Tomato sorting using independent component analysis on spectral images

G. Polder, G.W.A.M. van der Heijden, I.T. Young

    Research output: Contribution to journalArticleAcademicpeer-review

    49 Citations (Scopus)

    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
    Original languageEnglish
    Pages (from-to)253-259
    JournalReal-Time Imaging
    Volume9
    Issue number4
    DOIs
    Publication statusPublished - 2003

    Keywords

    • algorithms
    • lycopene
    • products

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