A Study on the Ayurveda Plant Recognition for Remedial Medications Using Image Processing Techniques

Abstract

Plants are considered an essential part of our ecosystem and Sri Lanka has a long history of using plants as a source of medicines in Ayurveda. In addition to some herbaceous plants serving as a food source, have medicinal values. In the Ayurveda medicinal industry, it is very important to identify the correct herbs that help in the preparation of remedial medicines. The identification of these suitable herbaceous plants is often done by skilled specialists. However the problem is since identification is based on human cognition, it can lead to misjudgment. So it a waste that humankind couldn’t use the herbal power of remedial medications. To address this question the paper proposes a simple and effectual methodology for identification of Ayurveda's herbaria, using mobile devices in the android platform by implementing image processing techniques. The main characteristics required to identify a medicinal herb are the shape, color, and texture of the leaf. The color and texture of the leaf cover vital parameters that are unique to a particular plant. Preprocessing, feature extraction, and classification are the three major phases in the suggested methodology. In order to train neural networks, images of herbal plant leaves were captured under the supervision of an Ayurveda doctor. For all the images backgrounds are removed and resized before applying classification techniques. According to the methodology, the leaf images are trained and the result can be shown through the mobile application. The study got 94% of accuracy for the proposed methodology