Author : Abdelmoty M.Ahmed
Affiliation : Faculty of Engineering /Al-Azhar University
Country : Egypt
Category : Computer Science & Information Technology
Volume, Issue,
Month, Year
: 6, 5, November, 2016
ABSTRACT
Sign
language continues to be the preferred tool of communication between the deaf
and the hearing-impaired. It is a well-structured code by hand gesture, where
every gesture has a specific meaning, In this paper has goal to develop a
system for automatic translation of Arabic Sign Language. To Arabic Text
(ATASAT) System this system is acts as a translator among deaf and dumb with
normal people to enhance their communication, the proposed System consists of
five main stages Video and Images capture, Video and images processing, Hand
Signs Construction, Classification finally Text transformation and
interpretation, this system depends on building a two datasets image features
for Arabic sign language gestures alphabets from two resources: Arabic Sign
Language dictionary and gestures from different signer's human, also using
gesture recognition techniques, which allows the user to interact with the
outside world. This system offers a novel technique of hand detection is
proposed which detect and extract hand gestures of Arabic Sign from Image or
video, in this paper we use a set of appropriate features in step hand sign
construction and classification of based on different classification algorithms
such as KNN, MLP, C4.5, VFI and SMO and compare these results to get better
classifier.
Keyword : Sign language, Hand Gesture, Hand Signs
Construction, gesture recognition, hand detection
For More Details : https://airccj.org/CSCP/vol6/csit65211.pdf
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