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  4. Wavelet based feature extraction in near infrared spectra for compositional analysis of food
 
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2018
  • Konferenzbeitrag

Titel

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

Abstract
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.
Author(s)
Krause, J.
Hauptwerk
Joint Workshop of Fraunhofer IOSB and Institute for Anthropomatics, Vision and Fusion Laboratory 2017. Proceedings
Konferenz
Fraunhofer Institute of Optronics, System Technologies and Image Exploitation and Institute for Anthropomatics, Vision and Fusion Laboratory (Joint Workshop) 2017
File(s)
N-506908.pdf (1.2 MB)
Language
Englisch
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