Automated Evaluation of Kikuchi Patterns by Means of Radon and Fast Fourier Transformation, and Verification by an Artificial Neural Network | Zendy

Schwarzer R.A. | Zendy; Sukkau J. | Zendy

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Automated Evaluation of Kikuchi Patterns by Means of Radon and Fast Fourier Transformation, and Verification by an Artificial Neural Network

Author(s) -

Schwarzer R.A.,

Sukkau J.

Publication year - 2003

Publication title -

advanced engineering materials

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.938

H-Index - 114

eISSN - 1527-2648

pISSN - 1438-1656

DOI - 10.1002/adem.200300374

Subject(s) - fast fourier transform , radon transform , materials science , fourier transform , transformation (genetics) , electron backscatter diffraction , radon , texture (cosmology) , orientation (vector space) , lattice (music) , diffraction , optics , computer science , artificial intelligence , acoustics , geometry , mathematics , physics , algorithm , mathematical analysis , chemistry , biochemistry , quantum mechanics , image (mathematics) , gene

Automated crystal orientation measurement (ACOM) in the SEM by interpreting backscatter Kikuchi patterns (see Figure) has become a standard tool of quantitative texture analysis in materials science during the last decade. A Radon transformation of the diffraction pattern, in combination with a 1D fast Fourier transformation, enables the fast extraction of the positions of Kikuchi bands. The high‐frequency coefficients of the 1D FFT are used to define pattern quality as a measure of lattice imperfection and residual stress of the real crystal structure.

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