Olive Fruits Recognition Using Neural Networks
Author(s) -
Gabriel Gatica,
Stanley Best,
José Ceroni,
Gastón Lefranc
Publication year - 2013
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2013.05.053
Subject(s) - computer science , olive trees , rgb color model , artificial neural network , artificial intelligence , pattern recognition (psychology) , moment (physics) , deep neural networks , horticulture , biology , physics , classical mechanics
A new method for olive fruit recognition is presented. Olive fruits size and weight are used for estimating the best harvesting moment of olive trees. Olive fruit recognition is performed by analyzing RGB images taken from olive trees. The harvesting decision comprehends two stages, the first stage focused on deciding whether or not the candidate identified in the picture corresponds to an olive fruit, and the second stage focused on olives overlapping in the pictures. The analyses required in these two stages are performed by implementing a neural networks solution approach
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