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3D optical flow for large CT data of materials microstructures

Tessa Nogatz, Claudia Redenbach, Katja Schladitz

2022Strain19 citationsDOIOpen Access PDF

Abstract

Abstract We compute three‐dimensional displacement vector fields to estimate the deformation of microstructural data sets in mechanical tests. For this, we extend the well‐known optical flow by Brox et al. to three dimensions, with special focus on the discretization of nonlinear terms. We evaluate our method first by synthetically deforming foams and comparing against this ground truth and second with data sets of samples that underwent real mechanical tests. Our results are compared to those from state‐of‐the‐art algorithms in materials science and medical image registration. By a thorough evaluation, we show that our proposed method is able to resolve the displacement best among all chosen comparison methods.

Topics & Concepts

Displacement (psychology)DiscretizationDeformation (meteorology)Focus (optics)Optical flowNonlinear systemFlow (mathematics)Image (mathematics)Ground truthMaterials scienceComputer scienceAlgorithmArtificial intelligenceMathematicsMathematical analysisComposite materialPhysicsGeometryOpticsPsychologyPsychotherapistQuantum mechanicsAdvanced Vision and ImagingAdvanced Image Processing TechniquesMedical Image Segmentation Techniques
3D optical flow for large CT data of materials microstructures | Litcius