Lemon Leaf Disease Detection and its Solution

Abstract

Citrus trees are very needful that the people consume the citrus fruits daily and are affected by various
diseases like Citrus canker, citrus black-spot and the citrus leaf-miner which are to be handled by the farmers within
some time to increase their production. Disease recognition on citrus leaves is a difficult work. Many diseases
commonly recognized on leaves of lemon tree. By taking the proper remedy for the disease, so that crop losses should
also reduces. This system is helpful for the owners of the crop to recognize the kind of the disease and helps them to
control within least amount of time. Our system recognizes the kind of disease as such as they occur on leaf of the
lemon tree. The main aim of this project is to detect the disease of the lemon leaves and providing appropriate solution
to that disease. Initially the images of the lemon leaves are captured through the high resolution digital camera for
good quality. Then the captured images are converted from RGB to gray scale level for enhancement. These converted
images are segmented by the method called K-Means cluster to extract the diseased part on the leave and the Multi
class SVM is used for classification. Therefore our proposed system increases the crop yield and improves the farming
economically.