Classification of Plant Types based on Leaf Image using the Artificial Neural Network Method

Abstract

Plants have an important role in human life. Several plants can be used for daily life, namely as food, in the health sector, to become a main ingredient for the industry. Plant type classification techniques using data mining methods become one of the efforts to help humans produce more accurate and consistent classifications. The learning process in the classification method requires good dataset quality, where a small number of datasets will affect the results of the classification. The main objective of this research is to test the Artificial Neural Network (ANN) method for classifying plant species in a relatively small dataset. Three stages are proposed, namely preprocessing using image segmentation thresholding methods and morphological operations, and the extraction of metric and eccentricity features. Based on the results of testing the ANN method can also work well with relatively small datasets, which results in accuracy reaching 96% with the number of training data 125 and testing data 25.