When it comes to productivity, economics, quality, and quantity of agricultural goods, plant diseases have a significant negative impact. It is important to reduce the damage caused by plant diseases because 70% of India's gross domestic product (GDP) depends on agricultural output. To prevent such illnesses, plants must be watched carefully beginning very early in their life cycle. The conventional way for this monitoring is naked eye inspection, which is more time-consuming, costly, and requires a great deal of experience. So, automating the illness detection system is necessary to speed up this procedure. It is necessary to use image processing techniques to create an illness detection system. Systems built using different image processing methods have been created by several researchers. This research examines the possibilities of plant leaf disease detection systems that aid in agricultural progress. It consists of several stages, including image acquisition, segmentation, feature extraction, and classification.