Parking Space Finder Using Image Processing and Machine Learning

Abstract

Finding a parking spot has become difficult in many places all over the globe due to the rise in the number of vehicles on the road. The use of image processing and machine learning methods to count the number of accessible parking spaces in a particular location is one of many smart parking solutions that have been put forth to handle this problem. In this study, we show a clever parking system that counts the number of parking spots that are open in real-time by using machine learning and image processing methods to identify and discover available spaces. The suggested system consists of a camera network that records pictures of the parking area and an algorithm that analyses these images to find open parking spots. To extricate the parking spots from the recorded pictures, the image processing algorithm carries out a number of image enhancement and segmentation operations. The machine learning programe then examines these segmented pictures to categories each parking spot as either empty or filled. For the ease of users, the system offers a real-time count of the available parking spots, which can be shown on electronic signage or sent to a smartphone application. The suggested clever parking system has a number of benefits over conventional parking systems. It can increase the effectiveness of parking administration, lessen traffic congestion, and make parking easier for travelers. In order to improve the total city infrastructure, it can also be combined with other smart city systems like traffic management, public transit, and environmental tracking systems