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Individual Detection of Olive Trees Under Different Olive Planting Distributions

Authors:
Pablo Latorre Hortelano
Francisco García del Castillo
David Jurado Rodríguez
Lidia Ortega Alvarado
Juan Manuel Jurado Rodríguez

Keywords: computer vision; plantation distribution; individual segmentation; point clouds.

Abstract:
This work in progress addresses the challenge of individual detection of olive trees in different planting frames using advanced computer vision techniques and environmental analysis using point clouds. Accurate identification of individual trees is essential for efficient olive orchard management, especially in planting systems that vary in density, geometric layout and spacing between trees, aspects that strongly affect the way the field should be worked afterwards. Through the combination of image processing algorithms and geometric models, this study aims to develop a robust system that automates the identification of each tree, improving the monitoring of the crop and allowing for more accurate decision-making on the future treatment of each segmented entity in terms of health, maintenance, pruning. Preliminary results show the potential of these tools to optimize olive grove management in different planting configurations.

Pages: 27 to 31

Copyright: Copyright (c) IARIA, 2025

Publication date: May 18, 2025

Published in: conference

ISSN: 2308-393X

ISBN: 978-1-68558-269-2

Location: Nice, France

Dates: from May 18, 2025 to May 22, 2025