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Surface topography characterization using 3D stereoscopic reconstruction of SEM images
Halmstad University, School of Business, Engineering and Science, The Rydberg Laboratory for Applied Sciences (RLAS).ORCID iD: 0000-0002-8364-202x
Halmstad University, School of Business, Engineering and Science, The Rydberg Laboratory for Applied Sciences (RLAS).ORCID iD: 0000-0002-2330-0597
Halmstad University, School of Business, Engineering and Science, The Rydberg Laboratory for Applied Sciences (RLAS).ORCID iD: 0000-0001-8058-1252
2018 (English)In: Surface Topography: Metrology and Properties, ISSN 2051-672X, Vol. 6, no 2, article id 024006Article in journal (Refereed) Published
Abstract [en]

A major drawback of the optical microscope is its limitation to resolve finer details. Many microscopes have been developed to overcome the limitations set by the diffraction of visible light. The scanning electron microscope (SEM) is one such alternative: it uses electrons for imaging, which have much smaller wavelength than photons. As a result high magnification with superior image resolution can be achieved. However, SEM generates 2D images which provide limited data for surface measurements and analysis. Often many research areas require the knowledge of 3D structures as they contribute to a comprehensive understanding of microstructure by allowing effective measurements and qualitative visualization of the samples under study. For this reason, stereo photogrammetry technique is employed to convert SEM images into 3D measurable data. This paper aims to utilize a stereoscopic reconstruction technique as a reliable method for characterization of surface topography. Reconstructed results from SEM images are compared with coherence scanning interferometer (CSI) results obtained by measuring a roughness reference standard sample. This paper presents a method to select the most robust/consistent surface texture parameters that are insensitive to the uncertainties involved in the reconstruction technique itself. Results from the two-stereoscopic reconstruction algorithms are also documented in this paper. © 2018 IOP Publishing Ltd.

Place, publisher, year, edition, pages
Bristol: Institute of Physics (IOP), 2018. Vol. 6, no 2, article id 024006
Keywords [en]
Image resolution, Interferometers, Light, Photogrammetry, Power spectral density, Scanning, Scanning electron microscopy, Spectral density, Stereo image processing, Surface measurement, Surface topography, Three dimensional computer graphics, High magnifications, Reconstruction algorithms, Reconstruction techniques, Reference standard samples, Scanning interferometers, Stereophotogrammetry, Surface texture parameters, The scanning electron microscopes (SEM), Image reconstruction
National Category
Medical Image Processing Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:hh:diva-38710DOI: 10.1088/2051-672X/aabde1ISI: 000432445700001Scopus ID: 2-s2.0-85051421851OAI: oai:DiVA.org:hh-38710DiVA, id: diva2:1276400
Available from: 2019-01-08 Created: 2019-01-08 Last updated: 2019-01-08Bibliographically approved

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Vedantha Krishna, AmoghFlys, OlenaReddy, Vijeth VenkataramRosén, Bengt Göran

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