AI/MLComputer Vision

Plate Detector

Computer vision pipeline for plate detection and ticket generation

Automated the flow from plate capture to database matching and ticket issuance using hosted YOLO-style inference with OpenCV preprocessing.

Overview

Plate Detector is a practical computer vision system that identifies license plates from image feeds, validates them against a records database, and produces ticket outputs.

Problem

Manual inspection and matching of plate records is time consuming and error-prone when throughput increases.

Solution

I implemented a pipeline combining OpenCV preprocessing with YOLO-style hosted inference, then connected results to a matching layer and automated ticket generation workflow.

Tech Stack

Python
OpenCV
Hosted YOLO-style inference
Database integration

Architecture

Simplified flow diagram rendered as text.

Camera / Image Input
  -> OpenCV preprocessing
    -> Hosted YOLO-style inference service
      -> Plate text extraction + DB match
        -> Ticket generation service

Key Features

License plate detection from image input
Database matching against known records
Automated ticket generation flow
Pipeline design optimized for extension and deployment

Challenges & Learnings

Handled variable image quality with preprocessing and validation checks.
Balanced model output confidence with downstream automation needs.
Strengthened approach to integrating CV systems into real business workflows.

Links

Private repo