Penerapan OpenCV dengan Metode Haar Cascade untuk Mendeteksi Jumlah Kendaraan di Tempat Parkir

Abstract

The extent of parking lots and the increasing number of vehicles are now obstacles for motorists to find out the number of parking spaces that are still empty. The current parking lot development system is still not optimal in terms of time efficiency. As time goes by, there will be more vehicles, and the need for parking spaces will increase. This system can find out how many empty spaces there are and the number of vehicles in the parking lot. This will make it easier to find parking spaces that are still empty, which can save motorists time in finding parking spaces. The system uses the OpenCV implementation as a popular and easily accessible framework and uses Haar Cascade for an efficient object detection method that can be implemented in real time. The results of this test show that the use of Haar Cascade is effective in detecting vehicle objects with 75% accuracy.