• DocumentCode
    2222983
  • Title

    Application of advanced image processing techniques to automatic Kikuchi lines detection

  • Author

    Fraczek, Rafal ; Zielinski, Tomasz

  • Author_Institution
    Instrum. & Meas. Dept., AGH Univ. of Sci. & Technol., Cracow, Poland
  • fYear
    2006
  • fDate
    4-8 Sept. 2006
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Automated crystal orientation measurement (ACOM) in the scanning electron microscope (SEM) is a standard technique of texture analysis (pattern recognition) that is used in materials science. The measurement is carried out by interpreting backscatter Kikuchi patterns, in particular by the extraction of the position of so-called Kikuchi bands, i.e. pairs of parallel lines. Their detection strongly depends on appropriate processing of a source image, which usually is highly corrupted by noise and has uneven background illumination. Such advanced processing is addressed in this paper. It exploits wavelet transform based de-noising as well as curve modification and curvelet transform based contrast enhancement methods. Additionally, directional, ridge detection type 2D filters are used for searching lines missing to pairs.
  • Keywords
    crystal orientation; curvelet transforms; electron diffraction crystallography; image denoising; image enhancement; image filtering; image texture; object detection; scanning electron microscopes; wavelet transforms; 2D filter; ACOM; Kikuchi band; SEM; automated crystal orientation measurement; automatic Kikuchi lines detection; backscatter Kikuchi pattern; contrast enhancement method; curve modification; curvelet transform; image processing technique; pattern recognition; ridge detection; scanning electron microscope; texture analysis; uneven background illumination; wavelet transform based denoising; Crystals; Microscopy; Noise; Noise reduction; Standards; Wavelet transforms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing Conference, 2006 14th European
  • Conference_Location
    Florence
  • ISSN
    2219-5491
  • Type

    conf

  • Filename
    7071534