Vehicle and Parking Slot Detection using Image Processing and Open CV

Abstract: This paper provides a smart parking system based on open CV that was created for open parking lots, multi-story parking garages, and many more applications. The suggested system design makes use of the coordinate bound pixel and combined bound pixel and combined edge detection sections in python and the open CV library to determine whether or not a parking space in the captured footage is occupied. Additionally, it shows how to convert images to text. Text is extracted from the processed image using Tesseract. To ensure that various slots receive varying degrees of treatment to yield optimal text results, image processing is variable.One of the key functionalities of these systems is automated occupancy detection. Through the use of edge detection and pixel analysis techniques provided by OpenCV, the system can determine in real-time whether a parking spot is occupied or vacant. This information is crucial for drivers seeking available spaces and for parking facility managers to monitor occupancy levels efficiently.The variable level of image processing ensures adaptability across different environments and lighting conditions. By adjusting the image processing algorithms, the system can effectively handle variations in image quality and environmental factors, providing consistent and reliable results regardless of the setting.