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- W48109737 abstract "The phenolic ripeness of the grape is one of the most important parameters to determine the optimal time for harvest. A recent line of studies proposes visual seed inspection by a trained expert to determine Phenolic Maturity. In this paper a innovative method to estimate the Grape Phenolic Maturity based in digital images is presented. Three classes of seed are defined (immature, mature and overmature) by the expert (enologist) involved in the research. A robust method of segmentation was proposed. The classification of seeds according to their degree of maturity was performed by a Artificial Neural Network. Descriptor used by the Neural Networks corresponds to a histogram of the occurrence of colors in a color scale. The method as a whole proved to be simple and effective in the classification of seeds. Therefore, it is possible to visualize the implementation of the method in real conditions due the high performance obtained." @default.
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- W48109737 date "2014-01-01" @default.
- W48109737 modified "2023-09-23" @default.
- W48109737 title "A Method to estimate Grape Phenolic Maturity based on Color Features" @default.
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