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Employing Constrained Nonnegative Matrix Factorization for Microstructure Segmentation.
Chauniyal, Ashish; Thome, Pascal; Stricker, Markus.
Afiliação
  • Chauniyal A; Interdisciplinary Centre for Advanced Materials Simulation (ICAMS), Ruhr-Universität Bochum, Univeristätstraße 150 44780, Bochum, Germany.
  • Thome P; Institute for Materials (IFM), Ruhr-Universität Bochum, Univeristätstraße 150 44780, Bochum, Germany.
  • Stricker M; Interdisciplinary Centre for Advanced Materials Simulation (ICAMS), Ruhr-Universität Bochum, Univeristätstraße 150 44780, Bochum, Germany.
Microsc Microanal ; 30(4): 712-723, 2024 Aug 21.
Article em En | MEDLINE | ID: mdl-38976492
ABSTRACT
Materials characterization using electron backscatter diffraction (EBSD) requires indexing the orientation of the measured region from Kikuchi patterns. The quality of Kikuchi patterns can degrade due to pattern overlaps arising from two or more orientations, in the presence of defects or grain boundaries. In this work, we employ constrained nonnegative matrix factorization to segment a microstructure with small grain misorientations, (<1∘), and predict the amount of pattern overlap. First, we implement the method on mixed simulated patterns-that replicates a pattern overlap scenario, and demonstrate the resolution limit of pattern mixing or factorization resolution using a weight metric. Subsequently, we segment a single-crystal dendritic microstructure and compare the results with high-resolution EBSD. By utilizing weight metrics across a low-angle grain boundary, we demonstrate how very small misorientations/low-angle grain boundaries can be resolved at a pixel level. Our approach constitutes a versatile and robust tool, complementing other fast indexing methods for microstructure characterization.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Microsc Microanal Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Microsc Microanal Ano de publicação: 2024 Tipo de documento: Article