深層学習を用いた柿の成熟度推定に関する検討

抄録

This paper describes a method for estimating the ripeness of persimmons from images. When a human visually judges the CC value, which is a numerical value indicating the degree of ripeness shown on a color chart for fruit, the judged value is not always the same for everyone, and there is a problem that it is not quantitative. We propose a method for measuring persimmon fruit peel color using a spectrophotometer and calculating the CC value. We also propose an image processing method that takes into account the characteristics of fruit peel color variation as a data augmentation method for training deep learning models. In the second half of the paper, we show the possibility of investigating the relationship between color and ripeness through experiments in which a wider range of CC values than those in the data set are trained. The follow-up study of CC values for each fruit also indicated the possibility of approximately predicting the optimal harvest time for each fruit.