Fitting Laguerre tessellation approximations to tomographic image data
Fitting Laguerre tessellation approximations to tomographic image data
复制标题
将拉盖尔曲面细分近似拟合到断层扫描图像数据
DOI:
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发表时间:
2015
期刊:
影响因子:
--
通讯作者:
V. Schmidt
中科院分区:
文献类型:
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作者:
A. Spettl;T. Brereton;Q. Duan;Thomas Werz;C. Krill;Dirk P. Kroese;V. Schmidt
The analysis of polycrystalline materials benefits greatly from accurate quantitative descriptions of their grain structures. Laguerre tessellations approximate such grain structures very well. However, it is a quite challenging problem to fit a Laguerre tessellation to tomographic data, as a high-dimensional optimization problem with many local minima must be solved. In this paper, we formulate a version of this optimization problem that can be solved quickly using the cross-entropy method, a robust stochastic optimization technique that can avoid becoming trapped in local minima. We demonstrate the effectiveness of our approach by applying it to both artificially generated and experimentally produced tomographic data.
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影响因子:
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DOI:
10.1088/0965-0393/23/6/065001
发表时间:
2015-07
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