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Instance Segmentation for Direct Measurements of Satellites in Metal Powders and Automated Microstructural Characterization from Image Data

  • Microstructure Characterization: Descriptors, Data-Intensive Techniques, and Uncertainty Quantification
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Abstract

We propose instance segmentation as a useful tool for image analysis in materials science. Instance segmentation is an advanced technique in computer vision which generates individual segmentation masks for every object of interest that is recognized in an image. Using an out-of-the-box implementation of Mask R-CNN, instance segmentation is applied to images of metal powder particles produced through gas atomization. Leveraging transfer learning allows for the analysis to be conducted with a very small training set of labeled images. As well as providing another method for measuring the particle size distribution, we demonstrate the first direct measurements of the satellite content in powder samples. After analyzing the results for the labeled data dataset, the trained model was used to generate measurements for a much larger set of unlabeled images. The resulting particle size measurements showed reasonable agreement with laser scattering measurements. The satellite measurements were self-consistent and showed good agreement with the expected trends for different samples. Finally, we present a small case study showing how instance segmentation can be used to measure spheroidite content in the UltraHigh Carbon Steel DataBase, demonstrating the flexibility of the technique.

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Acknowledgements

This work was supported by the National Science Foundation under Grant CMMI-1826218 and by the Air Force Research Laboratory under Cooperative Agreement No. FA8650-19-2-5209.

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Authors and Affiliations

  1. Materials Science and Engineering, Carnegie Mellon University, 5000 Forbes Ave., Pittsburgh, PA, 15213, USA

    Ryan Cohn & Elizabeth Holm

  2. Materials Science, Ames Laboratory, 311 Iowa State University, Ames, IA, 50011, USA

    Iver Anderson, Tim Prost, Jordan Tiarks & Emma White

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  1. Ryan Cohn
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  2. Iver Anderson
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Correspondence to Elizabeth Holm.

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Cohn, R., Anderson, I., Prost, T. et al. Instance Segmentation for Direct Measurements of Satellites in Metal Powders and Automated Microstructural Characterization from Image Data. JOM 73, 2159–2172 (2021). https://doi.org/10.1007/s11837-021-04713-y

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