Hand Gesture Recognition Via a New Self-organized Neural Network

  • E. Stergiopoulou
  • N. Papamarkos
  • A. Atsalakis
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3773)


A new method for hand gesture recognition is proposed which is based on an innovative Self-Growing and Self-Organized Neural Gas (SGONG) network. Initially, the region of the hand is detected by using a color segmentation technique that depends on a skin-color distribution map. Then, the SGONG network is applied on the segmented hand so as to approach its topology. Based on the output grid of neurons, palm geometric characteristics are obtained which in accordance with powerful finger features allow the identification of the raised fingers. Finally, the hand gesture recognition is accomplished through a probability-based classification method.


Gesture Recognition Hopfield Neural Network Hand Gesture Recognition Color Segmentation Hand Image 
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 2005

Authors and Affiliations

  • E. Stergiopoulou
    • 1
  • N. Papamarkos
    • 1
  • A. Atsalakis
    • 1
  1. 1.Image Processing and Multimedia Laboratory, Department of Electrical & Computer EngineeringDemocritus University of ThraceXanthiGreece

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