• DocumentCode
    136017
  • Title

    A survey of image-based Arabic sign language recognition

  • Author

    Mohandes, M. ; Junzhao Liu ; Deriche, M.

  • Author_Institution
    Dept. of Electr. Eng., King Fahd Univ. of Pet. & Miner., Dhahran, Saudi Arabia
  • fYear
    2014
  • fDate
    11-14 Feb. 2014
  • Firstpage
    1
  • Lastpage
    4
  • 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.
  • Keywords
    handicapped aids; natural language processing; sign language recognition; automatic translation; deaf impaired people; hearing impaired people; image based automatic recognition; image-based Arabic sign language recognition; information technology; native language; spoken language; spoken words; vocal people; Hidden Markov models; Image recognition; Image segmentation; Polynomials; Real-time systems; Thumb; Arabic sign language recognition; alphabet recognition; continuous recognition; image-based; sensor-based; word recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multi-Conference on Systems, Signals & Devices (SSD), 2014 11th International
  • Conference_Location
    Barcelona
  • Type

    conf

  • DOI
    10.1109/SSD.2014.6808906
  • Filename
    6808906