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Automated image processing for grain boundary analysis.

Sowmya Mahadevan1, David Casasent

  • 1Department of Electrical and Computer and Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA.

Ultramicroscopy
|April 4, 2003
PubMed
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Automated image processing accurately locates grain boundaries and triple junctions in scanning electron microscopy. This enables precise calculation of dihedral angles and selection of probe points for grain orientation analysis.

Area of Science:

  • Materials Science
  • Image Analysis
  • Microscopy

Background:

  • Scanning electron microscopy (SEM) generates complex images requiring sophisticated analysis.
  • Understanding grain boundaries and triple junctions is crucial for material properties.

Purpose of the Study:

  • To describe image processing techniques for automated analysis of SEM images.
  • To detail methods for identifying key microstructural features and deriving quantitative data.

Main Methods:

  • Image processing algorithms for locating grain boundaries and triple junctions.
  • Calculation of dihedral angles at triple junctions.
  • Selection of electron backscatter diffraction (EBSD) probe points for orientation mapping.

Main Results:

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  • Successful automated identification of grain boundaries and triple junctions.
  • Accurate computation of dihedral angles.
  • Efficient selection of EBSD probe points for reliable grain orientation data.

Conclusions:

  • The described image processing enables robust automated analysis of microstructural features in SEM.
  • This methodology facilitates quantitative characterization of materials at the microstructural level.