Hostname: page-component-cd9895bd7-dzt6s Total loading time: 0 Render date: 2024-12-25T06:51:19.915Z Has data issue: false hasContentIssue false
  • English
  • Français

An Open-Source Engine for the Processing of Electron Backscatter Patterns: EBSD-Image

Published online by Cambridge University Press:  06 May 2011

Philippe T. Pinard ,
Marin Lagacé ,
Pierre Hovington ,
Denis Thibault  and
Raynald Gauvin
Philippe T. Pinard*
Affiliation:
Materials and Mining Engineering Department, McGill University, 3610 University Street, Montreal, Quebec H3A 2B2, Canada
Marin Lagacé
Affiliation:
Materials Science Department, Institut de recherche d'Hydro-Québec, 1800 Lionel-Boulet Boulevard, Varennes, Québec J3Z 1S1, Canada
Pierre Hovington
Affiliation:
Materials Science Department, Institut de recherche d'Hydro-Québec, 1800 Lionel-Boulet Boulevard, Varennes, Québec J3Z 1S1, Canada
Denis Thibault
Affiliation:
Materials Science Department, Institut de recherche d'Hydro-Québec, 1800 Lionel-Boulet Boulevard, Varennes, Québec J3Z 1S1, Canada
Raynald Gauvin
Affiliation:
Materials and Mining Engineering Department, McGill University, 3610 University Street, Montreal, Quebec H3A 2B2, Canada
*
Corresponding author. E-mail: [email protected]
Get access

Abstract

An open source software package dedicated to processing stored electron backscatter patterns is presented. The package gives users full control over the type and order of operations that are performed on electron backscatter diffraction (EBSD) patterns as well as the results obtained. The current version of EBSD-Image (www.ebsd-image.org) offers a flexible and structured interface to calculate various quality metrics over large datasets. It includes unique features such as practical file formats for storing diffraction patterns and analysis results, stitching of mappings with automatic reorganization of their diffraction patterns, and routines for processing data on a distributed computer grid. Implementations of the algorithms used in the software are described and benchmarked using simulated diffraction patterns. Using those simulated EBSD patterns, the detection of Kikuchi bands in EBSD-Image was found to be comparable to commercially available EBSD systems. In addition, 24 quality metrics were evaluated based on the ability to assess the level of deformation in two samples (copper and iron) deformed using 220 grit SiC grinding paper. Fourteen metrics were able to properly measure the deformation gradient of the samples.

Keywords

EBSDpost-processingEBSPimage qualityimage analysisdeformation
Type
Electron Backscatter Diffraction Special Section
Information
Microscopy and Microanalysis , Volume 17 , Issue 3 , June 2011 , pp. 374 - 385
Copyright
Copyright © Microscopy Society of America 2011

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Brewer, L.N., Field, D.P. & Merriman, C.C. (2009). Mapping and assessing plastic deformation using EBSD. In Electron Backscatter Diffraction in Materials Science, Schwartz, A.J., Kumar, M., Adams, B.L. & Field, D.P. (Eds.), pp. 251–262. New York: Springer.CrossRefGoogle Scholar
Brough, I. & Humphreys, F.J. (2010). Evaluation and application of a fast EBSD detector. Mater Sci Technol 26, 636–639.CrossRefGoogle Scholar
Cizmar, P., Vladár, A.E., Ming, B. & Postek, M.T. (2008). Simulated SEM images for resolution measurement. Scanning 30, 381–391.CrossRefGoogle ScholarPubMed
Frank, J. & Al-Ali, L. (1975). Signal-to-noise ratio of electron micrographs obtained by cross-correlation. Nature 256, 376–379.CrossRefGoogle ScholarPubMed
Gonzalez, R.C. & Woods, R.E. (2007). Digital Image Processing. 3rd ed. Upper Saddle River, NJ: Prentice Hall.Google Scholar
Hielscher, H. & Schaeben, H. (2008). A novel pole figure inversion method: Specification of the MTEX algorithm. J Appl Crystallog 41, 1024–1037.CrossRefGoogle Scholar
Hovington, P., Pinard, P.T., Lagacé, M., Rodrigue, L., Gauvin, R. & Trudeau, M.L. (2009). Towards a more comprehensive microstructural analysis of Zr-2.5Nb pressure tubing using image analysis and electron backscattered diffraction (EBSD). J Nucl Mater 393, 162–174.CrossRefGoogle Scholar
Humphreys, F.J. (2004). Characterisation of fine-scale microstructures by electron backscatter diffraction (EBSD). Scripta Mater 51, 771–776.CrossRefGoogle Scholar
Kapur, J.N., Sahoo, P.K. & Wong, A.K.C. (1985). A new method for gray level picture thresholding using the entropy of the histogram. Comput Vis Graphics Image Process 29, 273–285.CrossRefGoogle Scholar
Keller, R.R., Roshko, A., Geiss, R.H., Bertness, K.A. & Quinn, T.P. (2004). EBSD measurement of strains in GaAs due to oxidation of buried AlGaAs layers. Microelec Eng 75, 96–102.CrossRefGoogle Scholar
Kittler, J. & Illingworth, J. (1986). Minimum error thresholding. Pattern Recogn 19, 41–47.CrossRefGoogle Scholar
Krieger Lassen, N.C. (1994). Automated determination of crystal orientations from electron backscattering patterns. PhD thesis, The Technical University of Denmark.Google Scholar
Krieger Lassen, N.C. (1998). Automatic high-precision measurements of the location and width of Kikuchi bands in electron backscatter diffraction patterns. J Microsc 190, 375–391.CrossRefGoogle Scholar
Petrov, R., Kestens, L., Wasilkowska, A. & Houbaert, Y. (2007). Microstructure and texture of a lightly deformed TRIP-assisted steel characterized by means of the EBSD technique. Mater Sci Eng A 447, 285–297.CrossRefGoogle Scholar
Ryde, L. (2006). Application of EBSD to analysis of microstructure in commercial steels. Mater Sci Technol 22, 1297–1306.CrossRefGoogle Scholar
Samuels, L.E. (2003). Metallographic Polishing, 4th ed. Materials Park, OH: ASM International.Google Scholar
Schwarzer, R.A. & Hjelen, J. (2010). Orientation microscopy with fast EBSD. Mater Sci Technol 26, 646–649.CrossRefGoogle Scholar
Tao, X. (2003). An EBSD study on mapping of small orientation differences in lattice mismatched heterostructures. PhD thesis, Lehigh University.Google Scholar
Tao, X. & Eades, A. (2005). Errors, artifacts, and improvements in EBSD processing and mapping. Microsc Microanal 11, 79–97.CrossRefGoogle ScholarPubMed
Wilkinson, A.K. & Dingley, D.J. (1991). Quantitative deformation studies using electron backscatter patterns. Acta Metall Mater 39, 3047–3055.CrossRefGoogle Scholar
Wilkinson, A.J., Meaden, G. & Dingley, D.J. (2005). High-resolution elastic strain measurement from electron backscatter diffraction patterns: New levels of sensitivity. Ultramicroscopy 106, 307–313.CrossRefGoogle ScholarPubMed
Wright, S.I. (1992). Individual lattice orientation measurements development and application of a fully automatic technique. PhD thesis, Yale University.Google Scholar
Wright, S.I. & Nowell, M.M. (2006). EBSD image quality mapping. Microsc Microanal 12, 72–84.CrossRefGoogle ScholarPubMed
Wu, J., Wray, P.J., Garcia, C.I., Hua, M. & Deardo, A.J. (2005). Image quality analysis: A new method of characterizing microstructures. ISIJ Int 45, 254–262.CrossRefGoogle Scholar