Indian Journal of Science and Technology
DOI: 10.17485/ijst/2016/v9i16/87950
Year: 2016, Volume: 9, Issue: 16, Pages: 1-5
Original Article
P. Kanchana Devi1 , A. Raji1 * and G. Srinivasan2
1Department of CSE, Mepco Schlenk Engineering College, Sivakasi - 626005, Tamil Nadu, India; [email protected], [email protected] 2Department of CSE, Kamaraj College of Engineering and Technology, Virudhunagar - 626001, Tamil Nadu, India; [email protected]
*Author of Corresponding: A. Raji Department of CSE, Mepco Schlenk Engineering College, Sivakasi - 626005, Tamil Nadu, India; [email protected]
Objectives: The sign language is very important for hearing impiared people. Finding an educated translator for the sign language every time and everywhere is difficult task. The human-computer interaction system is helpful for dumb people to overcome the difficulty, besides it and can be installed anywhere. This paper proposes the method or algorithm for an application which would help in recognizing the different signs and convert those sign gestures into voice. Methods: Different sets of hand gestures were captured using web camera and then stored in a directory. The correct signs by the user is identified by using feature extraction techniques and neural network algorithm. Findings: The sign languages for different numbers in words are trained and tested. The test image is aligned correctly with training images which is based on correlation and convert the matched image into text and then text into voice. Applications: By using this system, hearing impaired people can easily interact without depending on translators.
Keywords: Deaf and Mute, Human-Computer Interaction, Hand Gestures, Neural Network, Sign Language
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