Barrier Access Control Using Sensors Platform and Vehicle License Plate Characters Recognition

Area of Science:

• Computer Vision
• Robotics
• Embedded Systems

Background:

• Automated vehicle access control systems often rely on license plate recognition.
• Non-standard license plates present significant challenges for traditional image-based recognition systems due to variations in background, fonts, and deformations.

Purpose of the Study:

• To develop and evaluate a robust sensor platform for automated vehicle barrier control.
• To enhance license plate recognition accuracy for vehicles with non-standard license plates.

Main Methods:

• The system utilizes ultrasonic sensors for vehicle detection and a camera for image capture.
• An automated pipeline extracts the license plate, segments characters, and employs optical character recognition (OCR) for identification.
• The method is designed to handle variations in license plate appearance.

Main Results:

• The proposed system achieved 98% accuracy in license plate extraction.
• Character segmentation accuracy reached 96%.
• Character recognition accuracy was 93%.

Conclusions:

• The developed sensor platform effectively automates vehicle entry barriers.
• The image-based license plate recognition method demonstrates high accuracy and robustness, even with challenging, non-standard plates.