This document proposes a system to detect diseases in sugarcane leaves early using image processing techniques. It uses a hidden Markov model for image segmentation and anisotropic diffusion to remove noise from images without blurring edges. A convolutional neural network is then used for disease classification. The system allows users to either select sample leaf images showing symptoms or capture images using a mobile device. It aims to help farmers identify diseases accurately to help minimize crop losses. The proposed system can detect diseases with 75% accuracy.