Paper Details

Name: Mahesh Kini, Rakesh, Sagar M H, Sanjay R & Preethesh Clive D Souza
Country: India

Year: 2026
Volume: Volume No: 13, January, Year: 2026 (Special Issue)
Page Number: 50-55
DOI: https://doi.org/10.5281/zenodo.18950752

ABSTRACT:
From ancient times, plants have played a crucial role in Ayurveda as a source of medicine. Accurate recognition of medicinal plants is essential in preparing Ayurvedic formulations, which has traditionally relied on manual expertise. However, due to the increasing demand for large-scale herbal medicine production, automating this process is now necessary. This paper presents a systematic approach for identifying medicinal plants using the Random Forest algorithm, a robust ensemble-based machine learning technique. The method employs a combination of color, texture, and structural characteristics extracted from plant images to classify them effectively. The experimental findings confirm the efficiency of this approach in achieving high classification accuracy, offering a scalable and reliable solution for the herbal medicine industry. By integrating artificial intelligence into this domain, the process not only ensures accuracy but also minimizes
reliance on human expertise, thereby facilitating mass production while maintaining quality and authenticity.

Keywords— Medicinal Plants, Plant Identification, Machine Learning, Image Recognition, Convolutional Neural Networks (CNNs), Support Vector Machines (SVM).