Leaf Disease Detection using Support Vector Machine

Abstract

Agriculture is the most important sector in Indian economy. India occupies the second highest rank in farm outputs in the world. Its contribution to the development of Indian economy has immense potential. So agriculture products may play vital role for economic growth. But the different kind of diseases in plant decreases the production of crops and growth rate of farmers. To identify and monitor the leaf diseases manually by farmers is very difficult. This is one of the reasons to develop an automatic leaf diseases detection model. The proposed model helps in automatic detection of different plant diseases at early stages. Thus, the production will increase in many folds. The main aim of this study is to identify different types of leaf diseases. Different feature extraction techniques have been used to enhance the classification accuracy. Support Vector Machine (SVM), Random Forest and Logistic Regression have been applied to classify different types of leaf diseases. When obtained results are compared SVM outperforms other two classifiers. Results show that, the model can be used in real life applications.