Crop Plant Disease Detection Using Image Processing

Abstract

Our country depends greatly on the crop for its economy and to meet food needs. It is important to detect any disease in time to ensure healthy and proper growth of crop plants and before applying necessary treatment on the affected plants. Since the manual identification of the disease is much time and labor costs, so it is inevitably wise to take automatic system. The automatic method requires a towering lot of work, Plant diseases require efficiency and excessive processing time. In this project, the disease detection systems of rice leaves and various other plants and fruits presented using image processing. Most crop and fruit tree diseases such as Cercospora, leaf smut, bacterial blight, and Leaf Spot diseases are identified in this work. Hence, Steps such as detect the disease are involves image collection, image noise, and object removal prepared for pre-processing techniques, Using K-means clustering for segmentation and RGB to HIS, Color co-occurrence Strategy for Feature extraction then classified by utilizing SVM. This paper outlines the methods used to detect diseases in plant by identifying pictures of their leaves.