A Two-Stage Visual Turkish Sign Language Recognition System Based on Global and Local Features

  • Hakan Haberdar
  • Songül Albayrak
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4203)


In order to provide communication between the deaf-dumb people and the hearing people, a two-stage system translating Turkish Sign Language into Turkish is developed by using vision based approach. Hidden Markov models are utilized to determine the global feature group in the dynamic gesture recognition stage, and k nearest neighbor algorithm is used to compare the local features in the static gesture recognition stage. The system can perform person dependent recognition of 172 isolated signs.


Hide Markov Model Local Feature Gesture Recognition American Sign Hand Shape 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Hakan Haberdar
    • 1
  • Songül Albayrak
    • 1
  1. 1.Computer Science and Engineering DepartmentYıldız Technical UniversityBeşiktaşTurkey

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