License Plate Detection Methods Based on OpenCV

IEEE BASE PAPER ABSTRACT:

With the popularization of automobile and the progress of computer vision detection technology, intelligent license plate detection technology has gradually become an important part of intelligent traffic management. License plate detection is used to segment vehicle image and obtain license plate area for follow-up recognition system to screen. It is widely used in intelligent traffic management, vehicle video monitoring and other fields. In this paper, two license plate detection methods are studied, one is based on Sobel edge detection and the other is based on morphological gradient detection. Basing on OpenCV and visual studio 2012 under Windows system, two methods of license plate detection are implemented, and the two algorithms are compared in detail from the aspects of license plate detection accuracy. These methods have high efficiency and good interactivity, which provide a reference for later license plate recognition.

PROJECT OUTPUT VIDEO:

ALGORITHM / MODEL USED:

OpenCV.

SYSTEM REQUIREMENTS:

HARDWARE REQUIREMENTS:

System : Pentium i3 Processor.
Hard Disk : 500 GB.
Monitor : 15’’ LED
Input Devices : Keyboard, Mouse
Ram : 4 GB

SOFTWARE REQUIREMENTS:

Operating system : Windows 10 / 11.
Coding Language : Python 3.6
Web Framework : Flask.
Frontend : HTML, CSS, JavaScript.

REFERENCE:

Lin Xu,Wenqian Shang, Weiguo Lin, Wei Huang, “License Plate Detection Methods Based on OpenCV” IEEE Conference, 2021.

Python IEEE Projects

License Plate Detection Methods Based on OpenCV