Abstract

Abstract: Agriculture is the foundation of every economy on the planet. Crop output is one of the most important elements impacting a country's domestic market situation. Agricultural output, in any area of the world, is a fundamental precondition for economic development. It is vital because it offers raw materials, work, and food to a variety of individuals. Estimated crop output varies greatly around the globe due to a variety of factors. Overuse of chemical fertilizers, the presence of chemicals in water supplies, irregular rainfall distribution, varying soil fertility, and other factors are among them. Aside from these difficulties, one of the most commonly encountered challenges throughout the world is the destruction of a large portion of output due to disease. After giving appropriate resources to the fields, the presence of diseases in the plants cultivated reduces a large portion of the production. Plant diseases must be controlled since agricultural yields account for 70% of the Indian economy. To avoid infections, plants must be watched from the very beginning of their life cycle. The conventional form of supervision is naked eye inspection that is time-consuming, costly, & requires a great deal of experience. So, to speed up this procedure, the illness detection system must be automated. Image processing techniques will be used to create the illness detection system. Numerous investigators have created systems based on several image processing approaches. This study examines the possibility of technologies for detecting illness in plant leaves, which aids agricultural progress. Image capture, segmentation, feature extraction, & classification are some of the steps.Keywords: Computer Vision; Digital Image Processing; Plant Disease; Leaf