Tejas Amrutkar
Amaan Saifi
Sakshi Auti
Prashant Dahale
- Student Department of Electronics and Telecommunication Engineering, Singhad College of Engineering Maharashtra India
- Student Department of Electronics and Telecommunication Engineering, Singhad College of Engineering Maharashtra India
- Student Department of Electronics and Telecommunication Engineering, Singhad College of Engineering Maharashtra India
- Professor Department of Electronics and Telecommunication Engineering, Singhad College of Engineering Maharashtra India
Abstract
With the number of cars multiplying daily, safety precautions are judged required. Automatic number plate recognition uses image processing and machine learning techniques to recognize vehicle numbers. By utilizing the vehicle number plate, the approach recommended seeks to establish a capable automated approved auto identification system. We describe an automated vehicle number detection system based on image processing and Raspberry Pi that reads license plates. In this setting, a Raspberry Pi is linked to a camera. The device continuously examines incoming camera footage for any traces of number plates When it notices a particular number plate in front of the camera, it analyzes the input from the camera and extracts the number tag component from7 the picture. With a Raspberry Pi, the system continuously scans its environment for moving vehicles and instantly analyzes incoming video. The system immediately initiates image processing algorithms to extract and isolate the number plate region from the captured frame upon detecting a vehicle within its field of view. The vehicle number plate region is extracted from an image using OCR, Yolo algorithm through character segmentation. After that, the gathered data is reviewed with the relevant authority dataset to look into precise details like the owner of the car, the place of the vehicle’s registration, the address, and so on.
Keywords: Number Plate Recognition, Raspberry Pi, Gps Notification, Vibration Sensor, Pressure Sensor
[This article belongs to Trends in Machine design(tmd)]
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Trends in Machine design
| Volume | 11 |
| Issue | 01 |
| Received | April 17, 2024 |
| Accepted | May 3, 2024 |
| Published | May 23, 2024 |
