Car Number Plate Detection – Tesseract Technolabs

Case Study

project description

In this project, we created a parking system where it automatically stores information about entering a car in the parking plot.
From the camera, it will record the video and our model will detect the number plate of the car.
From this number plate, another model will detect the car number from the number plate and store this information regarding the timings and car number plate in the database.
Using this system any medium to large parking plot can store the information of the incoming cars and their information.
For the model, we used the YOLOv5 model for number plate detection and we used Image segmentation to get the number from the number plate.
Moreover, we used RasberyPi to connect the surveillance camera with our model and provide our model processing power.

Technologies used

We used Convolution Neural Network for image segmentation to get the number from the number plate.
We used the YOLOv5 model for number plate detection from the camera.
Moreover, we used RasberryPi to connect surveillance cameras with our models.
Along with this, we used AWS to store information about the car number plate and timings of the car.

Difficulties we faced

The major difficulty we faced was with the output from the camera, the camera was of low quality.

Solutions

To solve this problem we used some image processing techniques to get the right image for prediction.

Computer Vision

8 months

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