| About this Abstract |
| Meeting |
2021 TMS Annual Meeting & Exhibition
|
| Symposium
|
Data Science and Analytics for Materials Imaging and Quantification
|
| Presentation Title |
Improved EBSD Indexing through Non-Local Pattern Averaging |
| Author(s) |
David J. Rowenhorst, Patrick Brewick |
| On-Site Speaker (Planned) |
David J. Rowenhorst |
| Abstract Scope |
Electron Backscattered Diffraction has become a widely used technique for the characterization of polycrystalline materials. While recent advances in detector technology have greatly increased data collection speeds, the total time for collection can still be a significant limiting factor for many analyses, especially in low signal-to-noise situations. This work takes lessons learned from de-noising algorithms in image processing to develop a Non-Local Pattern Averaging Reindexing (NLPAR) method that can utilize the highly redundant information contained within most EBSD scans to enhance the the pattern quality without losing signal integrity near the interface boundaries, all the while operating on computational timescales that are similar to the traditional Hough based indexing algorithms. A benchmark case study within nickel will be presented as well as examples that in martensitic steels and aluminum alloys which show that data can be collected 2-3x faster than with traditional methods. |
| Proceedings Inclusion? |
Planned: |