A phoneme based sign language recognition system using interleaving feature and neural network
International Conference on Man Machine Systems (ICoMMS 2012) organized by School of Mechatronic Engineering, co-organized by The Institute of Engineer, Malaysia (IEM) and Society of Engineering Education Malaysia, 27th - 28th February 2012 at Bayview Beach Resort, Penang, Malaysia.
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| Language: | English |
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Universiti Malaysia Perlis (UniMAP)
2012
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| Online Access: | http://dspace.unimap.edu.my/xmlui/handle/123456789/20456 |
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my.unimap-204562012-07-19T09:10:44Z A phoneme based sign language recognition system using interleaving feature and neural network Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr. Sazali, Yaacob, Prof. Dr. Mohd Shuhanaz, Zanar Azalan Palaniappan, Rajkumar paul@unimap.edu.my s.yaacob@unimap.edu.my Sign language recognition Hand gesture Interleaving feature International Conference on Man Machine Systems (ICoMMS 2012) organized by School of Mechatronic Engineering, co-organized by The Institute of Engineer, Malaysia (IEM) and Society of Engineering Education Malaysia, 27th - 28th February 2012 at Bayview Beach Resort, Penang, Malaysia. A sign language is a language which, instead of acoustically conveyed sound patterns, uses visually transmitted sign patterns. Sign languages are commonly developed in hearing impaired communities, which can include interpreters, friends and families of deaf people as well as people who are deaf or hard of hearing themselves. 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 Neural Network. A simple segmentation process is carried out to separate the right and left hand regions from the image frame and in the preprocessing stage the vertical interleaving method is used to reduce the size of the image. The 2D moment of the right and left hand interleaved image is obtained as features. Using the interleaved 2D-moment features, a simple neural network model was developed. The system has been implemented and tested for its validity. Experimental results show that the system has a recognition rate of 91.12%. 2012-07-19T09:10:44Z 2012-07-19T09:10:44Z 2012-02-27 Working Paper http://hdl.handle.net/123456789/20456 en Proceedings of the International Conference on Man-Machine Systems (ICoMMS 2012) Universiti Malaysia Perlis (UniMAP) School of Mechatronic Engineering |
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Malaysia |
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Universiti Malaysia Perlis |
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http://dspace.unimap.edu.my/ |
| language |
English |
| topic |
Sign language recognition Hand gesture Interleaving feature |
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Sign language recognition Hand gesture Interleaving feature Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr. Sazali, Yaacob, Prof. Dr. Mohd Shuhanaz, Zanar Azalan Palaniappan, Rajkumar A phoneme based sign language recognition system using interleaving feature and neural network |
| description |
International Conference on Man Machine Systems (ICoMMS 2012) organized by School of Mechatronic Engineering, co-organized by The Institute of Engineer, Malaysia (IEM) and Society of Engineering Education Malaysia, 27th - 28th February 2012 at Bayview Beach Resort, Penang, Malaysia. |
| author2 |
paul@unimap.edu.my |
| author_facet |
paul@unimap.edu.my Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr. Sazali, Yaacob, Prof. Dr. Mohd Shuhanaz, Zanar Azalan Palaniappan, Rajkumar |
| format |
Working Paper |
| author |
Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr. Sazali, Yaacob, Prof. Dr. Mohd Shuhanaz, Zanar Azalan Palaniappan, Rajkumar |
| author_sort |
Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr. |
| title |
A phoneme based sign language recognition system using interleaving feature and neural network |
| title_short |
A phoneme based sign language recognition system using interleaving feature and neural network |
| title_full |
A phoneme based sign language recognition system using interleaving feature and neural network |
| title_fullStr |
A phoneme based sign language recognition system using interleaving feature and neural network |
| title_full_unstemmed |
A phoneme based sign language recognition system using interleaving feature and neural network |
| title_sort |
phoneme based sign language recognition system using interleaving feature and neural network |
| publisher |
Universiti Malaysia Perlis (UniMAP) |
| publishDate |
2012 |
| url |
http://dspace.unimap.edu.my/xmlui/handle/123456789/20456 |
| _version_ |
1643793079149264896 |