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Open AccessArticle

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

Institute of Measurement and Automatic Control, Faculty of Mechanical Engineering, Leibniz University Hannover, Nienburger Str. 17, 30167 Hannover, Germany
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Sensors 2020, 20(12), 3598; https://doi.org/10.3390/s20123598
Received: 29 April 2020 / Revised: 21 June 2020 / Accepted: 23 June 2020 / Published: 26 June 2020
(This article belongs to the Special Issue Sensing and Processing for 3D Computer Vision)
Scanning electron microscopes (SEMs) are versatile imaging devices for the micro- and nanoscale that find application in various disciplines such as the characterization of biological, mineral or mechanical specimen. Even though the specimen’s two-dimensional (2D) properties are provided by the acquired images, detailed morphological characterizations require knowledge about the three-dimensional (3D) surface structure. To overcome this limitation, a reconstruction routine is presented that allows the quantitative depth reconstruction from SEM image sequences. Based on the SEM’s imaging properties that can be well described by an affine camera, the proposed algorithms rely on the use of affine epipolar geometry, self-calibration via factorization and triangulation from dense correspondences. To yield the highest robustness and accuracy, different sub-models of the affine camera are applied to the SEM images and the obtained results are directly compared to confocal laser scanning microscope (CLSM) measurements to identify the ideal parametrization and underlying algorithms. To solve the rectification problem for stereo-pair images of an affine camera so that dense matching algorithms can be applied, existing approaches are adapted and extended to further enhance the yielded results. The evaluations of this study allow to specify the applicability of the affine camera models to SEM images and what accuracies can be expected for reconstruction routines based on self-calibration and dense matching algorithms. View Full-Text
Keywords: scanning electron microscope; 3D reconstruction; affine camera; epipolar geometry; self calibration; rectification; triangulation; dense point cloud; registration scanning electron microscope; 3D reconstruction; affine camera; epipolar geometry; self calibration; rectification; triangulation; dense point cloud; registration
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Töberg, S.; Reithmeier, E. Quantitative 3D Reconstruction from Scanning Electron Microscope Images Based on Affine Camera Models. Sensors 2020, 20, 3598.

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