A survey of image-based Arabic sign language recognition

Abstract

Sign language is the native language of deaf and hearing impaired people which they prefer to use on their daily life. Few interpreters are available to facilitate communication between deaf and vocal people. However, this is neither practical nor possible for all situations. Advances in information technology encouraged the development of systems that can facilitate the automatic translation between sign language and spoken language, and thus removing barriers facing the integration of deaf people in the society. A lot of research has been carried on the development of systems that translate sign languages into spoken words and the reverse. However, only recently systems translating between Arabic sign language and spoken language have been developed. Many signs of the Arabic sign language are reflection of the environment (White color in Arabic sign language is a finger pointing to the chest of the signer as the tradition for male is to wear white color dress). Several review papers have been published on the automatic recognition of other sign languages. This paper represents the first attempt to review systems and methods for the image based automatic recognition of the Arabic sign language. It reviews most published papers and discusses a variety of recognition methods. Additionally, the paper highlights the main challenges characterizing the Arabic sign language as well as potential future research directions in this area.