Open Access Open Access  Restricted Access Subscription Access

Real Time Identification of American Sign Language for Deaf and Dumb Community

Snehal Pawar, Pragati Salunke, Arati Mhasavade, Aishwaraya Bhutkar, K. R. Pathak

Abstract


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.

Full Text:

PDF

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.


Refbacks

  • There are currently no refbacks.