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Gesture recognition system for Kod Tangan Bahasa Melayu (KTBM) using neural network

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Main Authors: Paulraj, Murugesa Pandiyan, Prof. Dr., Sazali, Yaacob, Prof. Dr., Hazry, Desa, Assoc. Prof. Dr., Wan Mohd Ridzuan, Wan Ab Majid
Other Authors: paul@unimap.edu.my.
Format: Working Paper
Language:English
Published: IEEE Conference Publications 2014
Subjects:
Sign language recognition
Head and hand gestures
Discrete Cosine Transform (DCT)
Neural network
Online Access:http://dspace.unimap.edu.my:80/dspace/handle/123456789/33703
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spelling my.unimap-337032017-11-29T05:04:03Z Gesture recognition system for Kod Tangan Bahasa Melayu (KTBM) using neural network Paulraj, Murugesa Pandiyan, Prof. Dr. Sazali, Yaacob, Prof. Dr. Hazry, Desa, Assoc. Prof. Dr. Wan Mohd Ridzuan, Wan Ab Majid paul@unimap.edu.my. s.yaacob@unimap.edu.my hazry@unimap.edu.my Sign language recognition Head and hand gestures Discrete Cosine Transform (DCT) Neural network Link to publisher's homepage at http://ieeexplore.ieee.org/ This paper presents simple methods for translating Kod Tangan Bahasa Melayu (KTBM) into voice signal based on subject head and two hand gestures. Different gesture signs made by different subjects are captured using a USB web camera in RGB video stream format with a screen bit depth of 24 bits and a resolution of 320 X 240 pixels. The recorded video of the sign language is divided into number of image frames. Using a simple segmentation technique, the frame image is segmented into three region namely, head region, left hand region and right hand region. After performing the image segmentation, the image frames are converted into binary image format. A simple feature extraction method is then applied and the variations of the features in the subsequent frame are modeled using Discrete Cosine Transform (DCT). The features extracted are associated to the equivalent voice sound and a simple neural network model trained by error prob method is developed. An audio system is used to play the equivalent voice signal from the recognized sign language. Experimental results demonstrate that the recognition rate of the proposed neural network models is about 81.07%. 2014-04-15T04:02:40Z 2014-04-15T04:02:40Z 2009 Working Paper 5th International Colloquium on Signal Processing & Its Applications, 2009, pages 19-22 978-1-4244-4151-8 http://dspace.unimap.edu.my:80/dspace/handle/123456789/33703 http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=5069179&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D5069179 http://dx.doi.org/10.1109/CSPA.2009.5069179 en IEEE Conference Publications
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
Head and hand gestures
Discrete Cosine Transform (DCT)
Neural network
spellingShingle Sign language recognition
Head and hand gestures
Discrete Cosine Transform (DCT)
Neural network
Paulraj, Murugesa Pandiyan, Prof. Dr.
Sazali, Yaacob, Prof. Dr.
Hazry, Desa, Assoc. Prof. Dr.
Wan Mohd Ridzuan, Wan Ab Majid
Gesture recognition system for Kod Tangan Bahasa Melayu (KTBM) using neural network
description Link to publisher's homepage at http://ieeexplore.ieee.org/
author2 paul@unimap.edu.my.
author_facet paul@unimap.edu.my.
Paulraj, Murugesa Pandiyan, Prof. Dr.
Sazali, Yaacob, Prof. Dr.
Hazry, Desa, Assoc. Prof. Dr.
Wan Mohd Ridzuan, Wan Ab Majid
format Working Paper
author Paulraj, Murugesa Pandiyan, Prof. Dr.
Sazali, Yaacob, Prof. Dr.
Hazry, Desa, Assoc. Prof. Dr.
Wan Mohd Ridzuan, Wan Ab Majid
author_sort Paulraj, Murugesa Pandiyan, Prof. Dr.
title Gesture recognition system for Kod Tangan Bahasa Melayu (KTBM) using neural network
title_short Gesture recognition system for Kod Tangan Bahasa Melayu (KTBM) using neural network
title_full Gesture recognition system for Kod Tangan Bahasa Melayu (KTBM) using neural network
title_fullStr Gesture recognition system for Kod Tangan Bahasa Melayu (KTBM) using neural network
title_full_unstemmed Gesture recognition system for Kod Tangan Bahasa Melayu (KTBM) using neural network
title_sort gesture recognition system for kod tangan bahasa melayu (ktbm) using neural network
publisher IEEE Conference Publications
publishDate 2014
url http://dspace.unimap.edu.my:80/dspace/handle/123456789/33703
_version_ 1643802749799759872
score 13.222552

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