New Method for Optimization of License Plate Recognition system with Use of Edge Detection and Connected Component

TL;DR

This paper introduces a real-time license plate recognition method that combines adaptive thresholding, edge detection, and morphological operations to accurately locate and correct tilted plates, achieving a 98.66% extraction rate.

Contribution

The paper presents a novel, fast, and real-time license plate recognition approach that effectively handles tilted and poor-quality plates using edge detection and morphological techniques.

Findings

Achieved 98.66% correct plate extraction rate.

Effective in handling tilted and poor-quality license plates.

Validated on diverse background images with varying distances and angles.

Abstract

License Plate recognition plays an important role on the traffic monitoring and parking management systems. In this paper, a fast and real time method has been proposed which has an appropriate application to find tilt and poor quality plates. In the proposed method, at the beginning, the image is converted into binary mode using adaptive threshold. Then, by using some edge detection and morphology operations, plate number location has been specified. Finally, if the plat has tilt, its tilt is removed away. This method has been tested on another paper data set that has different images of the background, considering distance, and angel of view so that the correct extraction rate of plate reached at 98.66%.