Identification of foliar diseases in cotton crop
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Data
2012-01-01
Autores
Bernardes, A. A. [UNESP]
Rogeri, J. G. [UNESP]
Marranghello, N. [UNESP]
Pereira, A. S. [UNESP]
Araujo, A. F.
Tavares, Joao Manuel R. S.
Tavares, JMRS
Jorge, RMN
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Crc Press-taylor & Francis Group
Resumo
The pathogens manifestation in plantations are the largest cause of damage in several cultivars, which may cause increase of prices and loss of crop quality. This paper presents a method for automatic classification of cotton diseases through feature extraction of leaf symptoms from digital images. Wavelet transform energy has been used for feature extraction while Support Vector Machine has been used for classification. Five situations have been diagnosed, namely: Healthy crop, Ramularia disease, Bacterial Blight, Ascochyta Blight, and unspecified disease.
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Computational Vision And Medical Image Processing: Vipimage 2011. Boca Raton: Crc Press-taylor & Francis Group, p. 193-197, 2012.