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Static Hand Gesture Recognition Using Artificial Neural Network

Trong-Nguyen Nguyen1, Huu-Hung Huynh1, and Jean Meunier 2
1. DATIC, Department of Computer Science, Danang University of Technology, Danang, Vietnam
2. DIRO, University of Montreal, Montreal, Canada

Abstract—Computers are widely used in all fields. However, the interaction between human and machine is done mainly through the traditional input devices like mouse, keyboard etc. To satisfy the requirements of users, computers need other ways to interact more conveniently, such as using speech or body language (e.g. gestures, posture). In this paper, we propose a new method supporting hand gesture recognition in the static form, using artificial neural network. The proposed solution has been tested with high accuracy (98%) and is promising. 

Index Terms—gesture recognition, sign, boundary shape, cross section, skin color

Cite: Trong-Nguyen Nguyen, Huu-Hung Huynh, and Jean Meunier , "Static Hand Gesture Recognition Using Artificial Neural Network," Journal of Image and Graphics, Vol. 1, No. 1, pp. 34-38, March 2013. doi: 10.12720/joig.1.1.34-38

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