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Multispectral Fluorescence Imaging for the Identification of Food Products
Author(s) -
Novales Bruno,
Bertrand Dominique,
Devaux MarieFrançoise,
Robert Paul,
Sire Alain
Publication year - 1996
Publication title -
journal of the science of food and agriculture
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.782
H-Index - 142
eISSN - 1097-0010
pISSN - 0022-5142
DOI - 10.1002/(sici)1097-0010(199607)71:3<376::aid-jsfa585>3.0.co;2-5
Subject(s) - multispectral image , identification (biology) , fluorescence , artificial intelligence , linear discriminant analysis , food products , pixel , soya bean , remote sensing , sample (material) , pattern recognition (psychology) , fluorescence lifetime imaging microscopy , computer vision , computer science , food science , optics , geography , chemistry , botany , chromatography , biology , physics
A multispectral fluorescence imaging system was tested to identify four food products (maize, pea, soya bean and wheat). The system made it possible to record 12 images for each sample by a combination of various excitation and emission filters. Direct observation of images showed that the fluorescence of the four food products made identification possible, although more than one image was necessary to obtain satisfactory discrimination. The images were linearly combined and the most relevant images for identification were determined using a stepwise discriminant analysis and a mapping of the four food products was obtained. In the segmented images, the percentage of well‐classified pixels was up to 98·8% for the four products.