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Comparison of Motion History Image and Approximated Ellipse Method in Human Fall Detection System

IJCCS (Indonesian Journal of Computing and Cybernetics Systems) · Vol. 13 No. 2 (2019) · pp. 199–208

DOI
10.22146/ijccs.43632
ISSN
2460-7258, 1978-1520
Published
2019-04-30
Publisher
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

This paper compares two different method in human fall detection system namely motion history image and approximated ellipse. Research has been done in small studio with 4 CCTV camera as video data recorder, whereas video data are processed using MATLAB software. The experiment was carried out using three object’s fall direction and two type of falling movement. The fall direction is consist of front, side, and back fall. Whereas the falling movement is consist of direct and indirect fall movement. Meanwhile, the object’s initial position is standing and size of captured object is constant. The result is motion history image has accuracy 74.26% for direct falling movement, and 75.69% for indirect falling movement. Whereas approximated ellipse has accuracy 56.85% for direct falling movement, and 61.81% for indirect falling movement. Therefore, motion history image is better than approximated ellipse in human fall detection system.

Keywords

Collaboration network of the authors

4 authors · 4 co-authorship links

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  • Islamic University of Indonesia
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  • Same organisation
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Co-authorOrganisationJoint articles
Muhammad IrfanIslamic University of Indonesia1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://journal.ugm.ac.id/ijccs/oai, first harvested 26 Okt 2026, last seen 26 Okt 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">Comparison of Motion History Image and Approximated Ellipse Method in Human Fall Detection System</dc:title>
	<dc:creator>Frasetyo, Mohammad Brado</dc:creator>
	<dc:creator>Wahyuni, Elvira Sukma</dc:creator>
	<dc:creator>Setiawan, Hendra</dc:creator>
	<dc:subject xml:lang="en-US">Computer Science</dc:subject>
	<dc:subject xml:lang="en-US">Image Processing; Human Fall Detection; Method Comparison; Motion History Image; Approximated Ellipse</dc:subject>
	<dc:description xml:lang="en-US">This paper compares two different method in human fall detection system namely motion history image and approximated ellipse. Research has been done in small studio with 4 CCTV camera as video data recorder, whereas video data are processed using MATLAB software. The experiment was carried out using three object’s fall direction and two type of falling movement. The fall direction is consist of front, side, and back fall. Whereas the falling movement is consist of direct and indirect fall movement. Meanwhile, the object’s initial position is standing and size of captured object is constant. The result is motion history image has accuracy 74.26% for direct falling movement, and 75.69% for indirect falling movement. Whereas approximated ellipse has accuracy 56.85% for direct falling movement, and 61.81% for indirect falling movement. Therefore, motion history image is better than approximated ellipse in human fall detection system.</dc:description>
	<dc:publisher xml:lang="en-US">IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.</dc:publisher>
	<dc:contributor xml:lang="en-US"></dc:contributor>
	<dc:date>2019-04-30</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
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	<dc:identifier>https://journal.ugm.ac.id/ijccs/article/view/43632</dc:identifier>
	<dc:identifier>10.22146/ijccs.43632</dc:identifier>
	<dc:source xml:lang="en-US">IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 13, No 2 (2019): April; 199-208</dc:source>
	<dc:source>2460-7258</dc:source>
	<dc:source>1978-1520</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journal.ugm.ac.id/ijccs/article/view/43632/24365</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2019 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
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