AyurLeaf: A Deep Learning Approach for Classification of Medicinal Plants

Abstract

Ayurvedic medicines have a vital role in preserving physical and mental health of human beings. Identification and classification of medicinal plants are essential for better treatment. Lack of experts in this field makes proper identification and classification of medicinal plants a tedious task. Hence, a fully automated system for medicinal plant classification is highly desirable. This work proposes AyurLeaf, a Deep Learning based Convolutional Neural Network (CNN) model, to classify medicinal plants using leaf features such as shape, size, color, texture etc. This research work also proposes a standard dataset for medicinal plants, commonly seen in various regions of Kerala, the state on southwestern coast of India. The proposed dataset contains leaf samples from 40 medicinal plants. A deep neural network inspired from Alexnet is utilised for the efficient feature extraction from the dataset. Finally, the classification is performed using Softmax and SVM classifiers. Our model, upon 5-cross validation, achieved a classification accuracy of 96.76% on AyurLeaf dataset. AyurLeaf helps us to preserve the traditional medicinal knowledge carried by our ancestors and provides an easy way to identify and classify medicinal plants.