Dr. Atul Patel

In Indian economy, Agriculture is considered as a one of the strongest pillars. Agriculture sector contributes significantly in GDP of the country and it provides employability to many people live in rural area. Plant disease interrupts normal growth of plant and it is one of major reason behind less production that turns to economic losses. Timely detection of disease helps to provide the remedies that can control the spreading of disease in plants. Leaf examination is deliberated as a one of the best technique in plant disease diagnosis. Computer vision and machine learning become evolving fields that makes computers able to recognize and understand information from digital images. The paper proposed a prediction model for plant leaf disease detection and classification using computer vision and machine learning methods. The raw image of a leaf is pre-processed, segmented and features like shape, color, texture, vein etc. are extracted. Different machine learning classifiers are applied to classify the leaf image. The experimental results are evaluated and compared with Random Forest, Support Vector Machine, K-Neighrest Neighbor and Artificial Neural Network. The proposed prediction model performs well with random forest as compare to other classifiers.