Sumatra Traditional Food Image Classification Using Classical Machine Learning

Abstract

Indonesia is a country rich in culture. One of Indonesia's culturaldiversity is on traditional foods. Traditional food not only has a role in the cultural aspect, but also has an influence on biodiversity. Unfortunately, the current diet of people endangers the existence of traditional foods, which indirectly will also affect Indonesia's food security. Indonesia Local Food Database is one solution proposed to prevent this problem, where the database will play a role to monitor food systems in Indonesia. In this research, database development will focus on collecting data for Sumatra traditionalfood, and also building a model for image classification which will later become one of the main features of the database. Some features like color and texture are extracted from the image. These features are used for classification using 5 classical machine learning models. Evaluation results show performance that as good as deep learning approach.