## 3 Results and Discussion  
The stereo images recorded by the DIC system were processed using an in-house developed Matlab DIC code with large deformation capabilities [40]. A 5-pixels grid of control points was defined on the entire plate surface, and a 13 \(\times\) 13 pixels subset with bicubic grey-level interpolation was used to perform a hybrid local-global DIC image registration [40]. The Scale Invariant Feature Transform algorithm (SIFT, [41]) served to initialize the image registration by detecting and matching a sparse distribution of features in each image pair. Unlike DIC, SIFT is not sensitive to rotation and scale transformation between images and was therefore able to effectively deal with the large perspective distortion between the right (reference) and left (current) views (Figure 3). The sparse and noisy disparity maps obtained with SIFT were first fitted with NURBS and then used to coarsely morph the current image into its reference counterpart according to the iterative Image Morphing Method [40]. This generated two fairly similar images, which were then easily correlated with DIC. The resulting regular and dense set of point pairs was used to generate an updated and more accurate pair of disparity maps to be used for the next iteration. The process continued until convergence, i.e., until the mean distance between the matched point grid in the morphed current image and the reference image was less than a given threshold [40]. The correlated points in the four images of Figure 3 were then used to reconstruct the 3D position of the same set of surface points in the non-deformed and deformed configurations. No filtering was applied to the obtained shape and deformation data reported in this paper. Figure 3: Left (**a**) and right (**b**) views of the plate in its undeformed state and after being welded into the final traction frame subassembly (**c**,**d**). Note the wear of the speckle pattern on the upper and lower horizontal edges of the welded assembly due to the frictional contact with the workshop bench during the welding operations. The raw experimental data of the shape measurement of the undeformed plate are shown in Figure 4. DIC data were reconstructed in the reference system attached to the 3D calibration frame used to calibrate the stereo system. The reconstructed geometry was thus repositioned into a new reference system, with the _xy_ plane defined as the best-fitting plane of the front plate in its undeformed configuration with its origin at the center of the circular hole (Figure 4a). Comparison of the z-coordinate contour plots in Figure 4c,d shows a significant deviation from the nominal geometry prior to welding. In particular, the central region around the hole is not flat and the left lateral wing of the plate shows a significant curvature in the vertical direction. A single pair of images was sufficient to accurately retrieve the full-surface geometry of the front plate. The superiority of DIC over a CMM is evident when comparing the scarce and sparse set of depth data obtained from the latter measurement, with a regular distribution of more than \(8\times 10^{4}\) DIC data points from which information can be extracted on the deviation from flatness and on the local slope of the surface in any direction. The front plate was then taken to the PROMEC workshop and welded to the other parts of the final assembly according to the standard technological procedures of the industrial partner involved in this study (see the sequence of welding operations in Figure 5). The paint used to create the speckle pattern successfully withstood the high temperatures reached during the welding operations. However, in the first welding step, the plate had to be placed face-down on the workshop bench.