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Quantitative 3D Reconstruction from Scanning Electron Microscope Images Based on Affine Camera Models.

Stefan Töberg1, Eduard Reithmeier1

  • 1Institute of Measurement and Automatic Control, Faculty of Mechanical Engineering, Leibniz University Hannover, Nienburger Str. 17, 30167 Hannover, Germany.

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Summary
This summary is machine-generated.

This study presents a new method for creating 3D surface reconstructions from scanning electron microscope (SEM) images. The technique uses affine epipolar geometry for accurate depth mapping of microscale specimens.

Keywords:
3D reconstructionaffine cameradense point cloudepipolar geometryrectificationregistrationscanning electron microscopeself calibrationtriangulation

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Area of Science:

  • Materials Science
  • Microscopy
  • Computer Vision

Background:

  • Scanning electron microscopes (SEMs) provide 2D images, limiting detailed morphological analysis.
  • Three-dimensional (3D) surface structure knowledge is crucial for comprehensive specimen characterization.

Purpose of the Study:

  • To develop a quantitative depth reconstruction routine for SEM image sequences.
  • To enable 3D morphological characterization of micro- and nanoscale specimens using SEM data.

Main Methods:

  • Utilizing affine camera models to describe SEM imaging properties.
  • Employing affine epipolar geometry, self-calibration via factorization, and triangulation from dense correspondences.
  • Adapting and extending rectification algorithms for affine stereo-pair images.

Main Results:

  • Quantitative 3D surface reconstruction from SEM image sequences.
  • Comparison of different affine camera sub-models to identify optimal parameters.
  • Validation of reconstruction accuracy against confocal laser scanning microscope (CLSM) measurements.

Conclusions:

  • The study specifies the applicability of affine camera models for SEM-based 3D reconstruction.
  • It provides insights into expected accuracies for self-calibration and dense matching algorithms in SEM imaging.