Real-time hand gesture recognition for embedded system / Farah Farhana Mod Ma'asum, Suhana Sulaiman and Azilah Saparon

A system with low-cost hardware computer webcam as the replacement of mouse click is being applied in this research. In order to capture good image of hand in vision based system, various segmentation techniques proposed by other researchers are combined and tested to enhance the quality of seg...

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Main Authors: Mod Ma'asum, Farah Farhana, Sulaiman, Suhana, Saparon, Azilah
Format: Article
Language:English
Published: UiTM Press 2018
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Online Access:https://ir.uitm.edu.my/id/eprint/63045/1/63045.pdf
https://ir.uitm.edu.my/id/eprint/63045/
https://jeesr.uitm.edu.my/v1/
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Institution: Universiti Teknologi Mara
Language: English
id my.uitm.ir.63045
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spelling my.uitm.ir.630452022-06-29T03:11:26Z https://ir.uitm.edu.my/id/eprint/63045/ Real-time hand gesture recognition for embedded system / Farah Farhana Mod Ma'asum, Suhana Sulaiman and Azilah Saparon Mod Ma'asum, Farah Farhana Sulaiman, Suhana Saparon, Azilah Pattern recognition systems A system with low-cost hardware computer webcam as the replacement of mouse click is being applied in this research. In order to capture good image of hand in vision based system, various segmentation techniques proposed by other researchers are combined and tested to enhance the quality of segmentation image. Canny edges and Otsu threshold technique are used to segment the hand image while convex hull and convexity defects algorithm are used to extract the image of hand features. Embedded hardware (Arduino) board is employed for validating the signal sent using hand gesture to replace LEFT CLICK, RIGHT CLICK, MOVE cursors. An experiment is set up to determine the accuracy in percentage of this work with ten test subjects. They were prearranged for five minutes to become familiar with the hand tracking system after the initial attempt. The findings revealed that users are better trained in the second trial after five minutes training. The results significantly improved from 33.3 % to 52.6 % for LEFT CLICK, 46.7% to 61 % improvement for RIGHT CLICK while 56.7% to 77.3% for MOVE cursor. UiTM Press 2018-06 Article PeerReviewed text en https://ir.uitm.edu.my/id/eprint/63045/1/63045.pdf Real-time hand gesture recognition for embedded system / Farah Farhana Mod Ma'asum, Suhana Sulaiman and Azilah Saparon. (2018) Journal of Electrical and Electronic Systems Research (JEESR), 12: 8. pp. 51-57. ISSN 1985-5389 https://jeesr.uitm.edu.my/v1/
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
topic Pattern recognition systems
spellingShingle Pattern recognition systems
Mod Ma'asum, Farah Farhana
Sulaiman, Suhana
Saparon, Azilah
Real-time hand gesture recognition for embedded system / Farah Farhana Mod Ma'asum, Suhana Sulaiman and Azilah Saparon
description A system with low-cost hardware computer webcam as the replacement of mouse click is being applied in this research. In order to capture good image of hand in vision based system, various segmentation techniques proposed by other researchers are combined and tested to enhance the quality of segmentation image. Canny edges and Otsu threshold technique are used to segment the hand image while convex hull and convexity defects algorithm are used to extract the image of hand features. Embedded hardware (Arduino) board is employed for validating the signal sent using hand gesture to replace LEFT CLICK, RIGHT CLICK, MOVE cursors. An experiment is set up to determine the accuracy in percentage of this work with ten test subjects. They were prearranged for five minutes to become familiar with the hand tracking system after the initial attempt. The findings revealed that users are better trained in the second trial after five minutes training. The results significantly improved from 33.3 % to 52.6 % for LEFT CLICK, 46.7% to 61 % improvement for RIGHT CLICK while 56.7% to 77.3% for MOVE cursor.
format Article
author Mod Ma'asum, Farah Farhana
Sulaiman, Suhana
Saparon, Azilah
author_facet Mod Ma'asum, Farah Farhana
Sulaiman, Suhana
Saparon, Azilah
author_sort Mod Ma'asum, Farah Farhana
title Real-time hand gesture recognition for embedded system / Farah Farhana Mod Ma'asum, Suhana Sulaiman and Azilah Saparon
title_short Real-time hand gesture recognition for embedded system / Farah Farhana Mod Ma'asum, Suhana Sulaiman and Azilah Saparon
title_full Real-time hand gesture recognition for embedded system / Farah Farhana Mod Ma'asum, Suhana Sulaiman and Azilah Saparon
title_fullStr Real-time hand gesture recognition for embedded system / Farah Farhana Mod Ma'asum, Suhana Sulaiman and Azilah Saparon
title_full_unstemmed Real-time hand gesture recognition for embedded system / Farah Farhana Mod Ma'asum, Suhana Sulaiman and Azilah Saparon
title_sort real-time hand gesture recognition for embedded system / farah farhana mod ma'asum, suhana sulaiman and azilah saparon
publisher UiTM Press
publishDate 2018
url https://ir.uitm.edu.my/id/eprint/63045/1/63045.pdf
https://ir.uitm.edu.my/id/eprint/63045/
https://jeesr.uitm.edu.my/v1/
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