Open AccessIdentification of Medicinal Plants using Deep Learning
Author(s) -
R. Upendar Rao,
M. Sai Lahari,
K. P. RUPHAA SRI,
K. Yaminee Srujana,
D. Yaswanth
Publication year - 2022
Publication title -
international journal for research in applied science and engineering technology
Language(s) - English
Resource type - Journals
ISSN - 2321-9653
DOI - 10.22214/ijraset.2022.41190
Subject(s) - identification (biology) , medicinal plants , plant identification , feature (linguistics) , artificial intelligence , computer science , plant species , pattern recognition (psychology) , traditional medicine , botany , biology , medicine , linguistics , philosophy
Identification of the correct medicinal plants that goes in to the preparation of a medicine is very important in ayurvedic, folk and herbal medicinal industry. The main features required to identify a medicinal plant is its leaf shape, color and texture. Color and texture from both sides of the leaf contain deterministic parameters to identify the species. In this project we explore feature vectors from both the front and back side of a green leaf along with morphological features to arrive at a unique optimum combination of features that maximizes the identification rate. A database of medicinal plant leaves is created from scanned images of front and back side of leaves of commonly used medicinal plants. The leaves are classified based on the shape and dimension combination. It is expected that for the automatic identification of medicinal plants this system will help the community people to develop their knowledge on medicinal plants, help taxonomists to develop more efficient species identification techniques and also participate significantly in the pharmaceutical drug manufacturing. Keywords: Classification, feature extraction, morphological features, optimization, plant identification, texture features.