Analyzing License Plate Recognition Using EasyOCR and Machine Learning Techniques

The objective of the study is to provide a wide range of use of License Plate Recognition. A crucial component of intelligent transportation systems (ITS) is License plate Recognition (LPR). Using pictures or video feeds, License Plate Recognition (LPR) automates the identification, extraction, and interpretation of vehicle License plates. Due to their use in parking management, toll collecting, law enforcement, traffic management, and Vehicle tracking, LPR systems have drawn a lot of interest. Identifying a number plate involves several steps, including image capture, Pre-processing, license plate detection, character segmentation, and optical character recognition (OCR). OCR plays a significant part in image processing. open-source optical character recognition (OCR) tool in conjunction with traditional machine learning methods. The method places a strong emphasis on accuracy, simplicity, and real time applicability. To show the model's resilience, we further assess it using cross-validation methods and common OCR datasets.