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Machine Vision Systems in Precision Agriculture for Crop Farming

Human-Machines Interaction Laboratory (HUMAIN-Lab), Department of Computer Science, International Hellenic University (IHU), 57001 Thermi, Greece
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Received: 15 October 2019 / Revised: 4 December 2019 / Accepted: 6 December 2019 / Published: 7 December 2019
Machine vision for precision agriculture has attracted considerable research interest in recent years. The aim of this paper is to review the most recent work in the application of machine vision to agriculture, mainly for crop farming. This study can serve as a research guide for the researcher and practitioner alike in applying cognitive technology to agriculture. Studies of different agricultural activities that support crop harvesting are reviewed, such as fruit grading, fruit counting, and yield estimation. Moreover, plant health monitoring approaches are addressed, including weed, insect, and disease detection. Finally, recent research efforts considering vehicle guidance systems and agricultural harvesting robots are also reviewed. View Full-Text
Keywords: machine vision; precision agriculture; agrobots; intelligent systems; industry 4.0 machine vision; precision agriculture; agrobots; intelligent systems; industry 4.0
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MDPI and ACS Style

Mavridou, E.; Vrochidou, E.; Papakostas, G.A.; Pachidis, T.; Kaburlasos, V.G. Machine Vision Systems in Precision Agriculture for Crop Farming. J. Imaging 2019, 5, 89. https://0-doi-org.brum.beds.ac.uk/10.3390/jimaging5120089

AMA Style

Mavridou E, Vrochidou E, Papakostas GA, Pachidis T, Kaburlasos VG. Machine Vision Systems in Precision Agriculture for Crop Farming. Journal of Imaging. 2019; 5(12):89. https://0-doi-org.brum.beds.ac.uk/10.3390/jimaging5120089

Chicago/Turabian Style

Mavridou, Efthimia; Vrochidou, Eleni; Papakostas, George A.; Pachidis, Theodore; Kaburlasos, Vassilis G. 2019. "Machine Vision Systems in Precision Agriculture for Crop Farming" J. Imaging 5, no. 12: 89. https://0-doi-org.brum.beds.ac.uk/10.3390/jimaging5120089

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