Detection and Recognition of Papaya Leaf Diseases Using Image Processing

Abstract

Horticulture has been defined as the agriculture of plants mainly for food materials.  It includes plant conservation, landscape restoration, soil management and maintenance. In this paper we are going to detect the diseases which occurs in papaya leaf because papaya is a fruit which is rich in vitamins, amino acids, carbohydrates and minerals which strengthens the bones, prevents muscle cramping and increases the energy. Papaya is gaining importance nowadays which plays an important role in horticulture because of its medicinal properties and for its rich nutrients. It has found farmers are facing many issues regarding diseases which are affecting the papaya plant so we have planned to introduce computer vision techniques which will automatically detect the infected plant in order to increase the yield and quality of the fruit. We propose a system which captures the plant and processes it using gradient anisotropic diffusion and extracts the features using GLCM from the leaf, stem and fruits and finally it classifies using extreme learning machine which recognize the disease affected in the plant..