Classifying Java plum (Eugenia jambolana) Leaf for Tobacco Cigarette Wrapper using Convolutional Neural Network

Abstract

With the increasing prices of cigarettes and cigars, more and more smokers are looking for an alternative. One way to smoke without the use of traditional cigarettes, cigars, or electronic cigarettes is to roll tobacco leaves with Java plum leaves. It is difficult to select which leaves are to be used as cigarette covers because there are characteristics to be considered such as their texture, color, dryness and shape. This study aims to help or replace human experts in classifying Java Plum leaves using a Convolutional Neural Network Classifier. Tensorflow Inception V3 is retrained to classify the leaves of the Java plum into three categories, and with 1470 test images, the neural network model managed to achieve a 91.2% accuracy in the classification. The system needs more sample photos to get a higher accuracy rate.