A Computer Aided System for Tropical Leaf Medicinal Plant Identification

Abstract

The objective of this paper is to develop a computer aided system for leaf medicinal plant identification using Probabilistic Neural Network. In Indonesia only 20-22% of n1edicinal plants have been cultivated. Generally, identification process of medicinal plants has been done manually by a herbarium taxonomist using guidebook of taxonomy/dendrology. This system is designed to help taxonomist to identify leaf medicinal plant automatically using a computer-aided system. This system uses three features of leaf to identify the medicinal plant, i.e., morphology, shape, and texture. Leaf is used in this system for identification because easily to find. To classify medicinal plant \Ve used Probabilistic Neural Net\vork. The features \Vill be combined using Product Decision Rule (PDR). The system was tested on 30 species medicinal plant fro1n Garden of Biopharmaca Research Center and Greenhouse Center of Ex· situ Conservation of Medicinal Indonesian Tropical Forest Plants, Faculty of Forestry, Bogor Agriculture University, Indonesia. Experiment results showed that the accuracy of medicinal plant identification using combination of leaf features increase until 74,67%. The comparative analysis of leaf features has been performed statistically. It showed that shape is a dominant features for plant identification. This system is very pron1ising to help people identify medicinal plant auton1atically and for conservation and utilization of medicinal plants.