Grading of persimmon fruits into three commercially maturity stages was conducted by image analysis
technique. An automatic algorithm was developed to classify the fruits based on the external color
of them. Physical, mechanical and nutritional properties of fruits were determined to compare the
results of image analysis and visual classification. During the process of image segmentation, the black
spots on persimmon fruits were removed to dilute the effect of them on the features to be extracted
and used for classification. Among the features, there were significant differences between maturity
stages for mean values of R, G, b*, gray scale and S channels. Two classifiers based on linear (LDA) and
quadratic discriminant analysis (QDA) were used to assess the applicability of vision system. The results
showed that QDA classifier could be valuable in categorizing the fruits with better overall accuracy rate
of 90.24%.
maturity stages