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Abstract

This chapter focuses on the automated determination of crystallographic orientation from electron backscatter diffraction (EBSD) patterns. Early systems required an operator skilled in crystallography to manually identify features in a captured pattern in order to determine the corresponding orientation. The computer would then determine the orientation from the manually supplied data. Modern automated systems use image-processing techniques to identify the features needed to determine the crystallographic orientation from diffraction patterns without any operator intervention. This chapter describes the different procedures used in achieving automated EBSD. Image processing techniques used to enhance the diffraction patterns will be briefly described; the manual zone axis indexing technique will be discussed for historical introduction; a description of the procedure for detecting the diffraction bands with a focus on the Hough transform will be given; methods for determining orientation using diffraction bands will be detailed; issues concerning automated indexing uncertainties will be discussed; a description of the relevant structural data needed by the computer to index the patterns will be given and finally methods for calibrating a system will described. Whereas this chapter will briefly introduce alternative approaches and give some reference material where applicable, the focus will be on those techniques most familiar to the author.

Keywords

Zone Axis Vote Scheme Vote Procedure Confidence Index Automate Indexing 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 2000

Authors and Affiliations

  • Stuart I. Wright
    • 1
  1. 1.TexSEM Laboratories (TSL)DraperUSA

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