Isolated Sign Language Characters Recognition
Abstract: People with normal
senses use spoken language to communicate with others. This method cannot be
used by those with hearing and speech impaired. These two groups of people will
have difficulty when they try to communicate to each other using their own
language. Sign language is not easy to learn, as there are various sign
languages, and not many tutors are available. This study focuses on the
character recognition based on manual alphabet. In general, the characters are divided
into letters and numbers. Letters were divided into several groups according to
their gestures. Characters recognition was done by comparing the photograph of
a character with a gesture dictionary that has been previously developed. The
gesture dictionary was created using the normalized Euclidian distance.
Character recognition was performed by using the nearest neighbor method and
sum of absolute error. Overall, the level of accuracy of the proposed method
was 96.36%.
Author: Paulus Insap Santosa
Journal Code: jptkomputergg130087
