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Computer vision for agricultural monitoring and food quality inspection
Excellence is aimed at accomplishing the highest quality standards by ensuring minimum sizes, suitable colourings, no external damage, optimal organoleptic properties and absence of contamination, allowing our producers compete in the most demanding markets. We work developing fast inspection systems for in-line quality of the product or detecting invisible information using modern hyperspectral cameras.Postharvest inspection
Precision agriculture and robotics
Our research is focused on emergent technologies for precision agriculture such as robotics, satellite-based positioning systems, control architectures, novel field-oriented sensors, information technology, and precision farming to off-road vehicles. We also develop computer vision systems for inspecting the fruit in the field during growing or harvesting using autonomous optimised equipment to work in field conditions.
Field monitoring
Advanced systems for monitoring the vegetative status and yield prediction, ensuring the quality of the agricultural product from the early stages of production and allowing early decisions affecting the crop management or facilitating the delivery of the products to the appropriate markets by pre-sorting them in the field, thus reducing economic and environmental costs associated with their production, processing and handling.
We are a multidisciplinary and active research group on computers and optics applied to agriculture and food inspection, with large experience in the development of artificial vision systems, including spectroscopy, standard and multispectral computer vision, in-line inspection, remote monitoring, or robotics in agriculture, as well as software development for different platforms.
Recent Projects
INIA CITRUSREC, 2015 – 2018
Aplicación de nuevas tecnologías para una estrategia integral de la recolección mecanizada de
UE H2020 XF-ACTORS, 2016 – 2020
Xylella Fastidiosa Active Containment Through a multidisciplinary-Oriented Research Strategy (XFACTORS). H2020-SFS-2016-3, Project number
UE H2020 POnTE, 2015 – 2019
Pest Organisms Threatening Europe (POnTE). H2020-SFS-2014-2, Project number 635646