License Plate Dectection

The Project

Our project aims to automate the registration process by accurately detecting and capturing license plate information using computer vision techniques and deep learning algorithms. Leveraging the OpenCV and NumPy libraries, our code implements a robust license plate detection system. It captures frames from a video feed, sets frame dimensions, and employs a pre-trained cascade classifier to identify license plates in grayscale frames. Detected plates are outlined with rectangles and labeled as "Number Plate". If the plate area exceeds a specified threshold, the system saves a cropped image. Real-time feedback is provided by displaying processed frames with detected plates. Users can trigger plate saving by pressing 's', with the system confirming when a scan is saved. Pressing 'q' quits the application, offering a simple yet effective solution for real-time license plate detection.

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