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Implementation of A Dynamic Gesture Recognition Based Indian Sign Language

Pushpendra Patel*, Sandeep B. Patil**

* PG Student, Department of Electronics and Communication Engineering, Shri Shankaracharya Technical Campus of Engineering and Technology, Bhilai, India.

** Associate Professor, Department of Electrical and Electronics Engineering, Shri Shankaracharya College of Engineering and Technology, Bhilai, India.

Periodicity:September - November'2016
DOI : https://doi.org/10.26634/jpr.3.3.12404

Abstract

In this proposed work, the authors have designed a structure for the accurate hand gesture recognition using MATLAB. Computation based hand classifier is recommended for the dynamic gesture recognition. Now-a-days, it provides platform for those people who are unable to communicate like a normal person. The Principal Component Analysis based algorithm is capable of doing this work. This is done by creating an invariant subspace, which creates a vocabulary in such a manner that any abnormal person can learn and express himself easily. For doing so, using the movement of hands, its shape and position are obtained as an information which can be recognized for the gesture recognition. One of the methods is Hidden Markov Models (HMMs) capable of recognizing these combinations.

Keywords

Indian Sign Language, DWT, Computer Vision, HMMs, Gesture Recognition

How to Cite this Article?

Patel, P., and Patil, S. B. (2016). Implementation Of A Dynamic Gesture Recognition Based Indian Sign Language. . i-manager’s Journal on Pattern Recognition, 3(3), 1-6. https://doi.org/10.26634/jpr.3.3.12404

References

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