CLASSIFICATION OF AGATHOSMA PLANT SPECIES FROM OVERLAPPING LEAVES IMAGERY
This work is supported by the Department of Higher Education and Training, South Africa, Tshwane University of Technology, South Africa and the National Research Foundation (NRF), South Africa.
This work investigated the ability of hyperspectral imagery for identifying Agathosma (A) Betulina and Agathosma (A) Crenulata plants. The plants have been used as traditional medicines to heal diseases such as urinary tract infections, stomach complaints, for washing and cleaning wounds, kidney diseases, and symptomatic relief of rheumatism. The species are normally identified on the basis of their shapes. A. Betulina has round-leaves while A. Crenulata has oval-leaves. The recognition based on morphology is no longer adequate because of extensive cultivation. New hybrids of the leaves now exist which are not easily separable. The study proposed implementation of Local Polynomial Approximation (LPA) algorithm and Principal Component Analysis (PCA) for the data processing. The data generated from the two methods are subjected to classification procedures for the plants identification. Various classifiers were used for the data separations. The results obtained reveal that most of the classifiers performed better on LPA processed data as compared to PCA.