# An Efficient and Layout-Independent Automatic License Plate Recognition System Based on the YOLO detector

arXiv: https://arxiv.org/abs/1909.01754 · HTML: https://mlsanity.com/paper/1909.01754/

## Key facts

- Cited by 35 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 Sep 2019.

## Built on by (most cited first, 30 of 35)

- [On the Cross-dataset Generalization in License Plate Recognition](https://mlsanity.com/paper/2201.00267/) (2022)
- [A First Look at Dataset Bias in License Plate Recognition](https://mlsanity.com/paper/2208.10657/) (2022)
- [Do We Train on Test Data? The Impact of Near-Duplicates on License Plate Recognition](https://mlsanity.com/paper/2304.04653/) (2023)
- [Combining Attention Module and Pixel Shuffle for License Plate Super-Resolution](https://mlsanity.com/paper/2210.16836/) (2022)
- [Unified Chinese License Plate Detection and Recognition with High Efficiency](https://mlsanity.com/paper/2205.03582/) (2022)
- [IDD-3D: Indian Driving Dataset for 3D Unstructured Road Scenes](https://mlsanity.com/paper/2210.12878/) (2022)
- [Leveraging Model Fusion for Improved License Plate Recognition](https://mlsanity.com/paper/2309.04331/) (2023)
- [Super-Resolution of License Plate Images Using Attention Modules and Sub-Pixel Convolution Layers](https://mlsanity.com/paper/2305.17313/) (2023)
- [Enhancing License Plate Super-Resolution: A Layout-Aware and Character-Driven Approach](https://mlsanity.com/paper/2408.15103/) (2024)
- [Improving Small Drone Detection Through Multi-Scale Processing and Data Augmentation](https://mlsanity.com/paper/2504.19347/) (2025)
- [Advancing Multinational License Plate Recognition Through Synthetic and Real Data Fusion: A Comprehensive Evaluation](https://mlsanity.com/paper/2601.07671/) (2026)
- [Toward Advancing License Plate Super-Resolution in Real-World Scenarios: A Dataset and Benchmark](https://mlsanity.com/paper/2505.06393/) (2025)
- [LPLC: A Dataset for License Plate Legibility Classification](https://mlsanity.com/paper/2508.18425/) (2025)
- [Real-time Bangla License Plate Recognition System for Low Resource Video-based Applications](https://mlsanity.com/paper/2108.08339/) (2021)
- [Evaluation of Different Annotation Strategies for Deployment of Parking Spaces Classification Systems](https://mlsanity.com/paper/2207.11372/) (2022)
- [ICPR 2026 Competition on Low-Resolution License Plate Recognition](https://mlsanity.com/paper/2604.22506/) (2026)
- [SamLP: A Customized Segment Anything Model for License Plate Detection](https://mlsanity.com/paper/2401.06374/) (2024)
- [Image-based Automatic Dial Meter Reading in Unconstrained Scenarios](https://mlsanity.com/paper/2201.02850/) (2022)
- [Vehicle and License Plate Recognition with Novel Dataset for Toll Collection](https://mlsanity.com/paper/2202.05631/) (2022)
- [Character Time-series Matching For Robust License Plate Recognition](https://mlsanity.com/paper/2307.11336/) (2023)
- [A Training-Free Framework for Video License Plate Tracking and Recognition with Only One-Shot](https://mlsanity.com/paper/2408.05729/) (2024)
- [Veri-Car: Towards Open-world Vehicle Information Retrieval](https://mlsanity.com/paper/2411.06864/) (2024)
- [Relaxed syntax modeling in Transformers for future-proof license plate recognition](https://mlsanity.com/paper/2506.17051/) (2025)
- [LPTR-AFLNet: Lightweight Integrated Chinese License Plate Rectification and Recognition Network](https://mlsanity.com/paper/2507.16362/) (2025)
- [Real-time smart vehicle surveillance system](https://mlsanity.com/paper/2111.12289/) (2021)
- [On the Design of Privacy-Aware Cameras: a Study on Deep Neural Networks](https://mlsanity.com/paper/2208.11372/) (2022)
- [Reading Between the Mud: A Challenging Motorcycle Racer Number Dataset](https://mlsanity.com/paper/2311.09256/) (2023)
- [Beyond the Mud: Datasets and Benchmarks for Computer Vision in Off-Road Racing](https://mlsanity.com/paper/2402.08025/) (2024)
- [PlateSegFL: A Privacy-Preserving License Plate Detection Using Federated Segmentation Learning](https://mlsanity.com/paper/2404.05049/) (2024)
- [Efficient Video-Based ALPR System Using YOLO and Visual Rhythm](https://mlsanity.com/paper/2501.02270/) (2025)

## Abstract (arXiv)

This paper presents an efficient and layout-independent Automatic License Plate Recognition (ALPR) system based on the state-of-the-art YOLO object detector that contains a unified approach for license plate (LP) detection and layout classification to improve the recognition results using post-processing rules. The system is conceived by evaluating and optimizing different models, aiming at achieving the best speed/accuracy trade-off at each stage. The networks are trained using images from several datasets, with the addition of various data augmentation techniques, so that they are robust under different conditions. The proposed system achieved an average end-to-end recognition rate of 96.9% across eight public datasets (from five different regions) used in the experiments, outperforming both previous works and commercial systems in the ChineseLP, OpenALPR-EU, SSIG-SegPlate and UFPR-ALPR datasets. In the other datasets, the proposed approach achieved competitive results to those attained by the baselines. Our system also achieved impressive frames per second (FPS) rates on a high-end GPU, being able to perform in real time even when there are four vehicles in the scene. An additional contribution is that we manually labeled 38,351 bounding boxes on 6,239 images from public datasets and made the annotations publicly available to the research community.