Plant Disease Detection using an Image Processing Technique and Machine Learning

Abstract

Food plant cultivation and growth may be prevented in some areas by the presence of plant diseases; alternatively, food plant cultivation and growth may be possible, but plant diseases may attack the plants, destroy some or all of the plants, and reduce much of their produce, or food, before it can be harvested or consumed. The crops contract a variety of diseases as a result of diverse seasonal conditions. The plant's leaves are initially impacted by these diseases, and then contaminated the entire factory, which subsequently impacted the quality and quantity of the crop field. For classifying plant diseases, each algorithm is described along with the relevant processing techniques, such as feature extraction and image segmentation, as well as the common experimental setup. In this paper, we introduce an autonomous plant leaf disease detection and classification system that uses artificial intelligence. This system allows for rapid disease detection, classification, and application of the necessary treatments to cure the disease.