Variance Comparison for Volumetric Industrial CT Data

This paper proposes a novel technique for the direct comparison of a surface model with the corresponding industrial CT volume. We do not require the generation of a mesh from the CT scan and instead perform comparison directly with the raw volume dataset. Our technique uses the information from the surface model to locate corresponding points in the CT dataset. We then compute various comparison metrics to perform distance analysis and normal analysis. The metrics are presented to the user both visually as well as quantitatively. The comparison techniques are divided into two groups namely geometry-driven comparison techniques and visual-driven comparison techniques. The geometry-driven techniques color code the datasets and render distance glyphs to provide an overview, while the visual-driven techniques can be used for a localized examination and for determining precise information about the deviation between the datasets.