Sign Language Recognition using Neural Networks
Sabaheta Ðogic, Günay Karlı · TEM Journal · 2014
Sign language plays a great role as communication media for people with hearing difficulties.In developed countries, systems are made for overcoming a problem in communication with deaf people.This encouraged us to develop a system for the Bosnian sign language since there is a need for such system.The work is done with the use of digital image processing methods providing a system that teaches a multilayer neural network using a back propagation algorithm.Images are processed by feature extraction methods, and by masking method the data set has been created.Training is done using cross validation method for better performance thus; an accuracy of 84% is achieved.