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Robust License Plate Recognition in OCC-Based Vehicle Networks Using Image Reconstruction.

Dingfa Zhang¹, Ziwei Liu¹, Weiye Zhu¹

¹College of Computer Science, Sichuan University, Chengdu 610065, China.

Sensors (Basel, Switzerland)

|October 26, 2024

Summary

Optical Camera Communication (OCC) interferes with license plate recognition. We developed a new method to remove OCC stripes from images, significantly improving recognition accuracy in vehicle networks.

Keywords:

internet of vehicle (IoV)license-plate recognition (LPR)optical camera communication (OCC)vehicle to infrastructure (V2I)

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Area of Science:

Computer Vision
Internet of Vehicles (IoV)
Optical Camera Communication (OCC)

Background:

Optical Camera Communication (OCC) enables vehicle-to-infrastructure communication using traffic lights and street cameras.
OCC light emissions create stripe patterns in images, degrading the accuracy of license-plate recognition systems.
Existing license-plate recognition systems struggle with interference from OCC in Internet of Vehicles (IoV) applications.

Purpose of the Study:

To propose and demonstrate a method for reducing OCC stripe interference in license-plate recognition.
To enhance the accuracy of license-plate recognition in environments utilizing Optical Camera Communication.

Main Methods:

Developed an innovative pipeline featuring an end-to-end image reconstruction module.
Modeled OCC stripes as multiplicative noise to synthesize a pairwise dataset from existing license-plate data.
Built a prototype to simulate real-world OCC-based vehicle network scenarios and collect data.

Main Results:

Achieved 81.58% recognition performance on a synthesized dataset and 79.35% on real-scene captured data.
Demonstrated significant improvements of approximately 31.18% and 24.26% compared to conventional methods.
The proposed method effectively reconstructs high-quality license-plate images for recognition under OCC conditions.

Conclusions:

The developed method successfully mitigates OCC stripe interference, enhancing license-plate recognition accuracy.
The approach provides a viable solution for reliable vehicle identification in OCC-enabled IoV systems.
This research contributes to the practical deployment of Optical Camera Communication in intelligent transportation systems.