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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Identifying multiple plant diseases using digital image processing

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Author(s):
Barbedo, Jayme Garcia Arnal [1] ; Koenigkan, Luciano Vieira [1] ; Santos, Thiago Teixeira [1]
Total Authors: 3
Affiliation:
[1] Embrapa Agr Informat, Campinas, SP - Brazil
Total Affiliations: 1
Document type: Journal article
Source: BIOSYSTEMS ENGINEERING; v. 147, p. 104-116, JUL 2016.
Web of Science Citations: 16
Abstract

The gap between the current capabilities of image-based methods for automatic plant disease identification and the real-world needs is still wide. Although advances have been made on the subject, most methods are still not robust enough to deal with a wide variety of diseases and plant species. This paper proposes a method for disease identification, based on colour transformations, colour histograms and a pairwise-based classification system. Its performance was tested using a large database containing images of symptoms belonging to 82 different biotic and abiotic stresses, affecting the leaves of 12 different plant species. The wide variety of images used in the tests made it possible to carry out an in-depth investigation about the main advantages and limitations of the proposed algorithm. A comparison with other algorithms is also presented, and some possible solutions for the main challenges that still prevent this kind of tool to be adopted in practice. (C) 2016 IAgrE. Published by Elsevier Ltd. All rights reserved. (AU)

FAPESP's process: 13/06884-8 - Automatic disease diagnosis in plants using digital images
Grantee:Jayme Garcia Arnal Barbedo
Support Opportunities: Regular Research Grants