Similarity Measure for Fiber Clustering: A Constant Time Complexity Algorithm

Quan, Tran Anh; Vo, Bay

doi:10.1109/kse.2015.48

Cited by 1 publication

(1 citation statement)

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“…For example O'Donnel and Westin [OW07] employ a distance based on the mean closest point distance between two fibers. Quan and Vo [QV15] propose a measure based on the center of mass as well as the start and end point of each fiber. Bhattacharya et al [BWW * 17] employ distance measures for the clustering of fiber tracts of industrial fiber-reinforced materials into fiber bundles.…”

Section: Background and Related Workmentioning

confidence: 99%

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

Fröhler

Elberfeld

Möller

et al. 2019

Computer Graphics Forum

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We 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.

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Section: Background and Related Workmentioning

confidence: 99%