Extraction of head and hand gesture features for recognition of sign language
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IEEE Conference Publications
2014
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my.unimap-337002017-11-29T06:46:51Z Extraction of head and hand gesture features for recognition of sign language Paulraj, M. P. Sazali, Yaacob, Prof. Dr. Hazry, Desa, Assoc. Prof. Dr. Hema, Chengalvarayan Radhakrishnamurthy Wan Mohd Ridzuan, Wan Ab Majid wgengg@gmail.com s.yaacob@unimap.edu.my hazry@unimap.edu.my Gesture recognition Sign language recognition Sign languages Hand gestures Link to publisher's homepage at http://ieeexplore.ieee.org/ Sign language is the primary communication method that impaired hearing people used in their daily life. Sign language recognition has gained a lot of attention recently by researchers in computer vision. Sign language recognition systems in general require the knowledge of the hand's position, shape, motion, orientation and facial expression. In this paper we present a simple method for converting sign language into voice signals using features obtained from head and hand gestures which can be used by hearing impaired person to communicate with an ordinary person. A simple feature extraction method based on the area of the objects in a binary image and Discrete Cosine Transform (DCT) is proposed for extracting the features from the video sign language. A simple neural network models is developed for the recognition of gestures using the features computed from the video stream. An audio system is installed to play the particular word corresponding to the gestures. Experimental results demonstrate that the recognition rate of the proposed neural network models is about 91%. 2014-04-15T01:23:04Z 2014-04-15T01:23:04Z 2008 Working Paper International Conference on Electronic Design, 2008, pages 1-6 978-1-4244-2315-6 http://dspace.unimap.edu.my:80/dspace/handle/123456789/33700 http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4786633&tag=1 http://dx.doi.org/10.1109/ICED.2008.4786633 en IEEE Conference Publications |
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Universiti Malaysia Perlis |
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Asia |
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Malaysia |
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Universiti Malaysia Perlis |
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http://dspace.unimap.edu.my/ |
| language |
English |
| topic |
Gesture recognition Sign language recognition Sign languages Hand gestures |
| spellingShingle |
Gesture recognition Sign language recognition Sign languages Hand gestures Paulraj, M. P. Sazali, Yaacob, Prof. Dr. Hazry, Desa, Assoc. Prof. Dr. Hema, Chengalvarayan Radhakrishnamurthy Wan Mohd Ridzuan, Wan Ab Majid Extraction of head and hand gesture features for recognition of sign language |
| description |
Link to publisher's homepage at http://ieeexplore.ieee.org/ |
| author2 |
wgengg@gmail.com |
| author_facet |
wgengg@gmail.com Paulraj, M. P. Sazali, Yaacob, Prof. Dr. Hazry, Desa, Assoc. Prof. Dr. Hema, Chengalvarayan Radhakrishnamurthy Wan Mohd Ridzuan, Wan Ab Majid |
| format |
Working Paper |
| author |
Paulraj, M. P. Sazali, Yaacob, Prof. Dr. Hazry, Desa, Assoc. Prof. Dr. Hema, Chengalvarayan Radhakrishnamurthy Wan Mohd Ridzuan, Wan Ab Majid |
| author_sort |
Paulraj, M. P. |
| title |
Extraction of head and hand gesture features for recognition of sign language |
| title_short |
Extraction of head and hand gesture features for recognition of sign language |
| title_full |
Extraction of head and hand gesture features for recognition of sign language |
| title_fullStr |
Extraction of head and hand gesture features for recognition of sign language |
| title_full_unstemmed |
Extraction of head and hand gesture features for recognition of sign language |
| title_sort |
extraction of head and hand gesture features for recognition of sign language |
| publisher |
IEEE Conference Publications |
| publishDate |
2014 |
| url |
http://dspace.unimap.edu.my:80/dspace/handle/123456789/33700 |
| _version_ |
1643802749204168704 |
| score |
13.214268 |