Tomato sorting using independent component analysis on spectral images

Authors:
G. Polder;G. W. A. M. van der Heijden;I. T. Young
Affiliations:
Wageningen UR, Biometris, PO-Box 100, 6700AC, Wageningen, The Netherlands and Pattern Recognition Group, Dept. of Imaging Science and Technology, Delft University of Technology, Lorentzweg 1, 2628 ...;Wageningen UR, Biometris, PO-Box 100, 6700AC, Wageningen, The Netherlands;Pattern Recognition Group, Dept. of Imaging Science and Technology, Delft University of Technology, Lorentzweg 1, 2628 CJ, Delft, The Netherlands
Venue:
Real-Time Imaging - Special issue on spectral imaging
Year:
2003

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Abstract

Independent Component Analysis is one of the most widely used methods for blind source separation. In this paper we use this technique to estimate the most important compounds which play a role in the ripening of tomatoes. Spectral images of tomatoes were analyzed. Two main independent components were found. These components resemble the actual absorption spectra of lycopene and chlorophyll. Concentration images of these compounds show increase of one compound and decrease of the other during ripening. The method can be implemented in an unsupervised real time sorting machine, using the total compound concentrations and the spatial distribution of the concentrations as criteria.