• DocumentCode
    3090728
  • Title

    Video gestures identification and recognition using Fourier descriptor and general fuzzy minmax neural network for subset of Indian sign language

  • Author

    Futane, P.R. ; Dharaskar, R.V.

  • Author_Institution
    Dept. of Comput. Eng., Amravati Univ., Amravati, India
  • fYear
    2012
  • fDate
    4-7 Dec. 2012
  • Firstpage
    525
  • Lastpage
    530
  • Abstract
    Sign languages are natural languages that use to communicate with deaf and mute people. There exist different sign languages in the world. But we focused on Indian Sign Language which is on the way of standardization & very less work has been done on it so far. We have focused on Indian sign language history and progress in this domain and work carried out by various researchers in Indian Sign language recognition. Also we have proposed an approach that will convert the video of full sentence gesture of Indian sign language to text. It will initially identify individual words from the video & convert them on to text. Finally, the system will process those words to form a meaningful sentence in compliance with the simple grammar rules.
  • Keywords
    Fourier analysis; fuzzy neural nets; minimax techniques; natural language processing; sign language recognition; video signal processing; Fourier descriptor; Indian sign language recognition; Indian sign language subset; deaf people; full sentence gesture video; general fuzzy minmax neural network; grammar rules; individual word identification; mute people; natural languages; video gesture identification; video gesture recognition; Feature extraction; Gesture recognition; Handicapped aids; Image recognition; Shape; Thumb; General fuzzy min max; Gesture recognition; Indian Sign Language; Neural networ;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Hybrid Intelligent Systems (HIS), 2012 12th International Conference on
  • Conference_Location
    Pune
  • Print_ISBN
    978-1-4673-5114-0
  • Type

    conf

  • DOI
    10.1109/HIS.2012.6421389
  • Filename
    6421389