Machine Vision for Color Inspection of Potatoes and Apples

Abstract

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.