Department of Electrical Engineering, Universitas Brawijaya, Indonesia
BibTex Citation Data :
@article{JTSISKOM13158, author = {Muhammad Zulfikri and Erni Yudaningtyas and Rahmadwati Rahmadwati}, title = {Sistem Penegakan Speed Bump Berdasarkan Kecepatan Kendaraan yang Diklasifikasikan Haar Cascade Classifier}, journal = {Jurnal Teknologi dan Sistem Komputer}, volume = {7}, number = {1}, year = {2019}, keywords = {speed bump; haar cascade classifier; detection; vehicle speed}, 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. }, issn = {2338-0403}, pages = {12--18} doi = {10.14710/jtsiskom.7.1.2019.12-18}, url = {https://jtsiskom.undip.ac.id/article/view/13158} }
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