PENGGUNAAN HAAR CASCADE CLASSIFIERS UNTUK MENDETEKSI PELANGGAR DI ZEBRA CROSS LAMPU LALU LINTAS - Mahada Panji Anggadhita, (2020)
There are so many violations that occur at the traffic light zebra crossing. Many of these violations were caused by the driver's negligence himself who did not heed the existing regulations. As a result, there are many traffic accidents that should have been avoided. Starting from this problem, we need a tool that is able to give direct advice to drivers when a violation occurs. Based on this, the purpose of this research is to prevent accidents caused by motorists who are negligent of the rules by identifying vehicles that stop crossing the zebra crossing or drivers waiting for traffic lights that are not in their place using the Haar Cascade Classifiers image in the program. Python and OpenCV to assist digital image processing. The results of this study are expected to be able to simulate warning signs in the form of sounds to offenders detected by the system.