Published Paper Details:

India has been using Ayurveda for health purposes since the time of the Vedic era. It is still one of the most antiquated medical science systems in use today. Given that Ayurvedic medicine uses a large number of medicinal plants, it is crucial to correctly identify the plants that are utilized to make medication. Typically, knowledgeable professionals with advanced training in this sector identify the suitable medicinal plants. From generation to generation, people are passing along their expertise of how to identify these therapeutic herbs. Nonetheless, there is potential for mistakes or poor judgment because the identification is entirely dependent on human perception. The drug becomes useless when the raw components are incorrect or replaced. It may possibly have some adverse consequences.This calls for the development of an effective technique that can correctly identify the Ayurvedic plant from leaf samples. Shape, color, and leaf texture are the primary characteristics that are needed to identify a medicinal plant. Vital characteristics like leaf color and texture can be used to determine the exact species to which a given plant belongs. This will ultimately increase the medication's efficiency. The goal of this research is to develop an intelligent system that, using the input leaf sample as a basis, can identify the species of plant. This study investigates a green leaf's feature vectors in order to derive a special set of feature parameters that optimize identification accuracy. This distinct feature collection serves as the basis for classifying the leaf samples.