LED spectral imaging with food and agricultural applications

Jens Michael Carstensen

doi:10.1117/12.2304698

14 May 2018 LED spectral imaging with food and agricultural applications

Jens Michael Carstensen

Proceedings Volume 10656, Image Sensing Technologies: Materials, Devices, Systems, and Applications V; 1065604 (2018) https://doi.org/10.1117/12.2304698
Event: SPIE Commercial + Scientific Sensing and Imaging, 2018, Orlando, FL, United States

Abstract

Strobed LED spectral imaging systems share some principles with illumination filter wheel systems. The major advantages of strobed LED systems are: 1) speed, 2) no mechanical movement, 3) no dependency on unstable broadspectrum incandescent light source, 4) potential for high dynamic range imaging through the illumination, and 5) combined spectral reflectance imaging and spectral fluorescence imaging. All of the above advantages are exploited in the proposed system where the spectral illumination source is combined with an integrating sphere and a calibration model that provides traceability, high reproducibility, spatial homogeneity, and focus on chemical properties of a heterogenous sample. Application areas of such systems are quite broad and high performance systems are seen within fields like agriculture, food, pharmaceuticals, medical devices, cosmetics, forensics, cultural heritage, and general manufacturing. We will present the elements of our strobed LED imaging systems and highlight how such systems can be advantageous to other spectral imaging techniques like pushbroom imaging. The powerful multivariate analysis technique, normalized canonical discriminant analysis (nCDA) is used to optimize the application performance as well as to get information about the data/noise structure and importance of specific spectral ranges. The performance is illustrated on a number of real applications from industries within the above mentioned fields. Applications on agricultural seed analysis, coating analysis, food contamination, and counterfeit detection will be shown.

Citation Download Citation

Jens Michael Carstensen "LED spectral imaging with food and agricultural applications", Proc. SPIE 10656, Image Sensing Technologies: Materials, Devices, Systems, and Applications V, 1065604 (14 May 2018); https://doi.org/10.1117/12.2304698

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