Clustering on the Unit Hypersphere using von Mises-Fisher Distributions
The Journal of Machine Learning Research
Image Analysis and Mathematical Morphology
Image Analysis and Mathematical Morphology
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Stochastic modeling of a material microstructure is in general composed of multiple steps. First, geometric properties of the sample are measured by image analysis. Second, an appropriate stochastic model is chosen and model parameters are estimated from the geometric properties. Third, additional characteristics are computed on the data set and on realizations of stochastic models to evaluate the quality of the fitting. In this article, we show how to measure geometric properties of a fiber system, estimate parameters for two different fiber models, and evaluate the realizations with orientation covariance and tortuosity of the fibers. The considered stochastic models are the newly developed bended fiber model, composed of a force-biased packing of ball chains, and the classical cherry-pit cylinder model. We show the advantages and limitations of both methods.