Identification of Ayurvedic medicinal plants using machine learning

Abstract

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.