GFkuts: A novel multispectral image segmentation method applied to precision agriculture

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4 Citas (Scopus)

Resumen

Image segmentation enables the precise extraction of several crop traits from multispectral aerial imagery. This paper presents a novel segmentation technique called GFKuts. The method integrates a graph-based optimization algorithm with a k-means Monte Carlo approach. Here, we evaluate the performance of the proposed method against other approaches for image segmentation found in the specialized literature. Results report an improvement on the F1-score accuracy in terms of crop canopy segmentation. These findings are promising for the precise calculation of vegetative indices and other crop trait features.

Idioma originalInglés
Título de la publicación alojada2020 Virtual Symposium in Plant Omics Sciences, OMICAS 2020 - Conference Proceedings
EditoresJulian Colorado
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9781665433310
DOI
EstadoPublicada - 23 nov. 2020
Evento2020 Virtual Symposium in Plant Omics Sciences, OMICAS 2020 - Virtual, Online, Colombia
Duración: 23 nov. 202027 nov. 2020

Serie de la publicación

Nombre2020 Virtual Symposium in Plant Omics Sciences, OMICAS 2020 - Conference Proceedings

Conferencia

Conferencia2020 Virtual Symposium in Plant Omics Sciences, OMICAS 2020
País/TerritorioColombia
CiudadVirtual, Online
Período23/11/2027/11/20

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