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A simple sign language recognition system using affine moment blur invariant features

International Postgraduate Conference On Engineering (IPCE 2010), 16th - 17th October 2010 organized by Centre for Graduate Studies, Universiti Malaysia Perlis (UniMAP) at School of Mechatronic Engineering, Pauh Putra Campus, Perlis, Malaysia.

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Bibliographic Details
Main Authors: Rajkumar, Palaniappan, Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr., Sazali, Yaacob, Prof. Dr., Mohd Shuhanaz, Zanar Azalan
Other Authors: prkmect@gmail.com
Format: Working Paper
Language:English
Published: Universiti Malaysia Perlis (UniMAP) 2012
Subjects:
Sign language recognition
Hand gesture
Affine Moment Blur invariants
Online Access:http://dspace.unimap.edu.my/xmlui/handle/123456789/21620
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spelling my.unimap-216202012-11-05T08:58:01Z A simple sign language recognition system using affine moment blur invariant features Rajkumar, Palaniappan Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr. Sazali, Yaacob, Prof. Dr. Mohd Shuhanaz, Zanar Azalan prkmect@gmail.com Sign language recognition Hand gesture Affine Moment Blur invariants International Postgraduate Conference On Engineering (IPCE 2010), 16th - 17th October 2010 organized by Centre for Graduate Studies, Universiti Malaysia Perlis (UniMAP) at School of Mechatronic Engineering, Pauh Putra Campus, Perlis, Malaysia. Sign language recognition is one of the most promising sub-fields in gesture recognition research. Effective sign language recognition would grant the deaf and hard-of-hearing expanded tools for communicating with both other people and machines. Hand gesture is one of the typical methods used in sign language for non-verbal communication. It is most commonly used by people who have hearing or speech problems to communicate among themselves or with normal people. Developing a sign language recognition system will help the hearing impaired to communicate more fluently with the normal people. This paper presents a simple sign language recognition system that has been developed using skin color segmentation and Artificial Neural Network. The Affine Moment Blur invariants extracted from the right and left hand gesture images are used as feature vector to develop a network model. The system has been implemented and tested for its validity. Experimental results show that the recognition rate is 97.19%. 2012-11-05T08:58:01Z 2012-11-05T08:58:01Z 2010-10-16 Working Paper 978-967-5760-03-7 http://hdl.handle.net/123456789/21620 en Proceedings of the International Postgraduate Conference on Engineering (IPCE 2010) Universiti Malaysia Perlis (UniMAP) Centre for Graduate Studies
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Sign language recognition
Hand gesture
Affine Moment Blur invariants
spellingShingle Sign language recognition
Hand gesture
Affine Moment Blur invariants
Rajkumar, Palaniappan
Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr.
Sazali, Yaacob, Prof. Dr.
Mohd Shuhanaz, Zanar Azalan
A simple sign language recognition system using affine moment blur invariant features
description International Postgraduate Conference On Engineering (IPCE 2010), 16th - 17th October 2010 organized by Centre for Graduate Studies, Universiti Malaysia Perlis (UniMAP) at School of Mechatronic Engineering, Pauh Putra Campus, Perlis, Malaysia.
author2 prkmect@gmail.com
author_facet prkmect@gmail.com
Rajkumar, Palaniappan
Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr.
Sazali, Yaacob, Prof. Dr.
Mohd Shuhanaz, Zanar Azalan
format Working Paper
author Rajkumar, Palaniappan
Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr.
Sazali, Yaacob, Prof. Dr.
Mohd Shuhanaz, Zanar Azalan
author_sort Rajkumar, Palaniappan
title A simple sign language recognition system using affine moment blur invariant features
title_short A simple sign language recognition system using affine moment blur invariant features
title_full A simple sign language recognition system using affine moment blur invariant features
title_fullStr A simple sign language recognition system using affine moment blur invariant features
title_full_unstemmed A simple sign language recognition system using affine moment blur invariant features
title_sort simple sign language recognition system using affine moment blur invariant features
publisher Universiti Malaysia Perlis (UniMAP)
publishDate 2012
url http://dspace.unimap.edu.my/xmlui/handle/123456789/21620
_version_ 1643793415626817536
score 13.214268

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