PROMOTING ACCESS TO AFRICAN RESEARCH

Journal of Fundamental and Applied Sciences

The AJOL site is currently undergoing a major upgrade, and there will temporarily be some restrictions to the available functionality.
-- Users will not be able to register or log in during this period.
-- Full text (PDF) downloads of Open Access journal articles will be available as always.
-- Full text (PDF) downloads of subscription based journal articles will NOT be available
We apologise for any inconvenience caused. Please check back soon, as we will revert to usual policy as soon as possible.





Malaysian sign language dataset for automatic sign language recognition system

M. Karbasi, A. Zabidi, I.M. Yassin, A. Waqas, Z. Bhatti

Abstract


Hearing impaired individuals have issues to communicate with normal people. They have
their own language called Sign Language (SL) to express their feeling or to communicate
with others. As communication is an essential part of normal everyday life, it is particularly
important for deaf people to communicate as normally as possible with others. Recent
advancements in computing technologies have the potential to be applied in the field of SL
recognition. These computer-based approaches are able to translate the SL into verbal
language and vice-versa. This paper describes the development of a dataset for an automated
SL recognition system based on the Malaysian Sign Language (MSL). Implementation results
are described.

Keywords: sign language; pattern classification; database.





http://dx.doi.org/10.4314/jfas.v9i4S.26
AJOL African Journals Online