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Recognition of Two-handed Arabic Signs using the CyberGlove

Authors:
Mohamed Mohandes

Keywords: Arabic sign language; recognition; support vector machine; principle component analysis.

Abstract:
Abstract--Sign language maps letters, words, and expressions of a certain language to a set of hand gestures enabling an individual to communicate by using hands and gestures rather than by speaking. Systems capable of recognizing sign-language symbols can be used as a means of communication between hearing-impaired and vocal people. This paper represents the first attempt to recognize two-handed signs from the Unified Arabic Sign Language Dictionary using the CyberGlove and support vector machines. Principal Component Analysis is used for feature extraction. 20 samples of each of 100 two-handed signs were collected from an adult signer. 15 samples of each sign were used for training a Support Vector Machine to perform the recognition. The performance is obtained by testing the trained system on the remaining 5 samples of each sign. A recognition rate of 99.6% on the testing data was obtained. When more signs will be considered, the support vector machine algorithm must be parallelized so that signs are recognized on real time.

Pages: 124 to 129

Copyright: Copyright (c) IARIA, 2010

Publication date: October 25, 2010

Published in: conference

ISSN: 2308-4499

ISBN: 978-1-61208-101-4

Location: Florence, Italy

Dates: from October 25, 2010 to October 30, 2010