A system to recognize static gestures representing the words has been placed onto the system. The recognition of handmade gestures in certain sequence of image enables a human-computer interaction applications. Human Computer Interaction moves forward in the field of sign language interpretation. Indian Sign Language (ISL) Interpretation system is a good way to help the Indian hearing impaired people to interact with normal people with the help of computer. Vision based hand gesture recognition system have been discussed as hand plays vital communication mode. This work consist of three phases. First phase is pre-processing, in which images are processed through some steps such as reducing distortion and greyscale conversion. Greyscale image is taken so that it shapes and then descriptors can be applied easily to extract the required features.
 Aleem Khalid Alvi, M. Yousuf Bin Azhar, Mehmood Usman, Suleman Mumtaz, Sameer Rafiq, Razi Ur Rehman, Israr Ahmed T , ―Pakistan Sign Language Recognition Using Statistical Template Matching,‖ World Academy of Science, Engineering and Technology, 2005.  Byung-woo min, Ho-sub yoon, Jung soh, Takeshi ohashi and Toshiaki jima, ―Visual Recognition of Static/Dynamic Gesture: Gesture-Driven Editing System,‖ Journal of Visual Languages & Computing Volume10,Issue3, June 1999, Pages 291-309.  U. Zeshan, ― ‗A‘ level Introductory course in INDIAN SIGN LANGUAGE‖, Ali Yavar Jung National Institute for Hearing Handicapped, Mumbai, 2001, pp. 1-38.  P. Garg, N. Agrawal, S. Sofat, ―Vision based Hand Gesture Recognition‖, Proceedings of world Academy of Science, Engineering and Technology, Vol.37, 2009, pp. 1024-1029.  U. Zeshan, M. Vasishta, M. Sethna, ―Implementation of Indian Sign Language in Educational Setting‖, Asia pacific Disability Rehabilitation Journal,Vo.16, No.1, 2005, pp. 16-39  G. R. S. Murthy and R. S. Jadon, “A review of vision based hand gestures recognition”, International Journal of Information Technology and Knowledge Management, Vol. 2 (2), 405-410, 2009  sq Feng-Sheng Chen, Chih-Ming Fu and Chung-Lin Huang, “Hand gesture recognition using a real-time tracking method and hidden Markov model”, Image and Vision Computing, Vol. 21, 745–758, 2003.  Jeroen F. Lichtenauer, Emile A. Hendriks, and Marcel J.T. Reinders, “Sign Language Recognition by Combining Statistical DTW and Independent Classification”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 30 (11), 2040-2046, 2008.  C. Vogler and D. Metaxas, ―A Framework for Recognizing the Simultaneous Aspects of American Sign Language‖, Computer Vision and Image Understanding, 2001, vol. 81, no. 3, pp. 358-384  W. Gao, G. Fang , D. Zhao, and Y. Chen, ―Transition Movement Models for Large Vocabulary Continuous Sign Language Recognition,‖ Proc. Sixth IEEE Int‘l Conf. Automatic Face and Gesture Recognition, May 2004,pp. 553-55.
Hand Posture, Vector Classification, Pattern Matching, HGR, Machine Learning.