Medicinal Plant Classification Using Neural Network

The earth is filled with a different kinds of medicinal plants. These medicinal plants are used in some useful ways such as formulation of drugs, herbal products made from it, and common ailments and diseases cured by making medicines out of the medicinal plants. There are many medicinal plants in the wilderness. Recognition of those medicinal plants by human sight are going to take a long time, slow, tiresome, and not accurate. As many of them are under extinction as per the IUCN records, image processing comes into play by identifying the endangered plants and helping in preserving it. The Mendeley dataset has a collection of different species of healthy medicinal herbs such as Alpinia Galanga (Rasna), Citrus Limon (Lemon), and Moringa Oleifera (Drumstick), and 30 different medicinal plants with 1500–2000 images are available in Mendeley’s dataset. In each respective medicinal plant folder, 50–100 high-quality images are present. The species botanical/scientific name are named as the folder name which will be used to train the model. In this paper, it proposed a system that adopts the deep learning method to obtain high accuracy in the classification and recognition of medicinal plants. Convolutional Neural Network (CNN) is used as the system for classifying of medicinal plant images based on deep learning.