A Review on Various Plant Disease Detection Using Image Processing
Diksha Tandekar, Snehlata Dongre
Abstract
More than 50% of Indians are employed in agriculture. And any disruption in this sector affects a large part of the population. Some of these disturbances are climate change, infertile soils, and plant diseases. Leaf diseases are the major problem of crops and identification of leaf diseases is very difficult. If these diseases are not detected, it can lead to great losses. In this work, the disease of a plant leaf is detected using images. In this work, the process of feature extraction, dataset creation, classifier training, and classification feature algorithm is followed. In this work, many machine learning and deep learning algorithms are used to find out which are best for leaf disease detection, such as Random Forest Classifier (RFC), Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Convolutional Neural Network. It was obtained that the Random Forest algorithm was the most suitable for classification. This algorithm can help us classify the various kinds of diseases that would occur in the plant leaves.