Abstract
Human Computer Interaction is geared towards seamless human machine integration without the need for LCDs, Keyboards or Gloves. Systems have already been developed to react to limited hand gestures especially in gaming and in consumer electronics control. Yet, it is a monumental task in bridging the well-developed sign languages in different parts of the world with a machine to interpret the meaning. One reason is the sheer extent of the vocabulary used in sign language and the sequence of gestures needed to communicate different words and phrases. Auslan the Australian Sign Language is comprised of numbers, finger spelling for words used in common practice and a medical dictionary. There are 7415 words listed in Auslan website. This research article tries to implement recognition of numerals using a computer using the static hand gesture recognition system developed for consumer electronics control at the University of Wollongong in Australia. The experimental results indicate that the numbers, zero to nine can be accurately recognized with occasional errors in few gestures. The system can be further enhanced to include larger numerals using a dynamic gesture recognition system.
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References
Johnston, T.: Signs of Australia: A new dictionary of Auslan, North Rocks. North Rocks Press, NSW (1998)
Johnston, T., Schembri, A.: Australian Sign Language: An introduction to sign language linguistics. Cambridge University Press (2007)
Premaratne, P., Nguyen, Q.: Consumer Electronics Control System based on Hand Gesture Moment Invariants. IET Computer Vision 1(1), 35–41 (2007)
Premaratne, P., Ajaz, S., Premaratne, M.: Hand Gesture Tracking and Recognition System Using Lucas-Kanade Algorithm for Control of Consumer Electronics. Neurocomputing Journal (2012), How to Cite or Link Using DOI, http: ==dx:doi:org=10:1016=j:neucom:2011:11:039
Premaratne, P., Ajaz, S., Premaratne, M.: Hand gesture tracking and recognition system for control of consumer electronics. In: Huang, D.-S., Gan, Y., Gupta, P., Gromiha, M.M. (eds.) ICIC 2011. LNCS, vol. 6839, pp. 588–593. Springer, Heidelberg (2012)
Premaratne, P., Premaratne, M.: New structural similarity measure for image comparison. In: Huang, D.-S., Gupta, P., Zhang, X., Premaratne, P. (eds.) ICIC 2012. CCIS, vol. 304, pp. 292–297. Springer, Heidelberg (2012)
Premaratne, P., Premaratne, M.: Image similarity index based on moment invariants of approximation level of discrete wavelet transform. Electronics Letters 48-23, 1465–1467 (2012)
Harding, P.R.G., Ellis, T.: Recognizing hand gesture using Fourier descriptors. In: Proceedings of the 17th International Conference on Pattern Recognition, vol. 3, pp. 286–289 (2004)
Ho, S., Greig, G.: Space on image profiles about an object boundary. In: Griffin, L.D., Lillholm, M. (eds.) Scale-Space 2003. LNCS, vol. 2695, pp. 564–575. Springer, Heidelberg (2003)
Zhongliang, Q., Wenjun, W.: Automatic ship classification by superstructure moment invariants and two-stage classifier. In: ICCS/ISITA 1992 Communications on the Move (1992)
Hu, M.K.: Visual Pattern Recognition by Moment Invariants. IRE Trans. Info. Theory IT8, 179–187 (1962)
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Premaratne, P., Yang, S., Zou, Z., Vial, P. (2013). Australian Sign Language Recognition Using Moment Invariants. In: Huang, DS., Jo, KH., Zhou, YQ., Han, K. (eds) Intelligent Computing Theories and Technology. ICIC 2013. Lecture Notes in Computer Science(), vol 7996. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39482-9_59
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DOI: https://doi.org/10.1007/978-3-642-39482-9_59
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