Image-based magnification calibration for electron microscope

Koichi Ito, Ayako Suzuki, Takafumi Aoki, Ruriko Tsuneta

Research output: Contribution to journalArticlepeer-review

Abstract

Magnification calibration is a crucial task for the electron microscope to achieve accurate measurement of the target object. In general, magnification calibration is performed to obtain the correspondence between the scale of the electron microscope image and the actual size of the target object using the standard calibration samples. However, the current magnification calibration method mentioned above may include a maximum of 5 % scale error, since an alternative method has not yet been proposed. Addressing this problem, this paper proposes an image-based magnification calibration method for the electron microscope. The proposed method employs a multi-stage scale estimation approach using phase-based correspondence matching. Consider a sequence of microscope images of the same target object, where the image magnification is gradually increased so that the final image has a very large scale factor S (e.g.; S= 1,000) with respect to the initial image. The problem considered in this paper is to estimate the overall scale factor S of the given image sequence. The proposed scale estimation method provides a new methodology for high-accuracy magnification calibration of the electron microscope. This paper also proposes a quantitative performance evaluation method of scale estimation algorithms using Mandelbrot images which are precisely scale-controlled images. Experimental evaluation using Mandelbrot images shows that the proposed scale estimation algorithm can estimate the overall scale factor S=1,000 with approximately 0.1 % scale error. Also, a set of experiments using image sequences taken by an actual scanning transmission electron microscope (STEM) demonstrates that the proposed method is more effective for magnification calibration of a STEM compared with a conventional method.

Original languageEnglish
Pages (from-to)185-197
Number of pages13
JournalMachine Vision and Applications
Volume25
Issue number1
DOIs
Publication statusPublished - 2014 Jan

Keywords

  • Correspondence matching
  • Electron microscope
  • Image matching
  • Phase-only correlation
  • Scale estimation

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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