ABSTRACT
Given the increase in population, vehicle tracking is no longer practical. Both time and resources are wasted in doing it. The enormous daily growth in the automotive industry has made tracking individual automobiles an extremely challenging undertaking. This research suggests a system for automatically tracking moving cars using roadside security cameras. License plate recognition systems are used in toll collection, parking fee, and residential entry control in contemporary smart cities. In addition to being helpful in people’s daily lives, these electronic technologies also give management access to secure and effective services. The suggested technique now includes a useful method for identifying Indian license plates on cars. The suggested technique can work with number plates that are obtrusive, dimly lit, cross-angled, and have unusual fonts. The effective deep learning-based ALPR (Automatic License Plate Recognition) model presented in this study uses character segmentation and a CNN-based recognition model. The experimental finding yields a 94.94% accuracy percentage for the f1 score.
