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Proceedings Paper

Inline hyperspectral thickness determination of thin films using neural networks
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Paper Abstract

Combining reflectometry and hyperspectral imaging allows mapping of thin film thickness. Therefore, layer thickness is calculated by comparing a dataset of simulated spectra with the measured data. Utilizing the maximum frame rate of the hyperspectral imager, the pixel wise spectra comparing procedure cannot be performed using a standard computer due to the processing load. In this work, a method using neural networks for calculating layer thickness is presented. By the use of the nonlinear equation as result of a trained neural network, thickness data can be determined with a measurement rate matching the maximum frame rate of the hyperspectral imager.

Paper Details

Date Published: 28 April 2017
PDF: 7 pages
Proc. SPIE 10213, Hyperspectral Imaging Sensors: Innovative Applications and Sensor Standards 2017, 102130G (28 April 2017); doi: 10.1117/12.2262070
Show Author Affiliations
Anton J. Tremmel, Technische Univ. München (Germany)
Roman Weiss, Technische Univ. München (Germany)
Michael Schardt, Technische Univ. München (Germany)
Alexander W. Koch, Technische Univ. München (Germany)


Published in SPIE Proceedings Vol. 10213:
Hyperspectral Imaging Sensors: Innovative Applications and Sensor Standards 2017
David P. Bannon, Editor(s)

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