Mr. Stefan Töberg Profile

Stefan Töberg

at Leibniz Univ Hannover

SPIE Involvement:

Author

Publications (2)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 31 January 2020 Paper

Dense structure and motion recovery from scanning electron microscope image sequences based on factorization

Stefan Töberg, Eduard Reithmeier

Proceedings Volume 11433, 1143333 (2020) https://doi.org/10.1117/12.2556372

Read Abstract +

Scanning electron microscopes (SEM) are widely used to analyse the morphology of all kind of specimen providing high resolution image data. To overcome the two-dimensional limitation, a lot of effort has been put into the recovery of the hidden third dimension based on the acquired SEM images throughout the last decades. Especially methods based on photogrammetry were identified to yield qualitatively good reconstruction results. Nevertheless, precise quantitative 3D measurements still remain a challenge. One of the key problems is the robust estimation of the motion in the acquired image sequences. A possible solution is given by the factorization method for orthographic image streams. To evaluate the applicability of this algorithm on SEM image sequences, the motion for several sequences is estimated and compared to the stage settings. Furthermore, the method is extended to obtain a dense reconstruction from a stereo-pair based on the estimated rotations between the two views. The final reconstruction results are compared to reference measurements with a confocal laser scanning microscope for a quantitative evaluation.

Proceedings Article | 6 November 2018 Paper

3D reconstruction of particle agglomerates using multiple scanning electron microscope stereo-pair images

Stefan Töberg, Eduard Reithmeier

Proceedings Volume 10819, 108190I (2018) https://doi.org/10.1117/12.2502485

KEYWORDS: Scanning electron microscopy, 3D image processing, Clouds, Particles, 3D modeling, Reconstruction algorithms, 3D image reconstruction, Electron microscopes

Read Abstract +

Scanning electron microscopes (SEM) allow a detailed surface analysis of a wide variety of specimen. However, SEM image data does not provide depth information about a captured scene. This limitation can be overcome by recovering the hidden third dimension of the acquired SEM micrographs, for instance to fully characterize a particle agglomerate’s morphology. In this paper, we present a method that allows the three-dimensional (3D) reconstruction of investigated particle agglomerates using an uncalibrated stereo vision approach that is applied to multiple stereo-pair images. The reconstruction scheme starts with a feature detection and subsequent matching in each pair of stereo images. Based on these correspondences, a robust estimate of the epipolar geometry is determined. A following rectification allows a reduction of the dense correspondence problem to a one-dimensional search along conjugate epipolar lines. So the disparity maps can be obtained using a dense stereo matching algorithm. To remove outliers while preserving edges and individual structures, a disparity refinement is executed using suitable image filtering techniques. The investigated specimen’s qualitative depth’s information can be directly calculated from the determined disparity maps. In a final step the resulting point clouds are registered. State-of-the-art algorithms for 3D reconstruction of SEM micrographs mainly focus on structures whose image pairs contain hardly or even none-occluded areas. The acquisition of multiple stereo-pair images from different perspectives makes it possible to combine the obtained point clouds in order to overcome occurring occlusions. The presented approach thereby enables the 3D illustration of the investigated particle agglomerates.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years