Abstract:
The regulation of traffic and the identification of vehicle drivers have emerged as significant challenges around the globe. It is not always easy to determine the identity of the driver of a vehicle that breaks the laws of the road and travels at an unsafe speed. since of this, it is not feasible to apprehend and penalize the sorts of individuals who do this since the traffic officials might not be able to retrieve the vehicle number from the moving car because of the pace at which the vehicle is travelling. As a result of this, the development of the system as one of the potential answers to this problem is required.
A picture or video may be analyzed by our Detect and Recognize Vehicle License Plate software to locate the license plate number. In addition to that, it has the ability to detect in real time by utilizing OpenCV and Python-tesseract. The user will just need to upload a picture or video from their own device to complete the process.
This technology can detect and identify car license plates based on a file that a user has provided to the system. Simply clicking on the device’s camera is all that is required to activate the system’s ability to read license plates in real time. The system will identify and recognize the license plate, and if it has been detected, it will be presented to the user. If it has been detected, it will be displayed to the user. HTML, Cascading Style Sheets, and JavaScript are used for the front end, while Python is used for the back end. Django was chosen as the framework, while MySQL was selected as the database.
OpenCV and the Python-tesseract packages have been included by our team. Wrapper for Google’s Tesseract-OCR Engine, Python-tesseract is written in Python. Because it is able to read all available picture kinds, it may also be used as a standalone script to invoke Tesseract, which can be beneficial.
Note: Please discuss with our team before submitting this abstract to the college. This Abstract or Synopsis varies based on student project requirements.
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