Optimisation of EBSD indexing through pattern centre calibration and grain boundary refinement

To enhance the indexing rate of conventional electron backscatter diffraction (EBSD), this study employed EBSD to collect and analyse the mapping data of cubic phase materials. Kikuchi bands were identified using Hough transform, and the pattern centre was optimised through a genetic algorithm. Four objective functions were designed to investigate the influence of varying population sizes on the convergence of the algorithm. The results revealed that the calculation stabilised when the population size reached 400, with the HMAE (H-mean angular error) objective function exhibiting superior performance in screening by integrating the number of matched Kikuchi bands and mean angular error (MAE). Furthermore, to address indexing errors resulting from overlapping Kikuchi patterns at grain boundaries, an indexing optimisation method based on pattern similarity matching was proposed, significantly improving the indexing rate of EBSD mapping data. Finally, neighbourhood search strategy was implemented to further refine the indexing process, ensuring high indexing accuracy while substantially reducing computational time. This study offers novel methodologies and insights for improving the efficiency and precision of EBSD mapping data acquisition and analysis.