Classification of macaw palm fruits from colorimetric properties for determining the harvest moment
sexta-feira, outubro 05, 2018
Luis M. Navas Gracia
ABSTRACT
The aim of this study was to use the colorimetric properties of the macaw palm fruits to develop a neural network classifier to determine the ideal moment for harvesting, based on the oil content of the fruit mesocarp.
During nine weeks of maturation were sampled 900 fruits of macaw palm fruits and the colorimetric properties of the RGB, HSI and CIELab color models were used to classify the fruits into immature and mature fruits. Kappa index and the overall accuracy values were used to access the classifier performance. The classifiers based on RGB parameters and on hue were considered equivalents having a Kappa index of 0.901 and 0.942, respectively, indicating the 59th week of maturation as the ideal time to harvest with the highest oil content.
KEYWORDS digital images; maturation; neural networks; oil content
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