A Visual Tool for the Analysis of Algorithms for Tomographic Fiber Reconstruction in Materials Science

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dc.contributor.authorFröhler, Bernharden_US
dc.contributor.authorElberfeld, Timen_US
dc.contributor.authorMöller, Torstenen_US
dc.contributor.authorHege, Hans-Christianen_US
dc.contributor.authorWeissenböck, Johannesen_US
dc.contributor.authorDe Beenhouwer, Janen_US
dc.contributor.authorSijbers, Janen_US
dc.contributor.authorKastner, Johannen_US
dc.contributor.authorHeinzl, Christophen_US
dc.contributor.editorGleicher, Michael and Viola, Ivan and Leitte, Heikeen_US
dc.date.accessioned2019-06-02T18:27:42Z
dc.date.available2019-06-02T18:27:42Z
dc.date.issued2019
dc.description.abstractWe present visual analysis methods for the evaluation of tomographic fiber reconstruction algorithms by means of analysis, visual debugging and comparison of reconstructed fibers in materials science. The methods are integrated in a tool (FIAKER) that supports the entire workflow. It enables the analysis of various fiber reconstruction algorithms, of differently parameterized fiber reconstruction algorithms and of individual steps in iterative fiber reconstruction algorithms. Insight into the performance of fiber reconstruction algorithms is obtained by a list-based ranking interface. A 3D view offers interactive visualization techniques to gain deeper insight, e.g., into the aggregated quality of the examined fiber reconstruction algorithms and parameterizations. The tool was designed in close collaboration with researchers who work with fiber-reinforced polymers on a daily basis and develop algorithms for tomographic reconstruction and characterization of such materials. We evaluate the tool using synthetic datasets as well as tomograms of real materials. Five case studies certify the usefulness of the tool, showing that it significantly accelerates the analysis and provides valuable insights that make it possible to improve the fiber reconstruction algorithms. The main contribution of the paper is the well-considered combination of methods and their seamless integration into a visual tool that supports the entire workflow. Further findings result from the analysis of (dis-)similarity measures for fibers as well as from the discussion of design decisions. It is also shown that the generality of the analytical methods allows a wider range of applications, such as the application in pore space analysis.en_US
dc.description.number3
dc.description.sectionheadersVectors and Features
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume38
dc.identifier.doi10.1111/cgf.13688
dc.identifier.issn1467-8659
dc.identifier.pages273-283
dc.identifier.urihttps://doi.org/10.1111/cgf.13688
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf13688
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectKeywords Simulation
dc.subjectparameter space analysis
dc.subjectensemble visualization
dc.subjectindustrial CT
dc.titleA Visual Tool for the Analysis of Algorithms for Tomographic Fiber Reconstruction in Materials Scienceen_US
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