ROLE OF IMAGE ENHANCEMENT IN PADDY LEAF DISEASE DETECTION : A STUDY

Abstract

The detection and classification of illnesses using plant leaf photographs is required in the sector of agriculture. Finding the illnesses of paddy leaf using an image processing system will lessen the dependency on farmers in order to safeguard agricultural products. Using image processing, the study article identifies and categorises illness in paddy leaf. 2- Dimensional computerised photos are electronic images that have been made using a computer. They are mostly created utilising two-dimensional forms such as 2-Dimensional geometric shape, word, and electronic graphics, as well as ways unique to them. It is possible to use the term to refer to a branch of computer science that involves specific methodologies, or it may refer to the forms themselves. These are the most common forms of digital photographs. Initially, they are based on traditional printing and drawing technologies, such as scientific drawing, advertising, typography, mapping, and so forth. A two-dimensional image/graphic is more than simply a mirror of a real-world item in such implementations; it is an independent creation with extra textual content. Two-dimensional models are selected because they have more stringent control over images/graphics than three-dimensional electronic images. In terms of aesthetic, the approach of three Dimensional digital images is extremely similar to camera work. In this post, we used BILINEAR Interpolation to scale photos and compress them with little image quality loss. This research introduced an advanced CNN-based technique to detecting and classifying rice leaf disease. In order to diagnose illness more quickly and accurately, advanced mechanisms have used a strategy that considers picture compression, edge detection, and CNN.