Medicinal Leaf Dataset

****Overview of Medicinal Plant Dataset and Its Significance
Mother Earth thrives with an abundance of plant life, many of which play a vital role in health and wellness. These plants serve as essential resources for drug development, herbal product formulation, and treatments for a wide range of ailments. For over 5,000 years, Ayurveda, India’s ancient system of medicine has remained a respected and widely practiced tradition. India, in particular, is home to a rich diversity of medicinal flora.
Various plant parts including leaves, bark, roots, seeds, and fruits are commonly used in the preparation of herbal remedies. These natural medicines are increasingly favoured in both developing and developed nations as alternatives to synthetic drugs, largely due to their minimal side effects.
****Need for Technological Intervention
Identifying medicinal plants by visual inspection alone can be challenging, time-intensive, and prone to error. With many species facing extinction according to IUCN records, leveraging image processing and computer vision technologies becomes essential for accurate identification and conservation. Digitizing medicinal plants is a critical step toward preserving biodiversity.
****Dataset Composition and Collection
To support intelligent recognition systems, a robust dataset of medicinal plant leaves has been curated. This dataset includes 1,010 high-resolution images representing 9 species, with each species contributing between 100 to 120 images. Examples include Piper betle (Betel), Trigonella foenum-graecum (Fenugreek), Bergera koenigii (syn. Murraya koenigii) (Curry Tree), Mentha spp. (e.g., Mentha spicata, Mentha × piperita) (Mint), Senna tora (syn. Cassia tora) (Tora Leaves), Coriandrum sativum (Coriander), Allium cepam (Onion), Raphanus sativus (Radish), Aloe vera (syn. Aloe barbadensis) (Aloe Vera), among others. Each folder is labelled with the plant’s scientific name for clarity.
Leaves were carefully collected from different plants of the same species found in local gardens, ensuring minimal disruption to the environment. Only healthy, mature leaves were selected, and efforts were made to avoid unnecessary waste. Images were captured using a Nothing mobile of 50 MP OIS camera. To enhance model training, leaf images were slightly rotated and tilted to introduce variability.
Impact on AI Research
This medicinal plant leaf dataset is a valuable resource for developing machine learning and deep learning models. It enables researchers and computer scientists to identify plant species, diagnose diseases, and explore the therapeutic properties of herbs. By making this dataset publicly available, we aim to catalyse research in the field of medicinal botany, addressing the current gap in accessible datasets and fostering innovation in plant-based healthcare solutions.
* Ph.D. work of Ms. Amruta Jadhav
* Collaborative work of Government College of Engineering, Aurangabad and JSPM University Pune