ALPR — Automatic License Plate Recognition

Overview

An end-to-end Automatic License Plate Recognition (ALPR) system designed for real-time vehicular monitoring. The architecture consists of a high-throughput FastAPI backend handling heavy machine learning inference and OpenCV image processing pipelines, paired with an interactive Next.js dashboard that streams live recognition events, visualizes analytics, and manages historical query data.

Stack

Challenges

1. Optimizing OpenCV preprocessing and detection models to maintain a sub-50ms inference loop. 2. Architecting a reliable real-time messaging pipeline over WebSockets to stream recognized plates without dropping frames or causing UI lag under high traffic. 3. Designing robust image normalization techniques to handle diverse environmental factors like poor lighting, extreme angles, and vehicle speed.

Result

Successfully engineered a low-latency, resilient pipeline with distinct boundary separation between computer vision preprocessing, OCR extraction, and the dashboard presentation layer. The final system achieves over 95% recognition accuracy on test streams with seamless real-time UI updates.