Vision-based canopy area measurements

• Main Authors: Calangian, Xychryz A. Ron P., Gonzales, Justin Yollo C., Hilario, Crizel Aile N., Lopez, John Marcius M., Rulona, Boyd Lemuel E. E., Valencia, Immanuel Jose C., Billones, Robert Kerwin, Loresco, Pocholo James M., Valenzuela, Ira C., Dadios, Elmer Jose P.
• Format: text
• Published: Animo Repository 2019
• Subjects: Plant canopies—Measurement > Automation; Image processing; Computer vision; Manufacturing
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/2454; https://animorepository.dlsu.edu.ph/context/faculty_research/article/3453/type/native/viewcontent
• Institution: De La Salle University

Canopy area measurement is one of the important crop growth factors that is considered for the crop yield. This has been widely used parameter all over the world. Yet, the development of a system that can automatically computes the canopy area of the crop is still a challenge. In this study, a vision-based system is proposed. The system captures the image of the crop and process this through image processing algorithm. The extracted feature of the image is the pixel count. This pixel count determines the canopy area of the crop. A mathematical model was developed for the approximation of the canopy area. © 2018 IEEE.