Efficient Algorithms for Vehicle Plate Detection in Dynamic Environments

Abstract

One of these advanced search methods makes use of NPR systems to read license plates. A multitude of technologies work together to enable the system to take a photo of a car and digitally detect whether or not the license plate number can be read from it. The term "automatic license capture" refers to the procedure of extracting the license text from the pixel data of digital photographs. In this research, we provide a license plate identification technique that makes use of morphological techniques (easyOCR, imutils) applied to pictures. The primary goal is to employ and integrate several morphological procedures based on image processing, grayscale conversion, two-dimensional filtering, and licensing in order to detect and understand the license of specific automobiles from vehicle photos.

After completing the above steps, use the segmentation technique to identify the license text by comparing patterns and OCR. The system can accurately and quickly identify the driver's license from the vehicle image.