A Color and Texture Based Approach for the Detection and Classification of Plant Leaf Disease Using KNN Classifier

Modern organic farming is gaining popularity in the agriculture of many developing countries. There are many problems arise in farming due to various environmental factors and among these plant leaf disease is considered to be the most strong factor that causes the deficit of agricultural product quality. The goal is to mitigate this issue through computer vision and machine learning technique. This paper proposed a technique for plant leaf disease detection and classification using K-nearest neighbor (KNN) classifier. The texture features are extracted from the leaf disease images for the classification. In this work, KNN classifier will classify the diseases like alternaria alternata, anthracnose, bacterial blight, leaf spot, and canker of various plant species. The proposed approach can successfully detect and recognize the selected diseases with 96.76 % accuracy.