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Wavelet Based Feature Extraction in Near Infrared Spectra for Compositional Analysis of Food

Krause, Julius

Abstract (englisch):

Near infrared spectroscopy is a common method for analysis of food, soil and pharmaceutical products. New developments in sensor technology, like hyperspectral camera systems and mobile spectrometers, allow broad applications of spectroscopy with devices out of specialized laboratories. Therefore, it is necessary to develop robust algorithms for classification and regression, regardless of the device. The key to robust analysis lies in data preparation to get standardized spectral information from each device. Wavelet based feature extraction could be a possible method to compress spectral data to its material specific absorption information. A method for wavelet based feature extraction, which also reduces the influence from elastic scattering effects is proposed in this report.

Verlagsausgabe §
DOI: 10.5445/IR/1000085975
Veröffentlicht am 28.09.2018
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Anthropomatik und Robotik (IAR)
Publikationstyp Proceedingsbeitrag
Publikationsjahr 2018
Sprache Englisch
Identifikator ISBN: 978-3-7315-0779-6
ISSN: 1863-6489
KITopen-ID: 1000085975
Erschienen in Proceedings of the 2017 Joint Workshop of Fraunhofer IOSB and Institute for Anthropomatics, Vision and Fusion Laboratory. Ed.: J. Beyerer
Verlag KIT Scientific Publishing
Seiten 15-29
Serie Karlsruher Schriften zur Anthropomatik / Lehrstuhl für Interaktive Echtzeitsysteme, Karlsruher Institut für Technologie ; Fraunhofer-Inst. für Optronik, Systemtechnik und Bildauswertung IOSB Karlsruhe ; 34
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