## 3 Results and Discussion
### Analysis of Contour Reconstruction Reliability for S02  
Results variations between S01 and S02 scenarios were exclusively related to contrast differences because, although both specimens shared the same dimensions, only S01 had its background painted in black. All quality indicators showed a high dependence on \(T\), while \(S_{f}\) had a lower, but not negligible, influence (Figure 9). Nevertheless, overall results were clearly worse than those obtained for S01. This result was common to all the edge-detection methods tested, indicating that the reduction in contrast had a direct impact on the quality of contour characterisation. Thus, the range of \(T\) values providing 100% \(C_{f}\) was thinner independent of the method used, and a significant reduction in \(\overline{D}\) and \(\sigma_{D}\) was also found for equivalent test combinations between \(S01\) and \(S02\). Nevertheless, the observed worsening of results was less noticeable in the case of Canny and ApproxCanny methods. Under the coverage priority criterion (Table 4), the best achievable results for \(S02\) worsened the equivalent results for \(S01\). Only Canny provided results that, although still worse, could be compared to those obtained for \(S01\). On the other hand, assuming a slight reduction in \(C_{f}\) under the accuracy priority criterion, would improve \(\overline{D}\) and \(\sigma_{D}\). This was especially relevant in the case of ZeroCross, Canny and ApproxCanny methods. For example, in the case of the Canny method, a \(T=40\) and \(S_{f}=39\) combination reduced \(\overline{D}\) to 7.52 \(\upmu\)m and \(\sigma_{D}\) to 6.77 \(\upmu\)m while keeping 99.44% \(C_{f}\). ZeroCross would be the preferable option under this criterion, because an \(S_{f}=9\) and \(T=1\) combination achieved \(\overline{D}=6.25\upmu\)m and \(\sigma_{D}=6.51\upmu\)m. These results reinforced the idea that an a priori selection of processing conditions is a sine qua non condition to achieve reliable results. S02 showed a clear reduction in the range of adequate test combinations when using Canny. To clarify this circumstance, Figure 10 contains samples of contour points obtained with Canny for three different test combinations: \(T15/S39\), \(T40/S39\) and \(T75/S39\). The optimal combination under the accuracy priority criterion (\(T40;S_{f}39\)) provided clearly defined lines, although a small segment corresponding to a double contour can be observed in the \(0^{\circ}\) orientation sample and a small area without points was observed in the \(180^{\circ}\) orientation sample (Figure 10). These extracted contours provided excellent results in terms of coverage and accuracy (Table 4). Reducing \(T\) (\(T15\)) increased \(\overline{D}\) up to 14.97 \(\upmu\)m, and \(\sigma_{D}\) up to 8.56 \(\upmu\)m while simultaneously reaching a full coverage. Coverage improvement was achieved through an increment of multiple-contour detection issues (\(180^{\circ}\) orientation in Figure 10) which, on the other hand, reduced the overall accuracy. Using a higher threshold (\(T75\)), however, minimised multiple contour detection issues, at the cost of a lower coverage (\(C_{f}~{}=~{}92.5\%\)), which can be noticed in the complete loss of contour information around the \(180^{\circ}\) orientation.