MedicPlant: A mobile application for the recognition of medicinal plants from the Republic of Mauritius using deep learning in real-time

Sameerchand Pudaruth, Mohamad Fawzi Mahomoodally, Noushreen Kissoon, Fadil Chady

Abstract


To facilitate the recognition and classification of medicinal plants that are commonly used by Mauritians, a mobile application which can recognise seventy different medicinal plants has been developed. A convolutional neural network (CNN) based on the TensorFlow framework has been used to create the classification model. The system has a recognition accuracy of more than 90%. Once the plant is recognised, a number of useful information is displayed to the user. Such information includes the common name of the plant, its English name and also its scientific name. The plant is also classified as either exotic or endemic followed by its medicinal applications and a short description. Contrary to similar systems, the application does not require an internet connection to work. Also, there are no pre-processing steps, and the images can be taken in broad daylight. Furthermore, any part of the plant can be photographed. It is a fast and non-intrusive method to identify medicinal plants. This mobile application will help the Mauritian population to increase their familiarity of medicinal plants, help taxonomists to experiment with new ways of identifying plant species, and will also contribute to the protection of endangered plant species.


Keywords


Automatic identification, Convolutional neural network, Deep learning, Inception-v3, Medicinal plants

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DOI: http://doi.org/10.11591/ijai.v10.i4.pp938-947

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