grains reconstruction from 2d EBSD data
Syntax
[grains, ebsd.grainId] = calcGrains(ebsd,'angle',10*degree)% reconstruction low and high angle grain boundaries
lagb = 2*degree;
hagb = 10*degree;
grains = calcGrains(ebsd,'angle',[hagb lagb])% allow grains to grow into not indexed regions
grains = calcGrains(ebsd('indexed'),'angle',10*degree)% do not allow grains to grow into not indexed regions
grains = calcGrains(ebsd,'unitCell')% follow non convex outer boundary
grains = calcGrains(ebsd,'boundary','tight')% specify phase dependent thresholds
% thresholds follow the same order as ebsd.CSList and should have the same length
grains = calcGrains(ebsd,'angle',{angl_1 angle_2 angle_3})% Markovian clustering algorithm
p = 1.5; % inflation power (default = 1.4)
maxIt = 10; % number of iterations (default = 4)
delta = 5*degree % variance of the threshold angle
grains = calcGrains(ebsd,'method','mcl',[p maxIt],'soft',[angle delta])Input
| ebsd | EBSD |
Output
| grains | grain2d |
| ebsd.grainId | grainId of each pixel |
Options
| threshold, angle | array of threshold angles per phase of mis/disorientation in radians |
| minPixel | minimum number of pixels that form a grain |
| boundary | bounds the spatial domain ('convexhull', 'tight') |
| maxDist | maximum distance to for two pixels to be in one grain (default inf) |
| fmc | fast multiscale clustering method |
| mcl | Markovian clustering algorithm |
| custom | use a custom property for grain separation |
Flags
| unitCell | omit Voronoi decomposition and treat a unitcell lattice |
| qhull | use qHull for the Voronoi decomposition |
References
- F.Bachmann, R. Hielscher, H. Schaeben, Grain detection from 2d and 3d EBSD data - Specification of the MTEX algorithm: Ultramicroscopy, 111, 1720-1733, 2011
- C. McMahon, B. Soe, A. Loeb, A. Vemulkar, M. Ferry, L. Bassman, Boundary identification in EBSD data with a generalization of fast multiscale clustering, Ultramicroscopy, 2013, 133:16-25.