Number Plate Recognition using Deep Learning

YEAR : 2021


In this era of fast growing technologies, there is a huge demand among the people for a secure lifestyle and travelling. In the past decade, the number of vehicles on road has been increased. Tracking of individual vehicle becomes a very challenging task with the massive growth in the vehicular sector every day. This project suggests an automated vehicle tracking system for the fast moving vehicles with the help of the surveillance cameras on the roadside. The process of getting CCTV footage in the real time background is very tedious process. To cater to this problem, an efficient deep learning model used for object detection. The proposed work consists of four main steps. In the first step, video footage is converted into images and the car is detected from each of the frames. In the next step, license plate is detected from the detected cars. In the final step, the number plate characters reading are recognized from the detected number plates. The proposed deep learning model uses AI library to make the training process easier.


Operating System : Windows 7,8,10 (64 bit)
Software : Python
Tools : Anaconda (Jupyter notebook and anaconda prompt)


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