Car Detection in Roadside Parking for Smart Parking System Based on Image Processing
Deni Kristin Manase, Zahir Zainuddin, Syafruddin Syarif, Arsan Kumala Jaya
Abstract
This study aims to detect vehicles that are on the side of the parking lot so that it can be used as a smart parking system for parking management and find out information on the availability of parking spaces. In this study, the authors used the Haar Cascade Classifier, and YOLOv3 then compared them to get the best accuracy in detecting parked cars. The test was carried out using ten different scenarios, the highest accuracy obtained in this study was 96.88% using YOLOv3 with a probability of 90%. In contrast, the accuracy obtained by using the Haar Cascade Classifier is 63.34%.
Topics & Concepts
Haar-like featuresParking lotComputer scienceCascading classifiersCascadeArtificial intelligenceHaarClassifier (UML)Computer visionParking guidance and informationPattern recognition (psychology)Transport engineeringEngineeringFace detectionRandom subspace methodChemical engineeringCivil engineeringWaveletFacial recognition systemSmart Parking Systems ResearchVehicle License Plate RecognitionIoT and GPS-based Vehicle Safety Systems