@inproceedings{81fa73b32b8b409b9a9602b6ae86aecc,
title = "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.",
keywords = "classical machine learning, feature extractions, food security, Gabor features, histograms, traditional food",
author = "Fahira, {Puteri Khatya} and Ari Wibisono and Wisesa, {Hanif Arief} and Rahmadhani, {Zulia Putri} and Petrus Mursanto and Adi Nurhadiyatna",
year = "2019",
month = oct,
doi = "10.1109/ICICoS48119.2019.8982447",
language = "English",
series = "ICICOS 2019 - 3rd International Conference on Informatics and Computational Sciences: Accelerating Informatics and Computational Research for Smarter Society in The Era of Industry 4.0, Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "ICICOS 2019 - 3rd International Conference on Informatics and Computational Sciences",
address = "United States",
note = "3rd International Conference on Informatics and Computational Sciences, ICICOS 2019 ; Conference date: 29-10-2019 Through 30-10-2019",
}