An Intelligent Flower Analyzing System for Medicinal Plants

Abstract

The natural sciences have been transformed with the incorporation of advanced technologies, and the current technological wave of change is also revolutionizing biological science. With the wide use of herbal medicines in traditional medical systems, the demand for medicinal plants has increased enormously. Though the current trend has made the use of medicinal plants more popular, we still require better methods to distinguish between medicinal plants and plants which do not possess medicinal value. Manual methods of plant recognition rely on a plants flower information. However, these manual processes of flower recognition are not straightforward for lay persons unless expert guidance is provided. Motivated by this reasoning, an intelligent flower analyzing system has been developed to recognize medicinal plants. Various tests have been performed on 160 images taken from four types of flowers, to recognize flowers based on their colour and shape features. The experiment was carried out using Support Vector Machine (SVM) and Principal Component Analysis (PCA) methodologies respectively for colour and shape extraction. Acquiring an average of 65% recognition rate implies that the applicability PCA and SVM in the specified domain is a valuable step forward.