Indentification of ayurvedic medicinal plants using machine learning

Registration ID: IJNRD_195740

Published ID: IJNRD2305567

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Abhinav Kumar A R , Chandrashekhara , Raju S , Shreekanth Reddy

Ayurvedic, Medicinal

Identification of the correct medicinal plants that goes in to the preparation of a medicine is very important in ayurvedic medicinal industry. The main features required to identify a medicinal plant is its leaf shape, colour and texture. Colour and texture from both sides of the leaf contain deterministic parameters to identify the species. This paper explores 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 ayurvedic medicinal plants. The leaves are classified based on the unique feature combination. Identification rates up to 99% have been obtained when tested over a wide spectrum of classifiers. The above work has been extended to include identification by dry leaves and a combination of feature vectors is obtained, using which, identification rates exceeding 94% have been achieved.

Published Paper   E-Certificate

Abhinav Kumar A R, Chandrashekhara, Raju S, & Shreekanth Reddy (May-2023). Indentification of ayurvedic medicinal plants using machine learning. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(5), f433-f438. https://ijnrd.org/papers/IJNRD2305567.pdf

Volume 8 Issue 5, May-2023

Pages : f433-f438

Paper Reg. ID: IJNRD_195740

Published Paper Id: IJNRD2305567

Downloads: 000121991

Research Area: Engineering

Country: Raichur, Karnataka, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2305567.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2305567

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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