Klasifikasi Rambu Lalu Lintas Menggunakan Ekstraksi Ciri Wavelet Dan Jarak Euclidean

Driving is one of the human activities in which daily life is often done. Driving can be done by land, air, and sea. Human mobility in driving is very high on land routes using various means of transportation. For the sake of smooth driving, roads are often equipped with traffic signs in each tra...

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Autores principales:	Vincentius Abdi Gunawan, Ignatia Imelda Fitriani, Leonardus Sandy Ade Putra
Formato:	article
Lenguaje:	EN ID
Publicado:	P3M Politeknik Negeri Banjarmasin 2019
Materias:	traffics sign image processing haar wavelet extraction euclidean distance Electrical engineering. Electronics. Nuclear engineering TK1-9971 Information technology T58.5-58.64
Acceso en línea:	https://doaj.org/article/dfd704d3b7a94752a7f03b5cf9cae57b
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

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spelling	oai:doaj.org-article:dfd704d3b7a94752a7f03b5cf9cae57b2021-12-02T03:20:09ZKlasifikasi Rambu Lalu Lintas Menggunakan Ekstraksi Ciri Wavelet Dan Jarak Euclidean2598-32452598-328810.31961/eltikom.v3i1.105https://doaj.org/article/dfd704d3b7a94752a7f03b5cf9cae57b2019-05-01T00:00:00Zhttp://eltikom.poliban.ac.id/index.php/eltikom/article/view/105https://doaj.org/toc/2598-3245https://doaj.org/toc/2598-3288Driving is one of the human activities in which daily life is often done. Driving can be done by land, air, and sea. Human mobility in driving is very high on land routes using various means of transportation. For the sake of smooth driving, roads are often equipped with traffic signs in each traffic area. Traffic signs are a means for road users to provide information and guidance for motorists about the situation in the surrounding area. The number of motorists who lack awareness of the knowledge of reading traffic signs is one of the biggest causes of accidents in Indonesia. So that a system is needed that can help in recognizing traffic signs, especially prohibited signs. The system designed using Haar Wavelet feature extraction and Euclidean distance as a classification. From the data that has been tested, the level of recognition in reading traffic signs is prohibited by 92%.Vincentius Abdi GunawanIgnatia Imelda FitrianiLeonardus Sandy Ade PutraP3M Politeknik Negeri Banjarmasinarticletraffics signimage processinghaar wavelet extractioneuclidean distanceElectrical engineering. Electronics. Nuclear engineeringTK1-9971Information technologyT58.5-58.64ENIDJurnal ELTIKOM: Jurnal Teknik Elektro, Teknologi Informasi dan Komputer, Vol 3, Iss 1, Pp 26-35 (2019)
institution	DOAJ
collection	DOAJ
language	EN ID
topic	traffics sign image processing haar wavelet extraction euclidean distance Electrical engineering. Electronics. Nuclear engineering TK1-9971 Information technology T58.5-58.64
spellingShingle	traffics sign image processing haar wavelet extraction euclidean distance Electrical engineering. Electronics. Nuclear engineering TK1-9971 Information technology T58.5-58.64 Vincentius Abdi Gunawan Ignatia Imelda Fitriani Leonardus Sandy Ade Putra Klasifikasi Rambu Lalu Lintas Menggunakan Ekstraksi Ciri Wavelet Dan Jarak Euclidean
description	Driving is one of the human activities in which daily life is often done. Driving can be done by land, air, and sea. Human mobility in driving is very high on land routes using various means of transportation. For the sake of smooth driving, roads are often equipped with traffic signs in each traffic area. Traffic signs are a means for road users to provide information and guidance for motorists about the situation in the surrounding area. The number of motorists who lack awareness of the knowledge of reading traffic signs is one of the biggest causes of accidents in Indonesia. So that a system is needed that can help in recognizing traffic signs, especially prohibited signs. The system designed using Haar Wavelet feature extraction and Euclidean distance as a classification. From the data that has been tested, the level of recognition in reading traffic signs is prohibited by 92%.
format	article
author	Vincentius Abdi Gunawan Ignatia Imelda Fitriani Leonardus Sandy Ade Putra
author_facet	Vincentius Abdi Gunawan Ignatia Imelda Fitriani Leonardus Sandy Ade Putra
author_sort	Vincentius Abdi Gunawan
title	Klasifikasi Rambu Lalu Lintas Menggunakan Ekstraksi Ciri Wavelet Dan Jarak Euclidean
title_short	Klasifikasi Rambu Lalu Lintas Menggunakan Ekstraksi Ciri Wavelet Dan Jarak Euclidean
title_full	Klasifikasi Rambu Lalu Lintas Menggunakan Ekstraksi Ciri Wavelet Dan Jarak Euclidean
title_fullStr	Klasifikasi Rambu Lalu Lintas Menggunakan Ekstraksi Ciri Wavelet Dan Jarak Euclidean
title_full_unstemmed	Klasifikasi Rambu Lalu Lintas Menggunakan Ekstraksi Ciri Wavelet Dan Jarak Euclidean
title_sort	klasifikasi rambu lalu lintas menggunakan ekstraksi ciri wavelet dan jarak euclidean
publisher	P3M Politeknik Negeri Banjarmasin
publishDate	2019
url	https://doaj.org/article/dfd704d3b7a94752a7f03b5cf9cae57b
work_keys_str_mv	AT vincentiusabdigunawan klasifikasirambulalulintasmenggunakanekstraksiciriwaveletdanjarakeuclidean AT ignatiaimeldafitriani klasifikasirambulalulintasmenggunakanekstraksiciriwaveletdanjarakeuclidean AT leonardussandyadeputra klasifikasirambulalulintasmenggunakanekstraksiciriwaveletdanjarakeuclidean
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Klasifikasi Rambu Lalu Lintas Menggunakan Ekstraksi Ciri Wavelet Dan Jarak Euclidean

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