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      Novel Remapping Approach for HR-EBSD based on Demons Registration

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          Abstract

          In this study, the possibility of utilizing a computer vision algorithm, i.e., demons registration, to accurately remap electron backscatter diffraction patterns for high resolution electron backscatter diffraction applications is presented. First, the angular resolution of demons registration is demonstrated to be lower than the conventional cross-correlation based method, particularly at misorientation angles > 9 degrees. In addition, GPU acceleration has been applied to significantly boost the speed of iterative registration between a pair of patterns with 10{\deg} misorientation to under 1s. Second, demons registration is implemented as a first-pass remapping, followed by a second pass cross-correlation method, which results in angular resolution of ~0.5*10-4 degrees, a phantom stress value of ~35MPa and phantom strain of ~2*10-4, on dynamically simulated patterns, without the need of implementing robust fitting or iterative remapping. Lastly, the new remapping method is applied to a large experimental dataset collected from an as-built additively-manufactured Inconel 625 cube, which shows significant residual stresses built-up near the large columnar grain region and regularly arranged GND structures.

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          Most cited references 17

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          Image matching as a diffusion process: an analogy with Maxwell's demons.

           J.-P. Thirion (1998)
          In this paper, we present the concept of diffusing models to perform image-to-image matching. Having two images to match, the main idea is to consider the objects boundaries in one image as semi-permeable membranes and to let the other image, considered as a deformable grid model, diffuse through these interfaces, by the action of effectors situated within the membranes. We illustrate this concept by an analogy with Maxwell's demons. We show that this concept relates to more traditional ones, based on attraction, with an intermediate step being optical flow techniques. We use the concept of diffusing models to derive three different non-rigid matching algorithms, one using all the intensity levels in the static image, one using only contour points, and a last one operating on already segmented images. Finally, we present results with synthesized deformations and real medical images, with applications to heart motion tracking and three-dimensional inter-patients matching.
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            High-resolution elastic strain measurement from electron backscatter diffraction patterns: new levels of sensitivity.

            In this paper, we demonstrate that the shift between similar features in two electron backscatter diffraction (EBSD) patterns can be measured using cross-correlation based methods to +/- 0.05 pixels. For a scintillator screen positioned to capture the usual large solid angle employed in EBSD orientation mapping this shift corresponds to only approximately 8.5 x 10(-5)rad at the pattern centre. For wide-angled EBSD patterns, the variation in the entire strain and rotation tensor can be determined from single patterns. Repeated measurements of small rotations applied to a single-crystal sample, determined using the shifts at four widely separated parts of the EBSD patterns, showed a standard deviation of 1.3 x 10(-4) averaged over components of the displacement gradient tensor. Variations in strains and rotations were measured across the interface in a cross-sectioned Si1-x Gex epilayer on a Si substrate. Expansion of the epilayer close to the section surface is accommodated by tensile strains and lattice curvature that extend a considerable distance into the substrate. Smaller and more localised shear strains are observed close to the substrate-layer interface. EBSD provides an impressive and unique combination of high strain sensitivity, high spatial resolution and ease of use.
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              Additive manufacturing of metallic components – Process, structure and properties

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                Author and article information

                Journal
                12 July 2019
                1907.05993

                http://arxiv.org/licenses/nonexclusive-distrib/1.0/

                Custom metadata
                physics.comp-ph cond-mat.mtrl-sci

                Condensed matter, Mathematical & Computational physics

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