Real-Time Vehicle RC Expiry Detection and Smart Challan System Using YOLOv8 and OCR

With urban traffic levels reaching unprecedented levels, manual RC verification has become impractical, being both time-consuming and highly unreliable in its results. This work presents a Real-Time Vehicle Registration Certificate (RC) Expiry Detection and Smart Challan Generation System based on automated verification via computer vision. Webcam frames serve as input data for the proposed solution which uses a YOLOv8 detector to detect and crop the area occupied by the vehicle's number plate. Next, the cropped image undergoes preprocessing, including a conversion to grayscale, Gaussian filtering, and adaptive thresholding. After that, the detected number plate is recognized using the Tesseract OCR engine. The obtained alphanumeric value is used to compare the vehicle against an SQLite database with vehicles' identification numbers and dates of their RC expiration. Upon successful detection of an expired RC, the system generates a PDF document (challan) with the relevant vehicle information, timestamp of the violation, exact location of occurrence, and fine amount automatically. The pipeline itself is exposed through a Flask-based web interface allowing operators to monitor detection and enforcement events in real-time. Extensive testing proved that the system has good performance in terms of number plate recognition efficiency, minimal processing latency, and consistent challan generation.