Hand gesture recognition for human-robot interaction

This project proposes an image segmentation method that improves the recognition rate of vision-based hand gesture recognition system on low-resolution images and occluded hand gestures. The solution is based on the idea that random walker-based segmentation could provide high quality segmentation d...

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Bibliographic Details
Main Author:	Tan, Ann Nie
Format:	Thesis
Language:	English
Published:	2020
Subjects:	TK Electrical engineering Electronics Nuclear engineering
Online Access:	http://eprints.utm.my/id/eprint/93019/1/TanAnnNieMSKE2020.pdf
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id	my-utm-ep.93019
record_format	uketd_dc
spelling	my-utm-ep.930192021-11-07T06:00:29Z Hand gesture recognition for human-robot interaction 2020 Tan, Ann Nie TK Electrical engineering. Electronics Nuclear engineering This project proposes an image segmentation method that improves the recognition rate of vision-based hand gesture recognition system on low-resolution images and occluded hand gestures. The solution is based on the idea that random walker-based segmentation could provide high quality segmentation despite weak object boundaries. The approach has several notable merits, namely high segmentation accuracy, fast editing and computation. A comprehensive verification using Matlab is carried out to determine the effectiveness of random walker method in segmenting occluded hand gesture images. The segmented images are then classified by artificial neural network and its performance is evaluated in terms of recognition rate and time. The result confirms that the proposed method is performs better than color-based segmentation, that is 5% higher recognition rate for the same dataset. The method proposed in this project can be integrated in vision-based recognition systems to widen the vocabulary of hand gestures recognition systems, recognizing both gestures with finger gaps as well as occluded gestures. 2020 Thesis http://eprints.utm.my/id/eprint/93019/ http://eprints.utm.my/id/eprint/93019/1/TanAnnNieMSKE2020.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:135860 masters Universiti Teknologi Malaysia, Faculty of Engineering - School of Electrical Engineering Faculty of Engineering - School of Electrical Engineering
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	TK Electrical engineering Electronics Nuclear engineering
spellingShingle	TK Electrical engineering Electronics Nuclear engineering Tan, Ann Nie Hand gesture recognition for human-robot interaction
description	This project proposes an image segmentation method that improves the recognition rate of vision-based hand gesture recognition system on low-resolution images and occluded hand gestures. The solution is based on the idea that random walker-based segmentation could provide high quality segmentation despite weak object boundaries. The approach has several notable merits, namely high segmentation accuracy, fast editing and computation. A comprehensive verification using Matlab is carried out to determine the effectiveness of random walker method in segmenting occluded hand gesture images. The segmented images are then classified by artificial neural network and its performance is evaluated in terms of recognition rate and time. The result confirms that the proposed method is performs better than color-based segmentation, that is 5% higher recognition rate for the same dataset. The method proposed in this project can be integrated in vision-based recognition systems to widen the vocabulary of hand gestures recognition systems, recognizing both gestures with finger gaps as well as occluded gestures.
format	Thesis
qualification_level	Master's degree
author	Tan, Ann Nie
author_facet	Tan, Ann Nie
author_sort	Tan, Ann Nie
title	Hand gesture recognition for human-robot interaction
title_short	Hand gesture recognition for human-robot interaction
title_full	Hand gesture recognition for human-robot interaction
title_fullStr	Hand gesture recognition for human-robot interaction
title_full_unstemmed	Hand gesture recognition for human-robot interaction
title_sort	hand gesture recognition for human-robot interaction
granting_institution	Universiti Teknologi Malaysia, Faculty of Engineering - School of Electrical Engineering
granting_department	Faculty of Engineering - School of Electrical Engineering
publishDate	2020
url	http://eprints.utm.my/id/eprint/93019/1/TanAnnNieMSKE2020.pdf
_version_	1747818628227530752

Hand gesture recognition for human-robot interaction

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