• DocumentCode
    238025
  • Title

    Real time Sign Language Recognition using PCA

  • Author

    Sawant, Shreyashi Narayan ; Kumbhar, M.S.

  • Author_Institution
    Dept. of Electron. & Telecommun., Rajarambapu Inst. of Technol., Islampur, India
  • fYear
    2014
  • fDate
    8-10 May 2014
  • Firstpage
    1412
  • Lastpage
    1415
  • Abstract
    The Sign Language is a method of communication for deaf-dumb people. This paper presents the Sign Language Recognition system capable of recognizing 26 gestures from the Indian Sign Language by using MATLAB. The proposed system having four modules such as: pre-processing and hand segmentation, feature extraction, sign recognition and sign to text and voice conversion. Segmentation is done by using image processing. Different features are extracted such as Eigen values and Eigen vectors which are used in recognition. The Principle Component Analysis (PCA) algorithm was used for gesture recognition and recognized gesture is converted into text and voice format. The proposed system helps to minimize communication barrier between deaf-dumb people and normal people.
  • Keywords
    feature extraction; handicapped aids; image segmentation; mathematics computing; principal component analysis; real-time systems; sign language recognition; Indian sign language; Matlab; PCA; deaf-dumb people; feature extraction; gesture recognition; hand segmentation; principle component analysis; real time sign language recognition; Artificial neural networks; Feature extraction; Image resolution; Image segmentation; Speech recognition; Training; Vectors; Feature Extraction; PCA; Sign Language; Sign Recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Communication Control and Computing Technologies (ICACCCT), 2014 International Conference on
  • Conference_Location
    Ramanathapuram
  • Print_ISBN
    978-1-4799-3913-8
  • Type

    conf

  • DOI
    10.1109/ICACCCT.2014.7019333
  • Filename
    7019333