Home   >   CSC-OpenAccess Library   >    Manuscript Information
Full Text Available

This is an Open Access publication published under CSC-OpenAccess Policy.
Publications from CSC-OpenAccess Library are being accessed from over 74 countries worldwide.
Novel Approach to Use HU Moments with Image Processing Techniques for Real Time Sign Language Communication
Matheesha Fernando, Janaka Indrajith Wijjayanayake
Pages - 335 - 345     |    Revised - 30-11-2015     |    Published - 31-12-2015
Volume - 9   Issue - 6    |    Publication Date - November / December 2015  Table of Contents
Sign Language Recognition, Height to Width Ratio, Hu-moments, YCrCb Color Space.
Sign language is the fundamental communication method among people who suffer from speech and hearing defects. The rest of the world doesn’t have a clear idea of sign language. “Sign Language Communicator” (SLC) is designed to solve the language barrier between the sign language users and the rest of the world. The main objective of this research is to provide a low cost affordable method of sign language interpretation. This system will also be very useful to the sign language learners as they can practice the sign language. During the research available human computer interaction techniques in posture recognition was tested and evaluated. A series of image processing techniques with Hu-moment classification was identified as the best approach. To improve the accuracy of the system, a new approach; height to width ratio filtration was implemented along with Hu-moments. System is able to recognize selected Sign Language signs with the accuracy of 84% without a controlled background with small light adjustments.
1 Google Scholar 
2 CiteSeerX 
3 refSeek 
4 Scribd 
5 SlideShare 
6 PdfSR 
1 C. Harshith, R.S. Karthik, M. Ravindran, M.V.V.N.S Srikanth, N. Lakshmikhanth, “Survey on various gesture recognition Techniques for interfacing machines based on ambient intelligence”, International Journal of Computer Science & Engineering Survey (IJCSES) Vol.1, No.2, November, 2010
2 Q. Chen, N.D. Georganas, E.M. Petriu, “Real-time Vision-based Hand Gesture Recognition Using Haar-like Features”, Instrumentation and Measurement Technology Conference, 2007
3 W. T. Freeman and M. Roth, “Orientation histograms for hand gesture recognition”, IEEE Intl. Wkshp. on Automatic Face and Gesture Recognition, Zurich, June, 1995
4 M. Roth, K. Tanaka, C. ssman, W. Yerazunis, “Computer Vision for Interactive Computer Graphics”, IEEE Computer Graphics and Applications, May-June, 1998, pp. 42-53
5 S. Belongie, J. Malik, “Shape Matching and Object Recognition Using Shape Contexts”, IEEE Transactions on pattern analysis and machine intelligence, Vol.24, No.24, 2002
6 J. Flusser, “Moment Invariants in Image Analysis”, World Academy of Science, Engineering and Technology, 2005
7 N. Liu, B. C. Lovell, “Hand Gesture Extraction by Active Shape Models”, Digital Image Computing: Techniques and Applications, DICTA '05. Proceedings, 2005.
8 C. chang, J. chen, W. Tai and C. Han, “New Approach for Static Gesture Recognition”, Journal of information science and engineering, 2006
9 X. Zhang and Z. Tang, J. Yu, M. Guo, “A Fast Convex Hull Algorithm for Binary Image”, Informatica Oct2010, Vol. 34 Issue 3, pp.369, 2010
10 L. Y. Deng, J. C. Hung, H. Keh, K. Lin, Y. Liu, and N. Huang, “Real-time Hand Gesture Recognition by Shape Context Based Matching and Cost Matrix”, Journal of Networks, Vol. 6, No. 5, May 2011
11 E. Yörük, E. Konuko?glu, B. Sankur, “Shape-Based Hand Recognition”, IEEE transactions on image processing, vol. 15, no. 7, July 2006, 2006
12 Q. Chen, “Real-Time Vision-Based Hand Tracking and Gesture Recognition”, Doctoral Dissertation, University of Ottawa, 2008
13 Y. Fang, J. Cheng, J. Wang, K. Wang, J. Liu, H. Lu , “Hand Posture Recognition with CoTraining”, 19th International Conference on Pattern Recognition, 2008
14 G. Kukharev, A. Nowosielski, “Visitor Identification - Elaborating Real Time Face Recognition System”, WSCG Short Communication papers proceedings, 2004, pp. 157-164
15 X. Zabulisy, H. Baltzakisy, A. Argyroszy, “Vision-based Hand Gesture Recognition for Human-Computer Interaction”, World Academy of Science, Engineering and Technology, 2006
16 M.K. Hu, “Visual pattern recognition by moment invariants”, Information Theory, IRE Transactions, 1962, pp. 179-187
17 K.C.O. Rodriguez, G.C. Chavez, D. Menotti, “Hu and Zernike Moments for Sign Language Recognition”, Computing Department, Federal University of Ouro Preto, Brazil,
Dr. Matheesha Fernando
Department of Industrial Management, University of Kelaniya Sri Lanka - Sri Lanka
Dr. Janaka Indrajith Wijjayanayake
University of Kelaniya - Sri Lanka