Vehicle License Plate Detection using Image Processing
Number Plate Detection enhances security and surveillance by employing neural networks to identify and recognize vehicle license plates. By analyzing images or video streams, the system accurately captures and interprets license plate information. This application finds applications in law enforcement, parking management, and traffic monitoring. The neural networks’ ability to process diverse plate formats and variations ensures reliable and efficient identification in various scenarios.
1. Datset is download from Kaggle and place in project folder.
2. Model is developed from large dataset of images and videos and label dataset.
3. User have to gave input image or video to model and first model will detect Number Plate and then recognize text or number from license plate and complete image stored in seperate folder.
Vehicle Number Plate Detection and Recognition using Machine Learning
Software Requirements :-
- Coding Language : Python
- Implementation: Software Framework.
- Operating system : Windows 10 / 11.
- Graphical User Interface : Tkinter
Hardware Requirement:-
- Input Devices : Keyboard, Mouse.
- System : Pentium i3 Processor.
- Hard Disk : 500 GB.
- RAM : 4 GB.
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