Automated analysis of platelet microstructures using a feature length orientation space

Campbell, A. and Murray, P. and Yakushina, E. and Borocco, A. and Dokladal, P. and Decencière, P. and Ion, W. and Marshall, S. (2022) Automated analysis of platelet microstructures using a feature length orientation space. Journal of Materials Science, 57 (2). pp. 1448-1461. ISSN 0022-2461 (https://doi.org/10.1007/s10853-021-06630-6)

[thumbnail of Campbell-etal-JMS-2021-Automated-analysis-of-platelet-microstructures-using-a-feature]
Preview
Text. Filename: Campbell_etal_JMS_2021_Automated_analysis_of_platelet_microstructures_using_a_feature.pdf
Final Published Version
License: Creative Commons Attribution 4.0 logo

Download (2MB)| Preview

Abstract

The ability to measure elongated structures such as platelets and colonies, is an important step in the microstructural analysis of many materials. Widely used techniques and standards require extensive manual interaction making them slow, laborious, difficult to repeat and prone to human error. Automated approaches have been proposed but often fail when analysing complex microstructures. This paper addresses these challenges by proposing a new, automated image analysis technique, to reliably assess platelet microstructure. Tools from Mathematical Morphology are designed to probe the image and map the response onto a new feature-length orientation space (FLOS). This enables automated measurement of key microstructural features such as platelet width, orientation, globular volume fraction, and colony size. The method has a wide field of view, low dependency on input parameters, and does not require prior thresholding, common in other automated analysis techniques. Multiple datasets of complex Titanium alloys were used to evaluate the new techniques which are shown to match measurements from expert materials scientists using recognized standards, while drastically reducing measurement time and ensuring repeatability. The per-pixel measurement style of the technique also allows for the generation of useful colourmaps, that aid further analysis and provide evidence to increase user confidence in the quantitative measurements.

ORCID iDs

Campbell, A. ORCID logoORCID: https://orcid.org/0000-0002-4439-3630, Murray, P. ORCID logoORCID: https://orcid.org/0000-0002-6980-9276, Yakushina, E. ORCID logoORCID: https://orcid.org/0000-0001-6498-4502, Borocco, A., Dokladal, P., Decencière, P., Ion, W. ORCID logoORCID: https://orcid.org/0000-0003-0693-5942 and Marshall, S.;