Morphological feature based maturity level identification of Kalmegh and Tulsi leaves

Abstract

Medicinal plants are getting increasingly popular across the world for their ability to cure different diseases including chronic ones. The chemical compositions present in those plant leaves are main contributors for the healing characteristics. The potential of using such plants also depends on the maturity of the medicinal plant under use. The leaves with appropriate maturity can cause better healing potential. This paper presents a computer vision based approach towards identification of medicinal leaves namely Kalmegh and Tulsi against the different maturity levels. The morphological features from the processed images of leaves with different maturity levels are extracted in this work. The feature sets are subjected to Principal Component Analysis (PCA) based identification and separability measures for identification purpose. The results show that the presented morphological feature based maturity identification can be a promising method.