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  4. Hyperspectral imaging - from laboratory to in-line food sorting
 
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2010
Conference Paper
Title

Hyperspectral imaging - from laboratory to in-line food sorting

Abstract
Perfect quality control of food becomes more and more a matter of course. Foreign materialslike pieces of rocks, insects, plastics, carton etc. have to be identified and sorted out. For many years, near-infrared spectroscopy has been a widely-used analytical offline method for quality inspection for small samples in the food and agriculture industry. Up to now, high-speed automatic sorting machines work usually on the basis of visual inspection, not near-infrared inspection. This article describes how an in-line food sorting system can be developed on the basis of hyperspectral imaging data. We focus on analyzing the vast amount of data to yield minimum band selection with optimal classification results required for an industrial sorter.
Author(s)
Gruna, R.
Vieth, K.-U.
Michelsburg, M.
Puente Leon, F.
Mainwork
2nd International Workshop on Image Analysis in Agriculture 2010. CD-ROM  
Conference
International Workshop on Image Analysis in Agriculture 2010  
DOI
10.24406/publica-fhg-368171
File(s)
Download (2.47 MB)
Rights
Under Copyright
Language
English
Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung IOSB  
Keyword(s)
  • near-infrared hyperspectral imaging

  • food sorting

  • quality inspection

  • feature selection

  • band selection

  • Germany

  • kcm

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