Identifying multiple plant diseases using digital image processing

Autor(es)

Barbedo, Jayme Garcia Arnal ^[1] ; Koenigkan, Luciano Vieira ^[1] ; Santos, Thiago Teixeira ^[1]

Afiliação do(s) autor(es)

^[1] Embrapa Agr Informat, Campinas, SP - Brazil

• Tipo de documento: Artigo Científico
• Fonte: BIOSYSTEMS ENGINEERING; v. 147, p. 104-116, JUL 2016.
• Citações Web of Science: 16

Resumo

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)

• Processo FAPESP: 13/06884-8 - Diagnóstico automático de doenças em plantas usando imagens digitais
• Beneficiário: Jayme Garcia Arnal Barbedo
• Modalidade de apoio: Auxílio à Pesquisa - Regular