Master Thesis



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Master Thesis


Master Thesis

- Real Time Sign Language Recognition using CyberGlove: This is the topic of my master thesis and is done using an instrumented glove. Supervised by Dr. Mohandes.

Two types of Recognition System

        - Image Based

        -Glove Based (used in the thesis)

Hardware System

- CyberGlove

-Tracking System

-Computer or a laptop

Team of my Thesis work:

      -Dr. Mohammad Derechi(Associater Professor)

      -Mohammad Ajmal Khan (Lecturer)

      -Ja'far Al-Oqaah (Insturctor for deaf and signer)

      -Mahdi Al-Faraj (Signer)

Goal Achieved:

        Recognition of 344 signs with 95% accuracy.

Some References: You can find these references from the internet or 

        from the IEEE journal from the library

1.      Robert M. De Marco and R. Foulds, “Data Recording And Analysis Of American Sign Language,” 

     Proceedings of Bioengineering Conference, 2003 IEEE 29th Annual, pp. 49-50, March 2003.

2.      W. Kadous, “GRASP: Recognition of Australian Sign Language Using Instrumented Glove,”

      B.S. thesis, The University of New South Wales, 1995.

3.      M. Jiyong , G. Wen, W. Jiangqin and  W. Chunli, “A Continuous Sign Language 

     Recognition System,” IEEE Proc. Automatic Face Gesture Recognition,

     pp. 428-433, March, 28-30 2000. 

4.      David J. Sturman and David Zeltzer, “A Survey Of Glove-Based Input,” 

     IEEE  Computer Graphics and Applications, January 1994, pp. 30-39.

5.      Qaum D.,”Gesture Recognition with a DataGlove,” IEEE Proc. Aerospace and 

     Electronics Conference, vol.2, pp. 755-760, May 1990.

6.      S. Fels and G. Higton, "Glove-Talk: A Neural Network Interface Between 

     a Data-Glove and a Speech Synthesizer," IEEE Trans. Neural Networks, 

     vol. 4, pp. 2-8, Jan. 1993.

7.      S. Fels and G. Hinton, "Glove-TalkII: A Neural Network Interface which 

     Maps Gestures to Parallel Formant Speech Synthesize Controls," IEEE Trans.

     Neural Networks, vol. 8, pp. 977-984, Sept. 1997.

8.      Waldron, M. and Kim, S., “Isolated ASL Sign Language Recognition for Deaf Persons,” 

     IEEE Trans. Rehabilitation Engineering, pp. 261-270, Sept. 1995.

9.      Sagawa, H., Takeuchi, M. and Ohki, M., “Description and Recognition Methods for

     Sign Language Based on Gesture Components,” Proc. IUI97, ( Orlando , Florida ), 

     ACM, 1997, pp. 97-104.

10.  Kim, J., Jang, W. and Bien, Z., “A Dynamic Gesture Recognition System for the 

     Korean Sign Language (KSL),” IEEE Trans. System, Man and Cybernetics, pp. 354-359, 

     vol. 26, no. 2, April, 1996.

11.  Vamplew, P., “Recognition of Sign Language Gestures Using Neural Networks,” 

     Proc. 1st Euro. Conf. Disability, Virtual & Assoc. Tech. Maidenhead, UK

     pp. 27-33, 1996.

12.  Wu jiangqin, Gao wen, Song yibo, Liu wei and Pang bo, “A Simple Sign Language 

      Recognition System Based On Data Glove,” Proc. ICSP ’98, pp. 1257-1269, 1998.`

13.  J. Eisenstein, S. Ghandeharizadeh, L. Huang, C. Shahabi, G. Shanbhag, 

     R. Zimmermann, “Analysis of Clustering Technique to Detect Hand Signs,” 

     Proceedings of 2001 International Symposium on Inteligent Multimedia, Vedio 

     and Speech Processing, pp. 259-262, 24 May 2001.

14.  S. Mehdi and Y. Khan, “Sign Language Recognition Using Sensor Gloves,” 

      Proceedings of the 9th International Conference on Neural Information 

      Processing (ICONIP’02), vol. 5, pp.2204-2206, 2002.

15.  Hernandez-Reblollar, J.L., Lindeman, R.W. and Kyriakopoulos, N., “A Multi-Class 

      Pattern Recognitino System for Practical Finger Spelling Translation,” 

      Proc. Fourth IEEE International Conference on Multimodal Interfaces, Oct. 2002, pp-185-190.

16.  Hernandez-Rebollar, J.L., Kyriakopoulos, N. and Lindeman, R.W., 

      “A New Instrumented Approach for Translating American Sign Language into Sound and Text,” 

      IEEE Proc. Automatic Face and Gesture Recognition, pp. 574-552, May, 17-19 2004.

17.  S. Al-Buraiky, “Arabic Sign Language Recognition using an Instrumented Glove,” 

      M.S. Thesis, King Fahd University of Petroleum and Minerals, Sept. 2004. 


19.  Bhatnagar, Devesh K., “Position Trackers for Head Mounted Display System: A Survey,” 

     March 29 1993, pp. 1-22.

20.  The Flock of Birds, January 18, 1999, Ascension Technology Corporation.



23.  CyberGlove v1.0 Reference Manual.

24.  VirtualHand SDK User and Programmer Guides, 2001 Immersion Corporation. 

25.  Rafael C. Gonzalez and Paul Wintz. Digital Image Processing. 

     Addison-Wesley puplishing company, 1993.

26.  D. N. Lawley and A. E. Maxwell. Factor Analysis as a Statistical Method. 

     Buterworth, Londond, 1963.

27.  MATLAB help, The Language of Technical Computing, Version 6.5.

28.  Wen Gao, Jiyong Ma, Jangqin Wu and Chunli Wang, 

     “Sign Language Recognition Based on HMM/ANN/DP,”  

     International Journal of Pattern Recognition and Artificial Intelligence,

     Vol. 14, pp. 587-602 No. 5, 2000. 

29.  Jerome M. Allen and Pierre K., “Asselin, Richard Foulds American 

      Sign Language Finger Spelling Recognition System,” IEEE  pp. 285-286, 2003.