_ is returnable onto its 3D PC, regardless of the type of the surface. Therefore, no information will be lost. For more clarification, the set of points belonging to the segmented defect is also shown in blue color on the _skin image_ displayed in Figure 25b. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Defect** & **Magnitude** & \
\begin{tabular}{c} **Out of Sphericity (mm)** \\ **(Average)** \\ \end{tabular} &
\begin{tabular}{c} **Out of Sphericity (mm)** \\ **(Maximum)** \\ \end{tabular} \\ \hline
1 & 145 & 0.32 & 0.57 \\
2 & 40 & 0.1373 & 0.1730 \\
3 & 63 & 0.1819 & 0.3309 \\
4 & 44 & 0.1412 & 0.1957 \\
5 & 39 & 0.12 & 0.2059 \\
6 & 23 & 0.08 & 0.16 \\
7 & 64 & 0.2365 & 0.3502 \\ \hline \hline \end{tabular}
\end{table}