Plant Disease Detection Using Image Processing and Deep Learning

Abstract

Plants play a vital role in the survival of all organisms on Earth. Due to this fact, it is very important to ensure that measures are taken to detect and mitigate any diseases on plants. Identification of the plant diseases is important in order to prevent the losses within the yield. It's terribly troublesome to observe the plant diseases manually. It needs a tremendous quantity of labour, expertise within the plant diseases, and conjointly need the excessive time interval. Hence, with the advancement in deep learning and computer vision it is now possible to detect the plant disease effectively by observing the disease pattern of leaves of plants, which will help the farmers to classify the disease in their plant. Moreover, several performance metrics are also used for the evaluation of this project. This study provides an efficient solution for detecting multiple diseases in many plant families. In this study thousands of images of healthy and infected plant leaves which are available in public domain were used to train deep learning model, which can classify the respected disease. This model has achieved a high level of accuracy in detecting and recognizing the plant variety and the type of diseases the plan was infected with.