Indonesian Sign Language Recognition by Using the Static and Dynamic Features

Abstract

some hearing-impaired people face a communication problem. Even though they can communicate with others by using sign language, but a lot of people cannot understand the sign language. As a consequence, they can only communicate with limited people. Therefore, we need a Sign Language Recognition System (SLRs) which catch the sign language and translate them into text. Some research about SLRs have been done in some countries. But only a few people conducted research on Indonesian sign language. Further, the research were limited to static features for recognizing static sign language. Other researcher conducted a research on dynamic features, but the dynamic features were good only for dynamic sign language. Thus, in this study we proposed the integration between the static features and dynamic features to recognise both static sign language and dynamic sign language. In this study we conducted two integration scenario. Based on our experiment, recognising whether a gesture was static or dynamic before doing classification produced a good result. The accuracy of this proposed study reach 89% to recognise 20 words.