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A Novel Memory and Time-Efficient ALPR System Based on YOLOv5
Piyush Batra1, Imran Hussain1, Mohd Abdul Ahad1
1Department of Computer Science and Engineering, Jamia Hamdard, New Delhi 110062, India.
Sensors (Basel, Switzerland)
|July 27, 2022
Summary
This study introduces an efficient automatic license plate recognition (ALPR) system using YOLOv5, ideal for IoT devices. The novel approach achieves high accuracy and speed, making advanced ALPR accessible on resource-constrained hardware.
Area of Science:
- Computer Science
- Artificial Intelligence
- Machine Learning
Background:
- Deep learning advancements have spurred innovative license plate recognition systems.
- Current systems often demand significant computational resources, limiting their use on IoT devices.
- Automatic License Plate Recognition (ALPR) has diverse applications in traffic management and security.
Purpose of the Study:
- To propose a novel, memory and time-efficient ALPR system suitable for IoT devices.
- To develop an ALPR system using YOLOv5 that balances performance and resource consumption.
- To compare the performance of YOLOv5 against YOLOv4 for ALPR tasks.
Main Methods:
- Developed a two-stage ALPR system: custom transfer learned YOLOv5 for license plate detection and an LSTM-based OCR engine for recognition.
- Utilized a combined dataset including Google Open Images and Indian License Plates for training.
- Trained and compared YOLOv5 and YOLOv4 models on the same dataset.
Main Results:
- The proposed YOLOv5-based ALPR system achieved a mean average precision of 87.2% with a testing time of 4.8 ms per image (Nvidia T4 GPU).
- The complete system (detection and recognition) operates within 85 milliseconds.
- The resulting YOLOv5 model is compact, weighing only 14 megabytes.
Conclusions:
- The developed ALPR system offers a memory and time-efficient solution, suitable for deployment on resource-limited IoT devices.
- YOLOv5 demonstrates strong performance and efficiency for ALPR tasks compared to YOLOv4.
- This research contributes to making advanced ALPR technology more accessible and practical for various applications.
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