@inproceedings{bbc100ea661b41ff8ab61c1eda493210,
title = "Feature Extraction from Smartphone Images by Using Elliptical Fourier Descriptor, Centroid and Area for Recognizing Indonesian Sign Language SIBI (Sistem Isyarat Bahasa Indonesia)",
abstract = "Sistem Isyarat Bahasa Indonesia (SIBI) is the official sign language in Indonesia. This research aims to create a translator for SIBI to be installed on a smartphone. The translator will analyze gestures for inflectional words, which are root words combined with prefixes, and/or suffixes. The feature extraction method that was used in this research is Elliptical Fourier Descriptor (EFD), additionally centroid and area data were added to retain information on hand orientation, position and shape. The extracted features will be fed into, a Long Short-Term Memory (LSTM) model which will then recognize gestures into text. The method used in this research produced 99% accuracy for root word gestures, 71% accuracy for prefix gestures, 86% accuracy for suffix gestures.",
keywords = "computer vision, deep learning, feature extraction, image processing, machine learning, sign language",
author = "{Nur Fauzan}, {Mohamad Harits} and Erdefi Rakun and Dadan Hardianto",
year = "2019",
month = feb,
day = "1",
doi = "10.1109/ICoIAS.2019.00008",
language = "English",
series = "Proceedings - 2019 2nd International Conference on Intelligent Autonomous Systems, ICoIAS 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "8--14",
booktitle = "Proceedings - 2019 2nd International Conference on Intelligent Autonomous Systems, ICoIAS 2019",
address = "United States",
note = "2nd International Conference on Intelligent Autonomous Systems, ICoIAS 2019 ; Conference date: 28-02-2019 Through 02-03-2019",
}