| Abstract Scope |
There have been significant advances in the ability to collect and index electron back-scattered diffraction (EBSD) data, with collection speeds increasing an order of magnitude in the last decade, and advanced indexing method have greatly increased the accuracy and precision of indexing methods, but often require significant computational resources. Meanwhile new data collection modes, such as in-situ studies or 3D serial-sectioning methods would greatly benefit from fast indexing methods that can be tightly integrated into real-time analysis, something difficult with current commercial software packages. Here, we present a new indexing algorithm and software package that combines the traditional Hough/Radon-based methods and modified band voting with modern GPU processing. The current implementation indexes EBSD patterns >20,000 patterns/sec on typical desktop hardware, with indexing accuracy <0.1° misorientation. The algorithm is presented as a Python package with an open source license, making it available for the community to utilize and advance. |