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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