Excellence in Research and Innovation for Humanity
@article{(International Science Index):http://waset.org/publications/9202,
  title    = {Hand Gesture Recognition: Sign to Voice System (S2V)},
  author    = {Oi Mean Foong and  Tan Jung Low and  Satrio Wibowo},
  country   = {},
  abstract  = {Hand gesture is one of the typical methods used in
sign language for non-verbal communication. It is most commonly
used by people who have hearing or speech problems to
communicate among themselves or with normal people. Various sign
language systems have been developed by manufacturers around the
globe but they are neither flexible nor cost-effective for the end
users. This paper presents a system prototype that is able to
automatically recognize sign language to help normal people to
communicate more effectively with the hearing or speech impaired
people. The Sign to Voice system prototype, S2V, was developed
using Feed Forward Neural Network for two-sequence signs
detection. Different sets of universal hand gestures were captured
from video camera and utilized to train the neural network for
classification purpose. The experimental results have shown that
neural network has achieved satisfactory result for sign-to-voice
    journal   = {International Journal of Computer, Electrical, Automation, Control and Information Engineering},  volume    = {2},
  number    = {6},
  year      = {2008},
  pages     = {1794 - 1798},
  ee        = {http://waset.org/publications/9202},
  url       = {http://waset.org/Publications?p=18},
  bibsource = {http://waset.org/Publications},
  issn      = {eISSN:1307-6892},
  publisher = {World Academy of Science, Engineering and Technology},
  index     = {International Science Index 18, 2008},