Trabalho apresentado em evento
Identification of foliar diseases in cotton crop
Fecha
2012-02-13Registro en:
Computational Vision and Medical Image Processing, Proceedings of VipIMAGE 2011 - 3rd ECCOMAS Thematic Conference on Computational Vision and Medical Image Processing, p. 193-197.
10.1007/978-94-007-0726-9_4
2-s2.0-84856703865
2098623262892719
9667295076549924
0000-0003-1086-3312
Autor
Universidade Estadual Paulista (Unesp)
Institute of Mechanical Engineering and Industrial Management (INEGI)
Resumen
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. © 2012 Taylor & Francis Group.