학술논문
Snake Fruit Classification by Using Histogram of Oriented Gradient Feature and Extreme Learning Machine
Document Type
Conference
Author
Source
2019 3rd International Conference on Informatics and Computational Sciences (ICICoS) Informatics and Computational Sciences (ICICoS), 2019 3rd International Conference on. :1-5 Oct, 2019
Subject
Language
Abstract
Snake fruit, or most famous as Salak, is Indonesian local fruit. Salak is also one of fruit commodity from Indonesia. To perform export on Salak, rigid sortation is performed. The sortation is usually done manually. This study will implement digital image processing technique to differentiate Salak quality for export purpose. Salak sample were taken from Magelang district, one of the largest Salak producer. The feature used in this study is Histogram of Oriented Gradient. The classification used is Extreme Learning Machine (ELM). It is shown in this study that by using ELM, the highest accuracy can be achieved is 95%. A comparison classifier, SVM, is also used in this study. In this case SVM is able to achieve highest accuracy of 97.3%, which is still higher than ELM result