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Malay alphabet sign language recognition

This paper describes hardware design and sensors setting and configuration for Malay sign language gesture recognition systems. A set of sensors consists of accelerometers and flexure sensors has been setup to capture the movement or gesture of shoulder, elbow, wrist, palm and fingers. This project...

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Main Authors:	Tan, Tian-Swee, Salleh, Sh-Hussain, Ariff, A. K., Wang, Wee-Sern
Format:	Conference or Workshop Item
Published:	2007
Subjects:	TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://eprints.utm.my/id/eprint/14203/ https://www.researchgate.net/publication/260423043_Malay_Alphabet_Sign_Language_Recognition
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id	my.utm.14203
record_format	eprints
spelling	my.utm.142032017-06-12T07:10:30Z http://eprints.utm.my/id/eprint/14203/ Malay alphabet sign language recognition Tan, Tian-Swee Salleh, Sh-Hussain Ariff, A. K. Wang, Wee-Sern TK Electrical engineering. Electronics Nuclear engineering This paper describes hardware design and sensors setting and configuration for Malay sign language gesture recognition systems. A set of sensors consists of accelerometers and flexure sensors has been setup to capture the movement or gesture of shoulder, elbow, wrist, palm and fingers. This project is based on the need of developing an electronic device that can translate the sign language into speech (sound) in order to enable communication to take place between the mute and deaf community with the common public. Hence, the main objective of this project is to develop a system that can convert the sign language into speech so that deaf people are able to communicate efficiently with normal people. This Human-Computer Interaction system is able to recognize 25 common words signing in Bahasa Isyarat Malaysia (BIM) by using the Hidden Markov Models (HMM) method. Both hands are involved to perform the BIM with all the sensors connect wirelessly to a PC with a Bluetooth module. This project aims to capture the hand gestures which involve multiple axis of movement. Altogether 24 sensors have been setup in different hand locations to capture hand and wrist movement in different directions. 2007 Conference or Workshop Item PeerReviewed Tan, Tian-Swee and Salleh, Sh-Hussain and Ariff, A. K. and Wang, Wee-Sern (2007) Malay alphabet sign language recognition. In: Proceedings of the International Conference on Robotics,Vision, Information and Signal Processing,ROVISP'07, 2007, Penang. https://www.researchgate.net/publication/260423043_Malay_Alphabet_Sign_Language_Recognition
institution	Universiti Teknologi Malaysia
building	UTM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Teknologi Malaysia
content_source	UTM Institutional Repository
url_provider	http://eprints.utm.my/
topic	TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	TK Electrical engineering. Electronics Nuclear engineering Tan, Tian-Swee Salleh, Sh-Hussain Ariff, A. K. Wang, Wee-Sern Malay alphabet sign language recognition
description	This paper describes hardware design and sensors setting and configuration for Malay sign language gesture recognition systems. A set of sensors consists of accelerometers and flexure sensors has been setup to capture the movement or gesture of shoulder, elbow, wrist, palm and fingers. This project is based on the need of developing an electronic device that can translate the sign language into speech (sound) in order to enable communication to take place between the mute and deaf community with the common public. Hence, the main objective of this project is to develop a system that can convert the sign language into speech so that deaf people are able to communicate efficiently with normal people. This Human-Computer Interaction system is able to recognize 25 common words signing in Bahasa Isyarat Malaysia (BIM) by using the Hidden Markov Models (HMM) method. Both hands are involved to perform the BIM with all the sensors connect wirelessly to a PC with a Bluetooth module. This project aims to capture the hand gestures which involve multiple axis of movement. Altogether 24 sensors have been setup in different hand locations to capture hand and wrist movement in different directions.
format	Conference or Workshop Item
author	Tan, Tian-Swee Salleh, Sh-Hussain Ariff, A. K. Wang, Wee-Sern
author_facet	Tan, Tian-Swee Salleh, Sh-Hussain Ariff, A. K. Wang, Wee-Sern
author_sort	Tan, Tian-Swee
title	Malay alphabet sign language recognition
title_short	Malay alphabet sign language recognition
title_full	Malay alphabet sign language recognition
title_fullStr	Malay alphabet sign language recognition
title_full_unstemmed	Malay alphabet sign language recognition
title_sort	malay alphabet sign language recognition
publishDate	2007
url	http://eprints.utm.my/id/eprint/14203/ https://www.researchgate.net/publication/260423043_Malay_Alphabet_Sign_Language_Recognition
_version_	1643646350157414400
score	13.211869

Malay alphabet sign language recognition

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