IRJET - Paddy Crop Disease Detection using Deep Learning Technique by using Digital Image Processing

This document describes a study that uses deep learning and digital image processing techniques to detect diseases in paddy crops. The proposed system takes digital images of affected leaf parts as input and outputs the name of the detected disease and recommended pesticides. It first preprocesses and enhances the images before using edge detection, segmentation, and classification algorithms to analyze leaf parameters and identify diseases. The goal is to enable accurate, automated disease detection to help farmers protect crops and minimize pesticide usage.