WILLIAM REDDEN • MECHANICAL ENGINEERING TECHNOLOGY

ESP32-CAM License Plate Recognition (LPR) System | Summer 2025



Project Description

This project involved designing an embedded computer-vision system using a ESP32-CAM to capture vehicle images and perform license plate recognition (LPR). The system uses a button to trigger image capture. Once clicked, the image is processed and the identified text appear on the OLED display. This step leverages cloud based image processing to extract then return recognized license plate text. The final results are displayed both on the OLED screen and as an annotated image returned from remote processing.





System Overview / Hardware

  • ESP32-CAM used as the main embedded controller and camera module


  • ESP32's camera for still image capture


  • SSD1306 OLED display for system status and recognition feedback


  • Push-button trigger for controlled image capture


  • FTDI USB-to-UART adapter for power and programming


Inputs & Outputs

Inputs:


  • Push-button trigger (GPIO13) for image capture

  • Power input (5 V via FTDI USB-to-UART adapter)


Outputs:


  • OLED display (SSD1306, I²C) showing system status and recognized license plate text


  • Processed JPEG image returned from remote processing with license plate text overlaid


  • Serial Monitor output for debugging, calibration, and system verification


Image of Setup

Schematic

Code

Solution Methods

  • Fritzing used to create a schematic

  • Sketches performed in Onenote to stay organized


  • Serial monitor utilized for debugging, calibration, and system verification


  • Implemented button-controlled image capture to avoid continuous streaming


  • Incrementally tested hardware, communication, and display functionality during system integration

Results

  • Fully functional ESP32-CAM license plate recognition system


  • Reliable push-button controlled image capture operation


  • Successful transmission and retrieval of processed images from the license plate


  • Clear OLED display feedback for system status and recognition results


© William Redden - 2026