Data/hora: 09/06/2024 07:11:54

Biblioteca(s): | Embrapa Agricultura Digital.
Data corrente: | 12/11/2014
Data da última atualização: | 08/01/2020
Autoria: | BARBEDO, J. G. A.
Afiliação: | JAYME GARCIA ARNAL BARBEDO, CNPTIA.
Título: | An automatic method to detect and measure leaf disease symptoms using digital image processing.
Ano de publicação: | 2014
Fonte/Imprenta: | Plant Disease, Saint Paul, v. 98, n. 12, 1709-1716, Dec. 2014.
DOI: | http://dx.doi.org/10.10 94/PDIS-03-14-0290-RE
Idioma: | Inglês
Conteúdo: | A method is presented to detect and quantify leaf symptoms using conventional color digital images. The method was designed to be completely automatic, eliminating the possibility of human error and reducing time taken to measure disease severity. The program is capable of dealing with images containing multiple leaves, further reducing the time taken. Accurate results are possible when the symptoms and leaf veins have similar color and shade characteristics. The algorithm is subject to one constraint: the background must be as close to white or black as possible. Tests showed that the method provided accurate estimates over a wide variety of conditions, being robust to variation in size, shape, and color of leaves; symptoms; and leaf veins. Low rates of false positives and false negatives occurred due to extrinsic factors such as issues with image capture and the use of extreme file compression ratios.
Palavras-Chave: | Imagem digital; Processamento de imagens.
Thesagro: | Doença de planta.
Thesaurus Nal: | Digital images; Image analysis; Plant diseases and disorders.
Categoria do assunto: | X Pesquisa, Tecnologia e Engenharia
Registro original: | Embrapa Agricultura Digital (CNPTIA)
Exemplares: | CNPTIA - (18036-1) - UPC - AP - DD -  -  -  - DIS