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Estimation of Average Car Speed Using the Haar-Like Feature and Correlation Tracker Method

IJCCS (Indonesian Journal of Computing and Cybernetics Systems) · Vol. 14 No. 4 (2020) · pp. 353–364

DOI
10.22146/ijccs.57262
ISSN
2460-7258, 1978-1520
Published
2020-10-31
Publisher
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

The speed of a car traveling on the road can generally be estimated by using a speed gun. Efforts are needed to use CCTV (closed circuit television) as a tool that can be used to estimate the speed of the car so as to ease the burden on the road operator to estimate the speed of the car. This study discusses the estimated average speed of the car with the Haar-like Feature method used to detect the car, then the detection results are tracked using Correlatin Tracker to track the movement of objects that have been detected and calculate the distance of movement from the car, so that the speed of the car detected in video can be estimated. The results of the estimated average speed compared with the results of taking speed with a speed gun so that an error is obtained by MAE testing of 5,55 km / hour and the resulting standard deviation is 4,61 km / hour, thus it can be concluded that the system is made valid and can be used by road organizers to monitor the average speed of a car.

Keywords

Collaboration network of the authors

40 authors · 62 co-authorship links · 11 across different organisations · showing the 40 most connected

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Universitas Gadjah Mada
  • Universitas Halu Oleo
  • Indonesia Open University
  • University of Ulsan
  • Lambung Mangkurat University
  • Telkom University
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Reny Eka SariAffiliation unknown2
Chasandra PuspitasariUniversitas Gadjah Mada2
Kasliono KaslionoUniversitas Gadjah Mada2
Wahyu Sri MulyaniUniversitas Gadjah Mada2
Laksono KurnianggoroUniversity of Ulsan2
Rahmat RamadhanUniversitas Halu Oleo1
Ika Purwanti NingrumUniversitas Halu Oleo1
Dian NursantikaIndonesia Open University1
Endang AnggiratihUniversitas Gadjah Mada1
Joko HariyonoAffiliation unknown1
Agus HarjokoUniversitas Gadjah Mada1
Abdul KholikUniversitas Gadjah Mada1
Suprapto SupraptoUniversitas Gadjah Mada1
Yaqutina Marjani SantosaUniversitas Gadjah Mada1
Nur RokhmanUniversitas Gadjah Mada1
Riska Amalia PraptiwiUniversitas Gadjah Mada1
Nuruddin WirandaLambung Mangkurat University1
Aliyyah Nur AzhariUniversitas Gadjah Mada1
Suyanto SuyantoTelkom University1
Cholis MahardhikaAffiliation unknown1
Aida Roihana ZuhroAffiliation unknown1
Amin YusufAffiliation unknown1
Yanuarius Seran FahikAffiliation unknown1
Tri SuminarAffiliation unknown1
Aninda Mawar IntanuariAffiliation unknown1
Siti NurnaningsihAffiliation unknown1
Laela AtikahAffiliation unknown1
Dian ArifianiAffiliation unknown1
Shella PrahastiAffiliation unknown1
Ayu ErawatiAffiliation unknown1
Elizah ElizahAffiliation unknown1
Nuratun ZakiyahAffiliation unknown1
Falilah FalilahAffiliation unknown1
S MartonoAffiliation unknown1
Ariesa PrihartantiAffiliation unknown1
Rusdarti RusdartiAffiliation unknown1
Indah MerakatiAffiliation unknown1

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 Oct 2026, last seen 8 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">Estimation of Average Car Speed Using the Haar-Like Feature and Correlation Tracker Method</dc:title>
	<dc:creator>Fauzi, Muhammad Dzulfikar</dc:creator>
	<dc:creator>Putra, Agfianto Eko</dc:creator>
	<dc:creator>Wahyono, Wahyono</dc:creator>
	<dc:subject xml:lang="en-US"></dc:subject>
	<dc:subject xml:lang="en-US">Haar-like Feature; Car detection; Tracking; Average Estimation of Speed</dc:subject>
	<dc:description xml:lang="en-US">The speed of a car traveling on the road can generally be estimated by using a speed gun. Efforts are needed to use CCTV (closed circuit television) as a tool that can be used to estimate the speed of the car so as to ease the burden on the road operator to estimate the speed of the car. This study discusses the estimated average speed of the car with the Haar-like Feature method used to detect the car, then the detection results are tracked using Correlatin Tracker to track the movement of objects that have been detected and calculate the distance of movement from the car, so that the speed of the car detected in video can be estimated. The results of the estimated average speed compared with the results of taking speed with a speed gun so that an error is obtained by MAE testing of 5,55 km / hour and the resulting standard deviation is 4,61 km / hour, thus it can be concluded that the system is made valid and can be used by road organizers to monitor the average speed of a car.</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>2020-10-31</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
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	<dc:identifier>https://journal.ugm.ac.id/ijccs/article/view/57262</dc:identifier>
	<dc:identifier>10.22146/ijccs.57262</dc:identifier>
	<dc:source xml:lang="en-US">IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 14, No 4 (2020): October; 353-364</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/57262/29697</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2020 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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