Abstract
Visual communication is important for a deft and/or mute person. It is also one of the tools for the communication between human and machines. In this paper, we develop an automatic Thai finger-spelling sign language translation system using Fuzzy C-Means (FCM) and Scale Invariant Feature Transform (SIFT) algorithms. We collect key frames from several subjects at different times of day and for several days. We also collect testing Thai finger-spelling words video from 4 subjects. The system achieves 79.90% and 51.17% correct alphabet translation and the correct word translation, respectively, with the SIFT threshold of 0.7 and 1 nearest neighbor prototype. However, when we change the number of nearest neighbor prototypes to 3, the system yields 82.19% and 55.08% correct alphabet and correct word translation, respectively, at the same SIFT threshold. These results are comparable with the manually-picked Rframe translation system.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Kramer, J., Leifer, L.: The talking glove: a speaking aid for nonvocal deaf and deaf-bilid individuals. In: Proc. of RESNA 12th Annual Conference, New Orleans, Louisiana, pp. 471–472 (1989)
Fels, S.S., Hinton, G.E.: Glove-talk: a neural network interface between a data-glove and a speech synthesizer. IEEE Trans. On Neural Networks 4(1), 2–8 (1993)
Su, M.C., Jean, W.F., Chang, H.T.: A static hand gesture recognition system using a composite neural network. In: Proceedings of the Fifth IEEE International Conference on Fuzzy Systems, September 1996, pp. 786–792 (1996)
Chen, L.Y., Mizuno, N., Fujimoto, H., Fujimoto, M.: Hand shape recognition using the bending element of fingers in sign language. Transactions of the Japan Society of Mechanical Engineers, Part C 68(12), 3689–3696 (2002)
Wu, J.Q., Gao, W., Chen, X.L., Ma, J.Y.: Hierarchical DGMM recognizer for Chinese sign language recognition. Journal of Software 11(11), 1430–1439 (2000)
Gao, W., Chen, X.L., Ma, J.Y., Wang, Z.Q.: Building language communication between deaf people and hearing society through multimodal human-computer interface. Chinese Journal of Computers 23(12), 1253–1260 (2000)
Wu, J.Q., Gao, W., Song, Y., Liu, W., Pang, B.: Simple sign language recognition system based on data glove. In: International Conference on Signal Processing Proceedings (ICSP), vol. 2, pp. 1257–1260 (1998)
Min, B.W., Yoon, H.S., Soh, J., Yang, Y.M., Ejima, T.: Hand gesture recognition using Hidden Markov Models. In: IEEE International Conference on Systems, Man, and Cybernatics (Computational Cybernatics and Simulation), October 1997, pp. 4232–4235 (1997)
Huang, C.L., Huang, W.Y.: Sign language recognition using model-based tracking and a 3D Hopfield neural network. Machine Vision and Applications 10(5-6), 292–307 (1998)
Kobayashi, T., Haruyama, S.: Partly-Hidden Markov model and its application to gesture recognition. In: IEEE International Conference on Acoustics, Speech and Signal Processing – Proceedings (ICASSP), vol. 4, pp. 3081–3084 (1997)
Chen, F.S., Fu, C.M., Huang, C.L.: Hand gesture recognition using a real-time tracking method and hidden Markov models. Image and Vision Computing 21(8), 745–758 (2003)
Alon, J., Athisos, V., Yuan, Q., Sclaroff, S.: Simultaneous localization and recognition of dynamic hand gestures. In: Proc. IEEE Workshop on Motion and Video Computing, January 2005, pp. 254–260 (2005)
Auephanwiriyakul, S., Chaisatian, P.: Static Hand Gesture Translation Using String Grammar Hard C-Means. In: The Fifth International Conference on Intelligent Technologies, Houston, Texas, USA (December 2004)
Jiang, H., Helal, A., Elmagarmid, A.K., Joshi, A.: Scene change detection techniques for video database systems. ACM Multimedia Information Systems (1996)
Joshi, A., Auephanwiriyakul, S., Krishnapuram, R.: On Fuzzy Clustering and Content Based Access to Networked Video databases. In: 8th IEEE Workshop on Research Issue in Data Engineering (1998)
Auephanwiriyakul, S., Joshi, A., Krishnapuram, R.: Fuzzy Shot Clustering to Support Networked Video Databases. In: IEEE FUZZ-IEEE 1998/WCC I998 (May 1998)
Lowe, D.G.: Distinctive Image Features from Scale-Invariant Keypoints. International Journal of Computer Vision 60(2), 91–110 (2004)
Office of The Basic Education Commission, Thai Hand Sign Language Handbook under the Initiatives of Her Royal Highness Princess Maha Chakri Sirindhorn, Bangkok, Thailand (1997) (in Thai)
Jiang, H., Helal, A., Elmagarmid, A.K., Joshi, A.: Scene change detection techniques for video database systems. ACM Multimedia Information Systems (1996)
Bezdek, J.C.: Pattern Recognition with Fuzzy Objective Function Algorithms. Plenum Press, New York (1981)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Phitakwinai, S., Auephanwiriyakul, S., Theera-Umpon, N. (2008). Thai Sign Language Translation Using Fuzzy C-Means and Scale Invariant Feature Transform. In: Gervasi, O., Murgante, B., Laganà, A., Taniar, D., Mun, Y., Gavrilova, M.L. (eds) Computational Science and Its Applications – ICCSA 2008. ICCSA 2008. Lecture Notes in Computer Science, vol 5073. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69848-7_88
Download citation
DOI: https://doi.org/10.1007/978-3-540-69848-7_88
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69840-1
Online ISBN: 978-3-540-69848-7
eBook Packages: Computer ScienceComputer Science (R0)