AI Based Vehicle Information and Fraudulent Detection System
Authors/Creators
Description
The proposed system uses AI model for number plate detection. It uses computer vision and machine learning. The system checks the vehicle number plates in real time using Raspberry pi, a camera, Open CV, OCR (Optical Character Recognition) and YOLO model. This system uses a Raspberry Pi, a camera, OpenCV, OCR, and the YOLO model. These tools work together to examine car number plates in real-time. The system can automatically identify car registration details from photos and videos. This capability is particularly useful for Regional Transport Office work and helps to prevent fraud. The technology uses artificial intelligence to catch fake activities, like stolen or fake license plates, with high accuracy. The goal is to offer a solution that can grow in size and is low-cost for real-world use. This research aims to boost automated law enforcement and smart traffic monitoring.
Files
AI Based Vehicle Information and Fraudulent Detection System -Formatted Paper.pdf
Files
(348.7 kB)
| Name | Size | Download all |
|---|---|---|
|
md5:514269ff8f3ab19061442857edbd7e2c
|
348.7 kB | Preview Download |
Additional details
References
- 1. Saini, S. K., & Sinha, A. K. (2023). Extracting information from vehicle registration plate using OCR. Procedia Computer Science, 218.
- 2. Kumar, R., & Sharma, A. (2020). Automatic number plate recognition using machine learning techniques. International Journal of Computer Applications, 175(6), 23–30.
- 3. Srivastav, G. (2020). Automatic number plate recognition. International Journal for Research in Applied Science and Engineering Technology, 8, 1105–1108.
- 4. Agrawal, S. S. (2020). Automatic number plate recognition system for the detection of unauthorized vehicles.
- 5. Falaschetti et al., [2024 ], "Embedded Real-Time Vehicle and Pedestrian Detection Using a Compressed Tiny YOLOv3 Architecture", (IEEE Trans. Intelligent Transportation Systems)trid.trb.org.
- 6. Safran et al., [2024], "Efficient Multistage License Plate Detection and Recognition Using YOLOv8 and CNN for Smart Parking Systems", (Sensors/Journal of Sensors) studocu.com.
- 7. Khan et al., [2023], "Edge Computing for Effective and Efficient Traffic Characterization", (Sensors) mdpi.commdpi.com.
- 8. Ribeiro & Hirata, [2025], "Efficient Video-Based ALPR System Using YOLO and Visual Rhythm", (arXiv) arxiv.org.
- 9. Ribeiro & Hirata, [2025], "Combining YOLO and Visual Rhythm for Vehicle Counting", (arXiv) arxiv.org.
- 10. Wijaya & Soewito, [2024], "Efficient License Plate Detection and Recognition with YOLOv7 and OCR", (IJISAE) ijisae.org.