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

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

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%.

Original languageEnglish
Title of host publication2019 22nd Symposium on Image, Signal Processing and Artificial Vision, STSIVA 2019 - Conference Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728114910
DOIs
StatePublished - Apr 2019
Externally publishedYes
Event22nd Symposium on Image, Signal Processing and Artificial Vision, STSIVA 2019 - Bucaramanga, Colombia
Duration: 24 Apr 201926 Apr 2019

Publication series

Name2019 22nd Symposium on Image, Signal Processing and Artificial Vision, STSIVA 2019 - Conference Proceedings

Conference

Conference22nd Symposium on Image, Signal Processing and Artificial Vision, STSIVA 2019
Country/TerritoryColombia
CityBucaramanga
Period24/04/1926/04/19

Bibliographical note

Funding Information:
ACKNOWLEDGMENT The authors would like to thank the National Innovation Program for Competitiveness and Productivity (Innóvate Perú) for the funds allocated to the project 119-INNOVATEPERU-IDIBIO-2018. We also would like to thank the associated institutions APPALMEX and CITE Agroindustrial Moquegua, specially to Erick Chacaltana Espino and Daphne Castro Arata for their valuable logistic help.

Publisher Copyright:
© 2019 IEEE.

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

Keywords

  • Artificial neural networks
  • Avocado
  • leaf diseases
  • superpixels

Fingerprint

Dive into the research topics of 'An image processing method to automatically identify Avocado leaf state'. Together they form a unique fingerprint.

Cite this