This module allows the user to measure the displacement and strain errors from two repeat scans.
The user inputs a reference scan, a repeat scan, and defines the subset/element size window, and the script outputs a spreadsheet containing the mean and standard displacement/strain uncertainties for each subset/element size.
Data [required]: gray-level images of the reference and repeat images
Select the DVC approach. When using Local and Global, the datasets need to be regular and the texture needs to fully occupy the bounding box, Fig. 1a (note: in global the mesh is automatically generated). If the datasets are non-regular, Fig. 1b, a global approach is more suited and the user can use Global List to input the meshes (note: the user needs to generate the meshes separately either in Amira-Avizo or in a different software).
When using the local approach, this parameter allows the user to discard bad measurements from the displacement field. If the correlation value of a subset is below the filter threshold, the displacement vector is discarded and a median value is used instead.
If local approach is ticked, this parameter defines the size of the subvolumes. If global approach is ticked, it defines the Size of the elements. The script will calculate the mean and standard disp/strain uncertainties for each subvolume/element size ranging from Min to Max by increment of Step.
Mesh 1 (Mesh2>Mesh3>etc.):
If the dataset have non regular shapes (ex: tensile test specimen Fig 1b, CT specimen, etc.), the user can generate a separate mesh with a coarse mesh size and log it on Mesh1. Mesh2 can be used to generate a finer mesh (resp. Mesh3, Mesh4, etc.).
After running the script, the user can either export the spreadsheet to Excel or plot the results in Amira-Avizo. The displacement and strain uncertainties can be plotted against the subset/element size using the Plot Spreadsheet function.There is a trade-off between spatial resolution and standard disp/strain uncertainty, and the user needs to select the optimal subset/element size that gives enough confidence for his measurements.