Image Processing System for Detecting and Recovering from Cotton Leaf Disease using The Android Application

Abstract

A plant is the heart of an agricultural field and it improves source of energy as well as financial income. We discuss several types of leaf diseases in the plants and their identification process, symptoms of disease and remedy measures are explained. There is a huge source of plants, but due to the effect of environmental condition or as weather, climate change, many non-native diseases occur on plants and cause social, ecological and financial losses. Many of the farmers are unable to recognize new disease. So the farmer needs an expert person who recognizes the disease and symptoms appearing on the plants, this will increase the cost of farming. To reduce farming, we introduce Android Application which diagnosis and identify the type of disease and symptoms of disease on plant leaves. The Android application performs basic operations like color transformation, thresholding and edge detection. Our system work on such plant leaves which are affected by many diseases that is a virus, fungi, excess of nutrients and insects, etc.We use image processing to detect and classify these diseases. Implement image processing operation on an android mobile device. It identifies the actual type of disease and its symptoms. Finally, using SVM-GA classifier to diagnosis the cotton leaf disease. Using Android Application type of disease, symptoms, remedy measures and recovery suggestions are given at a very less time and low cost.