An image processing method to automatically identify Avocado leaf state

Itamar F. Salazar-Reque, Adison G. Pacheco, Ricardo Y. Rodriguez, Jinmy G. Lezama, Samuel G. Huamán

Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

2 Citas (Scopus)

Resumen

Nowadays, avocado has strong demand around the world due to its nutritional properties and because it is all year supplied from different parts of the world, being Peru one of the main providers. However, nutrient deficiencies and plague attacks during cultivation stages represent a major difficulty for farmers since early identification of these states (i.e. deficiencies and plagues) is a time-consuming activity that requires trained evaluators to do so. In this paper, an automatic method for identification of avocado leaf state is proposed. This method uses k-means, in a s-v space at superpixel level, to segment leaf from uniform background from images captured in-field in semi-controlled conditions and a shallow neural network to classify composed histograms from segmented leaves into 4 states: Healthy, Fe deficiency, Mg deficiency and red spider plague. The proposed method separates leaf from background with an average F-score of 0.98 and classifies leaf condition with an overall accuracy of 96.8%.

Idioma originalInglés
Título de la publicación alojada2019 22nd Symposium on Image, Signal Processing and Artificial Vision, STSIVA 2019 - Conference Proceedings
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9781728114910
DOI
EstadoPublicada - abr 2019
Publicado de forma externa
Evento22nd Symposium on Image, Signal Processing and Artificial Vision, STSIVA 2019 - Bucaramanga, Colombia
Duración: 24 abr 201926 abr 2019

Serie de la publicación

Nombre2019 22nd Symposium on Image, Signal Processing and Artificial Vision, STSIVA 2019 - Conference Proceedings

Conferencia

Conferencia22nd Symposium on Image, Signal Processing and Artificial Vision, STSIVA 2019
País/TerritorioColombia
CiudadBucaramanga
Período24/04/1926/04/19

Nota bibliográfica

Publisher Copyright:
© 2019 IEEE.

Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.

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