In the present World scenario, agricultural farming plays a crucial role as most of people depend on it. But in the current scenario, farmers are finding it hard as the plant leaves are being affected by various diseases in the yield. Tracking plant health and finding parasites for the good crop is essential to lessen disease spread and facilitate effective management practices. In order to bring down this problem and to increase the productivity of the crop, we have put forward a technique for detecting diseased leaves rather than examining them manually. Manual monitoring of leaf disease do not give satisfactory result as naked eye observation is an old method that consumes much time for disease recognition and also needs expertise, hence it is non-effective. In view of this, we introduced a modern technique to find out diseases related to leaves. To overcome the limitations of traditional eye observations, we used a digital image processing technique for fast and accurate disease detection of plant leaves. In our proposed system there exists a software solution for the automatic detection of plant leaf diseases using MATLAB software. The proposed approaches involve image pre-processing and feature extraction. The research work carried out has the potential to be used as an effective tool for the early detection and diagnosis of plant leaf diseases, which aids farmers to take preventive measures to reduce crop loss due to diseases infecting the crop and aids in enhancing economic growth.