Real Time Identification of American Sign Language for Deaf and Dumb Community
- 1. Student, Department of Computer Science, Rajgad Dnyanpeeth Technical Campus Dhangawadi, Pune, India.
- 2. Assistant Professor, Department of Computer Science, Rajgad Dnyanpeeth Technical Campus Dhangawadi, Pune, India.
Description
The only way for deaf and dumb for communication is based on sign language which involves hand gestures. In this system, we are working on the American Sign Language (ASL) dataset (A-Z), (0-9) and word alphabet identification escort by our word identification dataset of Indian Sign Language (ISL). Sign data samples to be making our system more faultless, error free, and unambiguous with help of Convolutional Neural Network (CNN). Today, much research has been going on the field of sign language recognition but existing study failed to develop trust full communication interpreter. The motivation of this system is to serve a real-time two-way communication translator based on Indian Sign Language (ISL) with higher precision, efficiency, and accuracy. Indian Sign Language (ISL) used by Deaf-mute people’s community in India, does have adequate, delightful, acceptable, meaningful essential and structural properties.
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Real Time Identification of American Sign Language -HBRP Publication.pdf
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Additional details
References
- Sharmila Konwar, Sagarika Borah and Dr. T. Tuithung, "An American sign language detection system using HSV color model and edge detection", International Conference on Communication and Signal Processing, IEEE, April 3-5, 2014, India
- Yo-Jen Tu, Chung-Chieh Kao, Huei- Yung Lin, "Human Computer Interaction Using Face and Gesture Recognition", Signal and Information Processing Association Annual Summit and Conference (APSIPA), 2013 Asia-Pacific, IEEE, Kaohsiung.
- Angur M. Jarman, Samiul Arshad, Nashid Alam and Mohammed J.Islam, "An automated Bengali sign language recognition based on fingertip finder Algorithm", International journal of Electronics & Informatics, 2015.
- Javeria Farooq and Muhaddisa Barat Ali, "Real time hand gesture recognition for computer interaction", International Conference on Robotics and Emerging Allied Technologies in Engineering (ICREATE), 22-24 April, 2014.
- Guillaume Plouffe and Ana-Maria Cretu, "Static and dynamic hand gesture recognition system in depth data using dynamic time warping" IEEE Transactions on Instrumentation and Measurement.2016.65(2).
- ZAFAR AHMED ANSARI, "Nearest neighbour classification of Indian sign language gestures using kinect camera" , February 2016.41(2):161– 182p
- Keerthi S Warrier, "Software based sign language converter", April 2016 IEEE.
Subjects
- Computer Science Engineering
- http://hbrppublication.com/journals.html