Plant Diseases Detection Using Image Processing and Suggest Pesticides and Managements

Abstract

Various plant diseases affect farmers all over the world and there is a very small amount of solutions available online for free in order to assist. In Sri Lanka, in order to address this issue, we have done a study which outputs a mobile application which utilizes image processing and recommend pesticides according to corresponding disease. The disease detection method includes image acquisition, image pre-processing, image segmentation, feature extraction, and classification. This study looked at methods for identifying plant ailments using photos of their leaves. This work also presented unique segmentation and feature extraction techniques for plant disease identification. For feature extraction, the CNN algorithm is utilized. This research paper may be a revolutionary approach to diagnosing plant illnesses by employing a deep convolutional neural network that has been trained and fine-tuned to suit a database of a plant's leaves gathered independently for distinct plant diseases. At the end of the study we achieved an accuracy of 98 percent in detecting the plant diseases and further on implemented mobile system which can suggest pesticide accordingly.