Research Article
Identification of Different Medicinal Plants Using Machine Learning and Image Processing
@INPROCEEDINGS{10.1007/978-3-031-77075-3_7, author={Kiran Sree Pokkuluri and Ch Phaneendra Varma and Ramesh Babu Gurujukota and P. B. V. Raja Rao and S. S. S. N. Usha Devi N and M. Prasad and Nagaraju Pamarthi and P. J. R. Shalem Raju}, title={Identification of Different Medicinal Plants Using Machine Learning and Image Processing}, proceedings={Cognitive Computing and Cyber Physical Systems. 5th EAI International Conference, IC4S 2024, Bhimavaram, India, April 5--7, 2024, Proceedings, Part-I}, proceedings_a={IC4S}, year={2025}, month={2}, keywords={Image Processing Machine learning CNN Medical Plants}, doi={10.1007/978-3-031-77075-3_7} }- Kiran Sree Pokkuluri
Ch Phaneendra Varma
Ramesh Babu Gurujukota
P. B. V. Raja Rao
S. S. S. N. Usha Devi N
M. Prasad
Nagaraju Pamarthi
P. J. R. Shalem Raju
Year: 2025
Identification of Different Medicinal Plants Using Machine Learning and Image Processing
IC4S
Springer
DOI: 10.1007/978-3-031-77075-3_7
Abstract
Medicinal plants have been an essential source of remedies and treatments for various ailments throughout human history. This paper presents an innovative approach that combines machine learning and image processing to identify various medicinal plants and extract information about their traditional and modern uses. This method offers efficiency and dependability by automating the identification procedure, which lessens the reliance on human expertise and may hasten the discovery and application of medicinal plants for therapeutic purposes. In this work identification of the medical plats is done thought the shape of the plant leave, text features using digital image processing techniques, color using Convolutional Neural Works (CNN). We have achieved an accuracy of 98.6% in identifying the medical plants and we have compared our work with the existing literature with various parameters like precision, accuracy and f1 score.
