24-08-2013, 04:56 PM
Development of Indian Sign Language Recognition System
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Introduction
A sign language is a language which uses visually transmitted sign patterns to convey meaning by simultaneously combining hand shapes, orientation and movement of the hands, arms or body, and facial expressions to express/communicate with each others.
Sign language is commonly used by the physically impaired people who cannot speak and hear.
India is diversified in culture, language and religion. Since there is a large diversity among Indian languages, literature survey reports the non-existence of standard form of Indian Sign Language (ISL) gestures. ISL alphabets are derived from British Sign Language (BSL) and French Sign Language (FSL).
Issues in sign Language Recognition
Indian sign language uses both hands to represent each alphabet and gesture.
Sign language recognition is a multidisciplinary research area involving Pattern recognition, computer vision and natural language processing.
Few research works has been carried out in ISL recognition and interpretation using image processing/vision techniques. But those are only initial work tried with simple image processing techniques and are not dealt with real time data.
Objectives of the project
To develop an automatic sign language recognition system with the help of image processing and computer vision techniques.
To use natural image sequences, without the signer having to wear data gloves or colored gloves, and to be able to recognize hundreds of signs.
The motivation for this work is to provide a real time interface so that signers can easily and quickly communicate with non-signers.
To efficiently and accurately recognize signed words, from indian Sign Language, using a minimal number of training examples.
System description
Real-time processing: -The translator is sufficiently fast to capture images of signer, process the images and display the sign translation on the computer screen.
A camera sensor is needed in order to capture the features/ gestures of the signer.
Development of the sign recognition system.
System Description
NEURAL NETWORK
The performance of the recognition system is evaluated by testing its ability to classify signs for both training and testing set of data. The effect of the number of inputs to the neural network is considered.
Plan of action
Study about the automatic sign language recognition system
Block diagram representation of the proposed ISL recognition
Collection of ISL database.
Simulation of ISL recognition system using MATLAB.
Testing the developed sign language recognition system
Creation of GUI design for user interface.
Real time implementation of ISL recognition system.