Measuring Agricultural Area Using YOLO Object Detection and ArUco Markers

This paper discusses the use of drones in image acquisition of agricultural land to detect the presence of disease and calculate the area of infected agriculture. Calculation of the area of infected and healthy areas will be calculated by combining the You Only Look Once (Yolo) object detection algo...

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Veröffentlicht in:Ingénierie des systèmes d'Information 2024-02, Vol.29 (1), p.95-106
Hauptverfasser: Masykur, Fauzan, Adi, Kusworo, Nurhayati, Oky Dwi
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Sprache:eng
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Zusammenfassung:This paper discusses the use of drones in image acquisition of agricultural land to detect the presence of disease and calculate the area of infected agriculture. Calculation of the area of infected and healthy areas will be calculated by combining the You Only Look Once (Yolo) object detection algorithm version 4 with the ArUco Marker reference image. The image resulting from the detection from the Yolo v4 algorithm will be used as a reference to be referenced using a reference image in the form of an AruCo Marker to convert it to area units to determine the area of the infected area and calculate the ratio between the area of the infected area and the area of the healthy area. The coordinate points at each corner are used as the first stage in converting pixels into area units. Measuring the infected area is necessary to localize the infection so that it does not spread to healthy plant areas. Apart from that, to anticipate the spread of infection which could result in crop failure. Evaluation of the calculation of the area of the detection area with the actual area resulted in an accuracy of 97.05%.
ISSN:1633-1311
2116-7125
DOI:10.18280/isi.290111