The Real-Time Vehicle Recognition System is an automated vehicle identification platform
developed to improve efficiency at expressway toll booths by eliminating manual vehicle
verification. The system uses image processing techniques to detect vehicle registration numbers
from camera images and retrieve vehicle information from a centralized database without human
intervention.
Traditional toll collection systems rely on manual ticketing and document verification, which
can lead to long queues and increased processing time. This project addresses these challenges
by automatically recognizing vehicle registration numbers and validating vehicle-related
information, including license status, insurance validity, and emission (eco) test records,
through an integrated database.
The project involved developing a vehicle number plate recognition system, designing a
relational database to store vehicle records, and implementing a search mechanism to retrieve
vehicle information in real time. The system demonstrates how image processing and database
technologies can be integrated to support intelligent transportation systems, reduce congestion,
improve toll operations, and assist in traffic monitoring and law enforcement applications.
* Developed a database to store vehicle registration and owner information.
* Designed and implemented the vehicle record retrieval system.
* Integrated image processing with database queries for automatic vehicle identification.
* Implemented validation of vehicle license, insurance, and emission test records.
* Tested the system using sample vehicle registration data.
Technologies
Python, OpenCV, MySQL, SQL, Image Processing, Database Management
Gallery
Team
Dilshani Karunarathna
Pasan Tennakoon
Suneth Samarasinghe
Pubudu Premathilake
Wishma Herath
Imesh Ekanayake