Expressive and Deployable Hand Gesture Recognition for Sign Way of Communication for Visually Impaired People

Authors

  • R. Padmavathi  Assistant Professor, Department of Computer Science and Engineering, Dhanalakshmi Srinivasan Institute of Technology, Samayapuram Tamil Nadu, India

Keywords:

Sign Language Recognition, Sign Language

Abstract

This project is mainly focuses the sign way of communication is one of the most effective communication tool for the people who are not able to speak or hear anything. It is also useful for the person who are able to speak but not able to hear or vice versa. Sign language is boon for the deaf and dumb people. Sign language is the combination of different gesture, shape and movement of hand, body and facial expression. With the help of sign language, these physical impaired people express their emotions and thoughts to other person. Hence sign language recognition has become empirical task. Since sign language consist of various movement and gesture of hand therefore the accuracy of sign language depends on the accurate recognition of hand gesture. This project present various method of hand gesture and sign language recognition proposed in the past by various researchers.

References

  1. Meena, S.,2011.A Study On Hand Gesture Recognition. Doctoral Dissertation, National Institute Of Technology, Rourkela.
  2. Van Den Bergh, M., 2010. Visual Body Pose Analysis For Human-Computer Interaction. Diss, Eidgenössische Technische Hochschule Eth Zürich, Nr. 18838.
  3. Hai, W., 2002. Gesture Recognition Using Principal Component Analysis, Multi-Scale Theory, And Hidden Markov Models. Doctoral Dissertation, Dublin City University.
  4. Dardas, N. H. A. Q., 2012. Real-Time Hand Gesture Detection And Recognition For Human Computer Interaction. Doctoral Dissertation, University Of Ottawa.
  5. Mitra, S., & Acharya, T., 2007. Gesture Recognition: A Survey. Systems, Man And Cybernetics, Part C: Applications And Reviews, Ieee Transactions On, Vol. 37, Issue 3, Pp. 311-324.
  6. Zeshan, U., 2001. ‘A’ Level Introductory Course In Indian Sign Language .Ali. Yavar Jung National Institute For Hearing Handicapped, Mumbai, Vol. 1, Issue 38.
  7. Ibraheem, N. A., Khan, R. Z., & Hasan, M. M., 2013. Comparative Study Of Skin Color Based Segmentation (Ijais), Vol. 5, Issue 10.
  8. Professor Charles A. Bouman’s Lecture Notes Gives Introduction To Colour Space And Chromaticity Diagram:Http://Cobweb.Ecn.Purdue.Edu/~Bouman/Ee637/Notes/Pdf/Colo Urspace.Pdf.
  9. Hasan, M. M., & Mishra, P. K., 2010. Hsv Brightness Factor Matching For Gesture Recognition System. International Journal Of Image Processing (Ijip), Vol 4, Issue 5, Pp. 456-467.
  10. Dougherty, E. R., 1992. An Introduction To Morphological Image Processing.Tutorial Texts In Optical Engineering.
  11. Bishop, C. M., 1995. Neural Networks For Pattern Recognition. Oxford University Press.
  12. Haykin, S., & Network, N., 2004. A Comprehensive Foundation. Neural Networks.
  13. Freeman, W. T., & Roth, M., 1995, June. Orientation Histograms For Hand Gesture Recognition. In International Workshop On Automatic Face And Gesture Recognition, Vol. 12, Pp. 296-301.
  14. Naidoo S, Omlin Cw, Glaser M., 1998. Vision-Based Static Hand Gesture Recognition Using Support Vector Machines. University Of Western Cape, Bellville.
  15. Chang Cc, Chen Jj, Tai W, Han Cc ., 2006. New Approach For Static Gesture Recognition. J Inform Sci Eng, Vol.22, Pp.1047–1057.

IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2021-08-30

Issue

Volume 7, Issue 4, July-August-2021

Section

Research Articles

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
R. Padmavathi, " Expressive and Deployable Hand Gesture Recognition for Sign Way of Communication for Visually Impaired People, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 7, Issue 4, pp.471-475, July-August-2021.