Advanced Tools for EBSD Processing
Merengue 2 ALGrId Utilities

Brief Description

Illustration of Algrid PerformancesALGrId stands for "Anti-Leak" GRain IDentification". It is an algorithm which allows to perform a grain identification in an EBSD map beyond the angular resolution of the map.
It was inspired by "Grain Boundary Completion" which is available in Channel5 software, but has an improved efficiency.

Principle

The detailed description of the method and its validation is described in [1]. The identification of grains with ALGrId starts with a classical identification using floodfill algorithm []. This detection requires a tolerance angle Omega1 and identifies as grains cluster of pixels connected to each other by a disorientation angle lower than Omega1.
In the map, some boundaries may have a disorientation angle > Omega1 but do not belong to a identified grain boundaries. They are the "markers" of a low angle boundaries and may be closed by AlGrId to sub-divise further the clusters.

Features

This version of the software calculates:
  • GOS (Grain Orientation Spread) [2]
  • GROD (Grain Reference Orientation Deviation) [2]
  • Provides a grain list with equivalent diameters
  • Provides a neighboring list with misorientation angles
This is more a demonstrator of what ALGrId is capable than a real analysis software. In any case, if you want more data extrated from an EBSD map from ALGrId - Grain detection, feel free to ask directly Lionel Germain.

Downloads

To install please read the ALGrId_install.txt file. This code generate some statistics about grain size and average disorientations between grains but more functionality could be added to it. Any feed back is appreciated

Publications

  • [1] Germain, L., Krastsch, D., Salib, M. & Gey, N. (2014). Identification of sub-grains and low angle boundaries beyond the angular resolution of EBSD maps. Materials Characterization 98, 66–72.
  • [2] Wright SI, Nowell MM, Field DP. Microscopy and Microanalysis 2011;17:316.

Copyright Lionel Germain
This work was conducted with the financial support of : Université de Lorraine CNRS Labex DAMAS