Malay alphabet sign language recognition

Abstract

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.