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Wavelet based feature extraction in near infrared spectra for compositional analysis of food

: Krause, J.

Fulltext urn:nbn:de:0011-n-5069084 (1.2 MByte PDF)
MD5 Fingerprint: 9f7f6dece69ac97d4ef213e512a481d4
Created on: 29.8.2018

Beyerer, Jürgen (Ed.); Pak, Alexey (Ed.); Taphanel, Miro (Ed.):
Joint Workshop of Fraunhofer IOSB and Institute for Anthropomatics, Vision and Fusion Laboratory 2017. Proceedings : July 30 - August 5, 2017, Triberg-Nussbach, Germany
Karlsruhe: KIT Scientific Publishing, 2018 (Karlsruher Schriften zur Anthropomatik 34)
ISBN: 978-3-7315-0779-6
ISBN: 3-7315-0779-X
DOI: 10.5445/KSP/1000081314
Fraunhofer Institute of Optronics, System Technologies and Image Exploitation and Institute for Anthropomatics, Vision and Fusion Laboratory (Joint Workshop) <2017, Triberg-Nussbach>
Conference Paper, Electronic Publication
Fraunhofer IOSB ()

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.