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Sign Language Recognition in Robot Teleoperation using Centroid Distance Fourier Descriptors

by Rayi Yanu Tara, Paulus Insap Santosa, Teguh Bharata Adji
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 48 - Number 2
Year of Publication: 2012
Authors: Rayi Yanu Tara, Paulus Insap Santosa, Teguh Bharata Adji
10.5120/7318-0100

Rayi Yanu Tara, Paulus Insap Santosa, Teguh Bharata Adji . Sign Language Recognition in Robot Teleoperation using Centroid Distance Fourier Descriptors. International Journal of Computer Applications. 48, 2 ( June 2012), 8-12. DOI=10.5120/7318-0100

@article{ 10.5120/7318-0100,
author = { Rayi Yanu Tara, Paulus Insap Santosa, Teguh Bharata Adji },
title = { Sign Language Recognition in Robot Teleoperation using Centroid Distance Fourier Descriptors },
journal = { International Journal of Computer Applications },
issue_date = { June 2012 },
volume = { 48 },
number = { 2 },
month = { June },
year = { 2012 },
issn = { 0975-8887 },
pages = { 8-12 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume48/number2/7318-0100/ },
doi = { 10.5120/7318-0100 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:43:02.572288+05:30
%A Rayi Yanu Tara
%A Paulus Insap Santosa
%A Teguh Bharata Adji
%T Sign Language Recognition in Robot Teleoperation using Centroid Distance Fourier Descriptors
%J International Journal of Computer Applications
%@ 0975-8887
%V 48
%N 2
%P 8-12
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Commanding in robot teleoperation system can be done in several ways, including the use of sign language. In this paper, the use of centroid distance Fourier descriptors as hand shape descriptor in sign language recognition from visually captured hand gesture is considered. The sign language adopts the American Sign Language finger spelling. Only static gestures in the sign language are used. To obtain hand images, depth imager is used in this research. Hand image is extracted from depth image by applying threshold operation. Centroid distance signature is constructed from the segmented hand contours as a shape signature. Fourier transformation of the centroid distance signature results in fourier descriptors of the hand shape. The fourier descriptors of hand gesture are then compared with the gesture dictionary to perform gesture recognition. The performance of the gesture recognition using different distance metrics as classifiers is investigated. The test results show that the use of 15 Fourier descriptors and Manhattan distance-based classifier achieves the best recognition rates of 95% with small computation latency about 6. 0573 ms. Recognition error is occurred due to the similarity of Fourier descriptors from some gesture.

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Index Terms

Computer Science
Information Sciences

Keywords

Hand Gesture Sign Language Fingerspelling Cefd Fourier Descriptor

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