Automatic Classification of Medicinal Plants of Leaf Images Based on Convolutional Neural Network

Abstract

AbstractPlants are the basis of all living things on earth, supplying us with oxygen, food, shelter, medicine, and preserving the planet from dam-ages that could face climate changes. Concerning their medicinal abilities, limited access to proper medical centers in many rural areas and developing countries made traditional medicine preferable by the community. In addition, their lower side effect and affordability also plays a big role. More than half of the population uses medicinal plants directly and indirectly for animals and personal use in Ethiopia. However, accurate medicinal plant identification has always been a challenge for manual identification and automatic recognition systems mainly because the knowledge transfer between the knowledge holders (traditional physicians, elderly) and modern science have a huge gap. Several studies addressed an automatic plant recognition system using different feature extraction methods and classification algorithms. In this paper, a novel dataset, which was based on Ethiopian medicinal plants, that use the leaf part of the plant, as a medicine was used to automatically classify the plants accordingly using their leaf image. An attempt has been made to collect leaf images of medicinal plants in Ethiopia, to train, test collected dataset images, and classify those images using convolutional neural network models like GoogleNet and AlexNet. The proposed convolutional neural networks were fine-tuned with the adjustment of hyper-parameters like learning rate, the number of epochs, optimizers to the models. Image augmentation is also implemented to enlarge the dataset. The experimental result for the augmented dataset and more training epoch gave better performance and accuracy in the classification of the images. From the two selected convolutional neural network models, the best model is then determined based on the result in accuracy and loss; from an experiment conducted, the best model, which is GoogLeNet with an accuracy of 96.7 % chosen to develop a web-based automatic medicinal plant classification system.KeywordsMedicinal plantsLeaf imagesConvolutional neural networkGoogleNetAlexNet