Deaf Sign Interpreter Service
Keywords:
Deaf Sign Interpreter, Deep learning, template-matching algorithm, RCNNAbstract
Sign language is the way of communication for hearing impaired people. There is a challenge for common people to communicate with deaf people which makes this system helpful in assisting them. This paper aims at implementing computer vision which can take the sign from the users and convert them into text in real time. The proposed methodology contains four modules such as: image capturing, pre-processing classification and prediction. This system uses a camera, which captures various gestures of the hand. Next, the captured image is pre-processed, the edges are determined an edge detection algorithm. Finally, a template-matching algorithm identifies the sign and display the text. As the output is text, one can easily interpret the meaning of a particular sign. This also curtails the difficulty to communicate with the deaf. The system is implemented by using OpenCV-Python. The system uses various libraries and finally translates the sign gestures to text with accuracy.
References
- Sunitha K. A, Anitha Saraswathi.P, Aarthi.M, Jayapriya. K, Lingam Sunny, “Deaf Mute Communication Interpreter- A Review”, International Journal of Applied Engineering Research ,Volume 11, pp 290-296 , 2016.
- Mathavan Suresh Anand, Nagarajan Mohan Kumar, Angappan Kumaresan, “ An Efficient Framework for Indian SignLanguage Recognition Using Wavelet Transform” Circuits and Systems, Volume 7, pp 1874- 1883, 2016.
- Mandeep Kaur Ahuja, Amardeep Singh, “Hand Gesture Recognition Using PCA”, International Journal of Computer Science Engineering and Technology (IJCSET ), Volume 5, Issue 7, pp. 267-27, July 2015.
- Sagar P.More, Prof. Abdul Sattar, “Hand gesture recognition system for dumb people”,
- International Journal of Science and Research (IJSR)
- Chandandeep Kaur, Nivit Gill, “An Automated System for Indian Sign Language Recognition”, International Journal of Advanced Research in Computer Science and Software Engineering.
- Pratibha Pandey, Vinay Jain, “Hand Gesture Recognition for Sign Language Recognition: A Review”, International Journal of Science, Engineering and Technology Research (IJSETR), Volume 4, Issue 3, March 2015 .
- Nakul Nagpal,Dr. Arun Mitra.,Dr. Pankaj Agrawal, “Design Issue and Proposed Implementation of Communication Aid for Deaf & Dumb People”, International Journal on Recent and Innovation Trends in Computing and Communication ,Volume: 3 Issue: 5,pp- 147 – 149.
- Neelam K. Gilorkar, Manisha M. Ingle, “Real Time Detection And Recognition Of Indian And American Sign Language Using Sift”, International Journal of Electronics and Communication Engineering & Technology (IJECET), Volume 5, Issue 5, pp. 11-18 , May 2014
- Neelam K. Gilorkar, Manisha M. Ingle, “A Review on Feature Extraction for Indian and American Sign Language”, International Journal of Computer Science and Information Technologies, Volume 5 (1) , pp314-318, 2014.
- Ashish Sethi, Hemanth , Kuldeep Kumar,Bhaskara Rao ,Krishnan R, “Sign Pro-An Application Suite for Deaf and Dumb”, IJCSET , Volume 2, Issue 5, pp-1203-1206, May 2012.
- Priyanka Sharma,“Offline Signature Verification Using Surf Feature Extraction and Neural Networks Approach”, International Journal of Computer Science and Information Technologies, Volume 5 (3) , pp 3539-3541, 2014.
Downloads
Published
Issue
Section
License
Copyright (c) IJSRCSEIT
This work is licensed under a Creative Commons Attribution 4.0 International License.