• DocumentCode
    1595
  • Title

    Image-Based and Sensor-Based Approaches to Arabic Sign Language Recognition

  • Author

    Mohandes, M. ; Deriche, M. ; Liu, Jiangchuan

  • Author_Institution
    Dept. of Electr. Eng., King Fahd Univ. of Pet. & Miner., Dhahran, Saudi Arabia
  • Volume
    44
  • Issue
    4
  • fYear
    2014
  • fDate
    Aug. 2014
  • Firstpage
    551
  • Lastpage
    557
  • Abstract
    Sign language continues to be the preferred method of communication among the deaf and the hearing-impaired. Advances in information technology have prompted the development of systems that can facilitate automatic translation between sign language and spoken language. More recently, systems translating between Arabic sign and spoken language have become popular. This paper reviews systems and methods for the automatic recognition of Arabic sign language. Additionally, this paper highlights the main challenges characterizing Arabic sign language as well as potential future research directions.
  • Keywords
    natural language processing; sign language recognition; Arabic sign language recognition; automatic translation; image-based approach; sensor-based approach; spoken language; Accuracy; Assistive technology; Feature extraction; Gesture recognition; Hidden Markov models; Image recognition; Sensors; Arabic sign language recognition (ArSLR); continuous sign recognition; image-based; isolated word recognition; sensor-based;
  • fLanguage
    English
  • Journal_Title
    Human-Machine Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    2168-2291
  • Type

    jour

  • DOI
    10.1109/THMS.2014.2318280
  • Filename
    6814287