Identification of Foliar Diseases in Cotton Crop

• Author(s): A. A. Bernardes ; J. G. Rogeri ; N. Marranghello ; A. S. Pereira ; A. F. Araujo ; João Manuel R. S. Tavares
• Date: 2011
• Persistent ID: http://hdl.handle.net/10216/56784
• Origin: Repositório Aberto da Universidade do Porto
• Subject(s): Ciências tecnológicas; Tecnologia; Tecnologia de computadores; Processamento de imagem
• Document Type: Conference Object
• Language: English

Description

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.