Sistem Penegakan Speed Bump Berdasarkan Kecepatan Kendaraan yang Diklasifikasikan Haar Cascade Classifier

Speed Bump Enforcement System Based on Vehicle Speed Classified by Haar Cascade Classifier

*Muhammad Zulfikri -  Department of Electrical Engineering, Universitas Brawijaya, Indonesia
Erni Yudaningtyas -  Department of Electrical Engineering, Universitas Brawijaya, Indonesia
Rahmadwati Rahmadwati -  Department of Electrical Engineering, Universitas Brawijaya, Indonesia
Received: 3 Dec 2018; Revised: 29 Jan 2019; Accepted: 30 Jan 2019; Published: 31 Jan 2019; Available online: 31 Mar 2019.
Open Access Copyright (c) 2019 Jurnal Teknologi dan Sistem Komputer
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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.
Keywords
speed bump; haar cascade classifier; detection; vehicle speed

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