Smart Number Plate Recognition System For Car Parking Lot

The Smart Number Plate Recognition System is an automated computer vision project built around a Raspberry Pi 5 running Raspbian OS and Python 3. The Raspberry Pi Camera Module connects directly to the single-board computer via a ribbon cable, securely housed in a dedicated camera mount positioned at a vehicle entry or exit point. When a vehicle approaches the parking lot, the camera captures a high-resolution digital image of the car's front or rear. This image is streamed into the processing pipeline via NumPy arrays for efficient memory handling and image manipulation. OpenCV, an open-source computer vision library, processes the captured frame by converting it to grayscale, reducing noise, and applying thresholding techniques to isolate the high-contrast region containing the vehicle's license plate. Once the plate region is successfully cropped and localized, Pytesseract, an optical character recognition (OCR) wrapper, analyzes the pixel data to identify alphanumeric characters on the plate. After extracting the text string, the Python script pairs the recognized license plate data with a precise date and timestamp. This logged information can then be used to manage automated parking lot entry, track vehicle movement, or facilitate digital record-keeping for parking management databases.