Vol 14, No 2 (2010) > Articles >

Static Hand Gesture Recognition of Indonesian Sign Language System Based on Backpropagation Neural Networks

Farida Asriani 1 , Hesti Susilawati 1


  1. Program Studi Teknik Elektro, Fakultas Sains dan Teknik, Universitas Jenderal Soedirman, Purwokerto 53122



The main objective of this research is to perform pattern recognition of static hand gesture in Indonesian sign language. Basically, pattern recognition of static hand gesture in the form of image had three phases include: 1) segmentation of the image that will be recognizable form of the hands and face, 2) feature extraction and 3) pattern classification. In this research, we used images data of 15 classes of words static. Segmentation is performed using HSV with a threshold filter based on skin color. Feature extraction performed with the Haar wavelet decomposition filter to level 2. Classification is done by applying the back propagation system of neural network architecture with 4096 neurons in input layer, 75 neurons in hidden layer and 15 neurons in output layer. The system was tested by using 225 data validation and accuracy achieved was 69%.

Keywords: artificial neural networks, feature extraction, hand gesture, segmentation, static
Published at: Vol 14, No 2 (2010) pages: 150-154

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K. Symeonidis, Hand Gesture Recognition using neural networks, Final Report Thesis Master of Science in Multimedia Signal Processing Communications School of Electronic and Electrical Engineering, UK, 2000.

S.L. Pung, Abdesslam Bouzerdoum, and Douglas Chai, Proc. Int Symposium on Signal Processing and its Applications, Paris, 2003, p.525.

E.S. Nielsen, L.A. Canalis, M.H. Tejera, Journal of WSCG 12 (2004) 395.

B. Bauer, K.-F. Kraiss, Proceeding of International Gesture Workshop, London, 2001, p.64.

M.J. Jones, J.M. Rehg, Int. J. of Comput. Vision. 46 (2002) 81.

B. Bauer, K.-F. Kraiss, Proceeding of International Conference on Pattern Recognition, 2 (2002) 434.

D. Saxe, R. Foulds, IEEE International Conference on Automatic Face and Gesture Recognition, Killington, 1996, p. 379.

Y. Cui, J. Weng, Comput. Vision Image Undertanding 78 (2000) 157.

C.L. Huang, S.H. Jeng, Mach. Vision Appl. 12 (2001) 243.

N. Tanibata, N. Stimada, J. Shirai, Proceeding of International Conference on Vision Interface, Calgary, Canada, 2002, p. 369.

M.H. Yang, N. Ahuja, M. Tabb, IEEE Transaction on Pattern Analysis and Machine Intelligence 24 (2002) 1061.

J.C. Terrillon A. Pilpre, J. Niwa, K. Yamamoto, Proceeding of International Conference on Vision Interface, Calgary, Canada , 2002, p. 369.

R. Carlos, P. Dionisio, M. Roberto, J.R. Cesar, Proceeding of the XIII Brazilian Symposium on Computer Graphics and Image Processing, Gramado, 2000.

P. Vamplew, Proceeding of 1st Euro Conference Disability, Virtual Reality Assoc. Tech., Maidenhead, UK, 1996, p. 27.

F.O. Mean, T.J. Low, W. Satrio, Proceeding of World Academy of Science, Engineering and Technology, Singapore, 42 (2008) 26.