Automatic steel labeling on certain microstructural constituents with image processing and machine learning tools
Dmitry S. Bulgarevich
Susumu Tsukamoto
Tadashi Kasuya
Masahiko Demura
Makoto Watanabe
10.6084/m9.figshare.8057300.v2
https://tandf.figshare.com/articles/figure/Automatic_steel_labelling_on_certain_microstructural_constituents_with_image_processing_and_machine_learning_tools/8057300
<p>It is demonstrated that optical microscopy images of steel materials could be effectively categorized into classes on preset ferrite/pearlite-, ferrite/pearlite/bainite-, and bainite/martensite-type microstructures with image pre-processing and statistical analysis including the machine learning techniques. Though several popular classifiers were able to get the reasonable class-labeling accuracy, the random forest was virtually the best choice in terms of overall performance and usability. The present categorizing classifier could assist in choosing the appropriate pattern recognition method from our library for various steel microstructures, which we have recently reported. That is, the combination of the categorizing and pattern-recognizing methods provides a total solution for automatic quantification of a wide range of steel microstructures.</p>
2019-06-05 07:32:21
Metallurgy
machine learning
microstructures
optical microscopy
pattern recognition
10 Engineering and structural materials
106 Metallic materials
404 Materials informatics / Genomics
505 Optical / Molecular spectroscopy