Recent advances in 3D SEM surface reconstruction

Tafti, Ahmad P.; Kirkpatrick, Andrew B.; Alavi, Zahrasadat; Owen, Heather A.; Yu, Zeyun

doi:10.1016/j.micron.2015.07.005

Cited by 83 publications

(57 citation statements)

References 35 publications

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“…There has been a long interest in the development and application of microscale 3D characterization either using non‐invasive SEM by means of multi‐view photogrammetric techniques (3D SEM) or using destructive slice&view methods with focus ion beam milling (SEM‐FIB) . Figure C shows the result of applying the 3D SEM approach on the Cu‐Zn‐Al pellet using multi‐view photogrammetry on a collection of 2D SEM images acquired from 36 viewpoints around the catalyst body (see Experimental Section).…”

Section: Figurementioning

confidence: 99%

Accurate 3D Characterization of Catalytic Bodies Surface by Scanning Electron Microscopy

et al. 2019

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Catalytic bodies of millimetric dimensions are frequently used in industrial catalysis. The engineering process applied on the raw nanocatalyst during the fabrication and the working conditions affect the spatial and chemical relations of the exposed surface of the catalytic device. Hence, for improving their synthesis and for monitoring the evolution during its life cycle it is important understanding the actual heterogeneities of their surfaces. In this work scanning electron microscopy, photogrammetry and X‐Ray spectroscopy are combined to perform physico‐chemical characterization in three‐dimensions and with high resolution of the surface of commercial water gas shift catalyst bodies. By analyzing a phase of carbon present on their surface we show that the method provides measurements that are at the same time reliable, accurate and precise.

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Section: Figurementioning

confidence: 99%

Accurate 3D Characterization of Catalytic Bodies Surface by Scanning Electron Microscopy

et al. 2019

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“…, ; Tafti et al. , ). Eulitz & Reiss () describe a broadly similar approach to that utilized in this study, but their approach used manual control of the SEM and utilized just 40 images for their reconstruction of a single model of a rabbit glomerulus.…”

Section: Introductionmentioning

confidence: 99%

“…However, SfM 3D photogrammetry reconstruction techniques applied to SEM datasets have previously relied upon complex workflows and custom-written code and demonstrated only limited ability to recreate complex 3D structures (e.g. Cornille et al, 2003;Tafti et al, 2015). Eulitz & Reiss (2015) describe a broadly similar approach to that utilized in this study, but their approach used manual control of the SEM and utilized just 40 images for their reconstruction of a single model of a rabbit glomerulus.…”

Section: Introductionmentioning

confidence: 99%

SEM‐microphotogrammetry, a new take on an old method for generating high‐resolution 3D models from SEM images

Ball

Job

Walker

2017

Journal of Microscopy

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The method we present here uses a scanning electron microscope programmed via macros to automatically capture dozens of images at suitable angles to generate accurate, detailed three-dimensional (3D) surface models with micron-scale resolution. We demonstrate that it is possible to use these Scanning Electron Microscope (SEM) images in conjunction with commercially available software originally developed for photogrammetry reconstructions from Digital Single Lens Reflex (DSLR) cameras and to reconstruct 3D models of the specimen. These 3D models can then be exported as polygon meshes and eventually 3D printed. This technique offers the potential to obtain data suitable to reconstruct very tiny features (e.g. diatoms, butterfly scales and mineral fabrics) at nanometre resolution. Ultimately, we foresee this as being a useful tool for better understanding spatial relationships at very high resolution. However, our motivation is also to use it to produce 3D models to be used in public outreach events and exhibitions, especially for the blind or partially sighted.

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“…The vast literature of used techniques for the problem of surface reconstruction can be categorized into three major classes: a) single-view, b) multi-view, and c) hybrid strategies [15]. In single-view approaches, using varying lighting (electron beam) directions on a single perspective, a group of 2D SEM micrographs are captured and utilized for 3D SEM surface modeling.…”

Section: Introductionmentioning

confidence: 99%

“…Zolotukhin et al [31] studied the pros and cons of SfM algorithm focusing on two-view 3D SEM surface reconstruction problem. Tafti et al [15] reviewed the state-of-the-art 3D SEM surface reconstruction solutions, addressing several enhancements for the research study, and developed a sparse multi-view algorithm to tackle 3D SEM surface modeling problem. Using machine learning solutions and adaptive strategies, Tafti et al [32] proposed an improved sparse feature-based multi-view method which outperforms their earlier work in terms of accuracy and computation demands.…”

Section: Introductionmentioning

confidence: 99%

Three-dimensional reconstruction of highly complex microscopic samples using scanning electron microscopy and optical flow estimation

et al. 2017

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Scanning Electron Microscope (SEM) as one of the major research and industrial equipment for imaging of micro-scale samples and surfaces has gained extensive attention from its emerge. However, the acquired micrographs still remain two-dimensional (2D). In the current work a novel and highly accurate approach is proposed to recover the hidden third-dimension by use of multi-view image acquisition of the microscopic samples combined with pre/post-processing steps including sparse feature-based stereo rectification, nonlocal-based optical flow estimation for dense matching and finally depth estimation. Employing the proposed approach, three-dimensional (3D) reconstructions of highly complex microscopic samples were achieved to facilitate the interpretation of topology and geometry of surface/shape attributes of the samples. As a byproduct of the proposed approach, high-definition 3D printed models of the samples can be generated as a tangible means of physical understanding. Extensive comparisons with the state-of-the-art reveal the strength and superiority of the proposed method in uncovering the details of the highly complex microscopic samples.

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Recent advances in 3D SEM surface reconstruction

Cited by 83 publications

References 35 publications

Accurate 3D Characterization of Catalytic Bodies Surface by Scanning Electron Microscopy

Accurate 3D Characterization of Catalytic Bodies Surface by Scanning Electron Microscopy

SEM‐microphotogrammetry, a new take on an old method for generating high‐resolution 3D models from SEM images

Three-dimensional reconstruction of highly complex microscopic samples using scanning electron microscopy and optical flow estimation

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