Groundnut Leaf Disease Detection and Classification by using Back Probagation Algorithm

Ramakrishnan M., YILDIZ E.

2015 International Conference on Communications and Signal Processing (ICCSP), Melmaruvathur, India, 2 - 04 April 2015, pp.964-968 identifier

  • Publication Type: Conference Paper / Full Text
  • City: Melmaruvathur
  • Country: India
  • Page Numbers: pp.964-968
  • Keywords: Cercospora, Color Co-occurrence matrix, Feature Extraction, BPN
  • Istanbul University Affiliated: Yes

Abstract

Many studies shows that quality of agricultural products may be reduced from many causes. One of the most important factors contributing to low yield is disease attack. The plant disease such as fungi, bacteria and viruses. The leaf disease completely destroys the quality of the leaf. Common ground nut disease is cercospora. It is one of the type of disease in early stage of ground nut leaf. The upgraded processing pattern comprises of four leading steps. Initially a color renovation constitute intended for the input RGB image is formed, This RGB is converted into HSV because RGB is for Color generation and color descriptor. The next step is plane separation. Next performed the color features. Then using back propagation algorithm detection of leaf disease is done.