Volume 2 - Issue 2, March - April 2026

Timely and accurate diagnosis of crop diseases is critical for ensuring agricultural productivity and food security. Traditional methods of disease detection are often timeconsuming, require expert knowledge, and may not be feasible for large-scale implementation. This project presents a Crop Disease Diagnosis System based on image processing techniques to automate the identification of common plant diseases. Using a dataset of leaf images, the system employs preprocessing, segmentation, feature extraction, and classification algorithms to detect and categorize diseases. Advanced machine learning models, such as Convolutional Neural Networks (CNNs), are integrated to enhance accuracy and efficiency. The proposed system provides farmers and agricultural professionals with a fast, cost-effective, and user-friendly solution to monitor plant health, potentially reducing crop losses and improving yield outcomes.

Atchaya S, Dr.Vinoth A,"Crop Diseases Diagnosis System Image Process" International Journal of Advanced Multidisciplinary Research and Educational Development, V2(2): Page(1412-1420) Mar-Apr 2026. ISSN: 3107-6513. www.ijamred.com. Published by Scientific and Academic Research Publishing.