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IJMLC 2021 Vol.11(4): 317-322 ISSN: 2010-3700
DOI: 10.18178/ijmlc.2021.11.4.1054

Grain Size Characterization of Ceramic Matrix Composites

Gao Xiang, Tan Rong, Li Guanghui, and Yao Leijiang

Abstract—In the field of materials science, the mesoscopic geometry of materials is of great significance for the research and development of materials and materials. This paper mainly focuses on the image data of existing ceramic matrix composites, and studies the characterization method of grain image of ceramic matrix, which realizes the accurate characterization of grain size. It has important practical research on the mesostructure of ceramic matrix composites. Value. Taking the SEM grain image of 5μm resolution of self-toughening silicon nitride (Si3N4) ceramic as an example, the grain image is segmented by median filtering, image binarization and watershed algorithm, and then used to directional bounding box (Oriented). The Bounding Boxes, OBB) algorithm finds the rectangular outline bounding box of the grain, enabling accurate measurement and statistics of the grain size.

Index Terms—Ceramic Matrix Composites (CMC), grain size characterization, digital image processing, Oriented Bounding Boxes (OBB).

Gao Xiang and Li Guanghui are with the School of Computer Science, Northwestern Polytechnical University, Xi’an, Shaanxi 710129 China (e-mail: gaoxg@nwpu.edu.cn, sxlllslgh@mail.nwpu.edu.cn).
Tan Rong is with the School of Software, Northwestern Polytechnical University, Xi’an, Shaanxi 710129 China (e-mail: tanrong@mail.nwpu.edu.cn).
Yao Leijiang is with the School of Laboratory of Science and Technology on UAV, Northwestern Polytechnical University, Xi’an 710072 China (e-mail: yaolj@nwpu.edu.cn).


Cite: Gao Xiang, Tan Rong, Li Guanghui, and Yao Leijiang, "Grain Size Characterization of Ceramic Matrix Composites," International Journal of Machine Learning and Computing vol. 11, no. 4, pp. 317-322, 2021.

Copyright © 2021 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

General Information

  • E-ISSN: 2972-368X
  • Abbreviated Title: Int. J. Mach. Learn.
  • Frequency: Quaterly
  • DOI: 10.18178/IJML
  • Editor-in-Chief: Dr. Lin Huang
  • Executive Editor:  Ms. Cherry L. Chen
  • Abstracing/Indexing: Inspec (IET), Google Scholar, Crossref, ProQuest, Electronic Journals LibraryCNKI.
  • E-mail: ijml@ejournal.net

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