Klasifikasi Rambu Lalu Lintas Menggunakan Ekstraksi Ciri Wavelet Dan Jarak Euclidean


  • Vincentius Abdi Gunawan Palangka Raya University
  • Ignatia Imelda Fitriani Palangka Raya University
  • Leonardus Sandy Ade Putra STMIK PALANGKARAYA




Traffics Sign, Image Processing, Haar Wavelet Extraction, Euclidean Distance


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%.


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How to Cite

Abdi Gunawan, V. et al. 2019. Klasifikasi Rambu Lalu Lintas Menggunakan Ekstraksi Ciri Wavelet Dan Jarak Euclidean. Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer. 3, 1 (May 2019), 26–35. DOI:https://doi.org/10.31961/eltikom.v3i1.105.