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All Journal KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal)
Aditiya Anwar
Politeknik Elektronika Negeri Surabaya
Computer Science & IT

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HAND GESTURE RECOGNITION FOR INDONESIAN SIGN LANGUAGE INTERPRETER SYSTEM WITH MYO ARMBAND USING SUPPORT VECTOR MACHINE Aditiya Anwar; Achmad Basuki; Riyanto Sigit
KLIK- KUMPULAN JURNAL ILMU KOMPUTER Vol 7, No 2 (2020)
Publisher : Lambung Mangkurat University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/klik.v7i2.320

Abstract

Hand gestures are the communication ways for the deaf people and the other. Each hand gesture has a different meaning.  In order to better communicate, we need an automatic translator who can recognize hand movements as a word or sentence in communicating with deaf people. This paper proposes a system to recognize hand gestures based on Indonesian Sign Language Standard. This system uses Myo Armband as hand gesture sensors. Myo Armband has 21 sensors to express the hand gesture data. Recognition process uses a Support Vector Machine (SVM) to classify the hand gesture based on the dataset of Indonesian Sign Language Standard. SVM yields the accuracy of 86.59% to recognize hand gestures as sign language.Keywords: Hand Gesture Recognition, Feature Extraction, Indonesian Sign Language, Myo Armband, Moment Invariant
Co-Authors Achmad Basuki Riyanto Sigit