Machine vision for color inspection of potatoes and apples

Y. Tao, P. H. Heinemann, Z. Varghese, C. T. Morrow, H. J. Sommer

Research output: Contribution to journalArticlepeer-review

181 Scopus citations


A machine vision system was trained to distinguish between good and greened potatoes and yellow and green `Golden Delicious' apples. The method of using the HSI (Hue, Saturation, and Intensity) color system proved highly effective for color evaluation and image processing. The vision system achieved over 90% accuracy in inspection of potatoes and apples by representing features with hue histograms and applying multivariate discriminant techniques. Reducing the number of hue bins by selecting significant features only or by summing groups of hue bins increased misclassification by the vision system. Color classification represents an important quality feature evaluation method that needs to be integrated into an overall automated quality inspection and grading system.

Original languageEnglish (US)
Pages (from-to)1555-1561
Number of pages7
JournalTransactions of the American Society of Agricultural Engineers
Issue number5
StatePublished - Sep 1995

All Science Journal Classification (ASJC) codes

  • Agricultural and Biological Sciences (miscellaneous)


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