Publication Type:

Conference Paper

Source:

2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI), IEEE, Udupi, India (2017)

URL:

https://ieeexplore.ieee.org/abstract/document/8126001

Keywords:

background subtraction, Histogram comparison, Indian sign language, ORB, Thresholding

Abstract:

The communication barrier of deaf and dumb community with the society still remains a matter of concern due to lack of perfect sign language translators. Usage of mobile phones for communication remains a dream for deaf and dumb community. We propose an android application that converts sign language to natural language and enable deaf and dumb community to talk over mobile phones. Developing Sign Recognition methods for mobile applications has challenges like need for light weight method with less CPU and memory utilization. The application captures image using device camera process it and determines the corresponding gesture. An initial phase of comparison using histogram matching is done to identify those gestures that are close to test sample and further only those samples are subjected to Oriented Fast and Rotated BRIEF(Binary Robust Independent Element Features) based comparison hence reducing the CPU time. The user of the application can also add new gestures into the dataset. The application allows easy communication of deaf and dumb with society. Though there are many computer based applications for sign language recognition, development in android platform is adequately less.

Cite this Research Publication

M. Mahesh, Jayaprakash, A., and M. Geetha, “Sign language translator for mobile platforms”, in 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI), Udupi, India, 2017.