A Computer Aided System for Tropical Leaf Medicinal Plant Identification

Yeni Herdiyeni, Elvira Nurfadhilah, Ervizal A.M. Zuhud, Ellyn K. Damayanti, Kohei Arai, Hiroshi Okumura


The objective of this paper is to develop a computer aided system for leaf medicinal plant identification using ProbabilisticNeural Network. In Indonesia only 20-22% of medicinal plants have been cultivated. Generally, identification process of medicinalplants has been done manually by a herbarium taxonomist using guidebook of taxonomy/dendrology. This system is designed to helptaxonomist to identify leaf medicinal plant automatically using acomputer-aided system. This system uses three features of leaf toidentify 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 we used Probabilistic Neural Network. The features will be combined using Product Decision Rule (PDR).The system was tested on 30 species medicinal plant from Garden of Biopharmaca Research Center and Greenhouse Center of Exsitu 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 until74,67%.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 promising to help people identify medicinal plant automatically and for conservation and utilization of medicinal plants.


leaf identification; leaf morphology; leaf shape; product decision rule; medicinal plants; probabilistic neural network.

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DOI: http://dx.doi.org/10.18517/ijaseit.3.1.270


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Published by INSIGHT - Indonesian Society for Knowledge and Human Development