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Muhammad Zulfikri
Department of Electrical Engineering, Universitas Brawijaya
Computer Science & IT Electrical & Electronics Engineering

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Sistem Penegakan Speed Bump Berdasarkan Kecepatan Kendaraan yang Diklasifikasikan Haar Cascade Classifier Muhammad Zulfikri; Erni Yudaningtyas; Rahmadwati Rahmadwati
Jurnal Teknologi dan Sistem Komputer Volume 7, Issue 1, Year 2019 (January 2019)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (600.315 KB) | DOI: 10.14710/jtsiskom.7.1.2019.12-18

Abstract

Driving at high speed is among the frequent causes of accidents. In this research, a warning system was developed to warn drivers when their speed beyond the safety limit. Haar cascade classifier was proposed for the detection system which comprises Haar features, integral image, AdaBoost learning, and cascade classifier. The system was implemented using Python OpenCV library and evaluated on road traffic video collected in one way traffic. As a result, the proposed method yields 97.92% of car detection accuracy in daylight and MSE of 2.88 in speed measurement.
Co-Authors Erni Yudaningtyas Rahmadwati, n/a