3D LEAST SQUARES MATCHING APPLIED TO MICRO-TOMOGRAPHY DATA
- 1Institute of Photogrammetry and Remote Sensing, Technische Universität Dresden, Germany
- 2Department of Chemical and Materials Engineering, Pontifícia Universidade Católica do Rio de Janeiro (PUC-Rio), Rio de Janeiro, Brazil
- 3Institute of Construction Materials, Technische Universität Dresden, Germany
- 4University of Manchester at Harwell, Diamond Light Source, Harwell Science & Innovation Campus, Didcot, Oxfordshire OX11 0DE, UK
Keywords: 3D Least Squares Matching, Cuboid Tracking, Displacement Vector Field, Material Testing, Computed Tomography, In-situ Test
Abstract. The paper introduces 3D least squares matching as a technique to analyze multi-temporal micro-tomography data in civil engineering material testing. Time series of tomography voxel data sets are recorded during an in-situ tension test of a strain-hardening cement-based composite probe at consecutive load steps. 3D least squares matching is a technique to track cuboids in consecutive voxel data sets minimizing the sum of the squares of voxel value differences after a 12-parameter 3D affine transformation. For a regular grid of locations in each voxel data set of the deformed states, a subvoxel-precise 3D displacement vector field is computed. Discontinuities in these displacement vector fields indicate the occurrence of cracks in the probes during the load tests. These cracks are detected and quantitatively described by the computation of principal strains of tetrahedrons in a tetrahedral mesh, that is generated between the matching points. The subvoxel-accuracy potential of the technique allows the detection of very small cracks with a width much smaller than the actual voxel size.