[Project] End-to-End Real-Time ALPR System
January 2019 - September 2021
Affiliation: Research Software Engineer at GSTP, Rasht, Iran
Target Audience: Traffic Law Enforcement, Smart Toll Booths, & Secured Parking Systems, Rasht, Iran
Project Ecosystem: GitHub | Dataset | Paper#1 | Paper#2 | Paper#3 | Paper#4
- Robust End-to-End License Plate Recognition: production-ready Intelligent Transportation asset comprising a high-speed ALPR system.
- Open-Source Dataset: the largest specialized open-source dataset for Persian alphanumeric OCR with 83,000+ instances.
- Linguistic Nuance Localization: tuned to recognize non-standard variations, syntax arrangements, and individual alphanumeric properties unique to Iranian state vehicle identification codes.
- 💡 Stack: Python, OpenCV, YOLO, Keras, TensorFlow
A. Tourani, A. Shahbahrami, S. Soroori, S. Khazaee and C. Y. Suen,
"A Robust Deep Learning Approach for Automatic Iranian Vehicle License Plate Detection and
Recognition for Surveillance Systems,"
IEEE Access, pp. 201317-201330, 2020.
DOI: 10.1109/ACCESS.2020.3035992
DOI: 10.1109/ACCESS.2020.3035992
S. Khazaee, A. Tourani, S. Soroori, A. Shahbahrami, and C. Y. Suen,
"A Real-Time License Plate Detection Method Using a Deep Learning Approach,"
International Conference on Pattern Recognition and Artificial Intelligence (ICPRAI),,
Springer Lecture Notes in Computer Science, vol. 12068, pp. 425-438, 2020.
DOI: 10.1007/978-3-030-59830-3_37
DOI: 10.1007/978-3-030-59830-3_37
A. Tourani, S. Soroori, A. Shahbahrami, S. Khazaee, and C. Y. Suen,
"An Accurate Real-Time License Plate Detection Method Based On Deep Learning Approaches,"
International Journal of Pattern Recognition and Artificial Intelligence, vol. 35, no. 12,
p. 2160008, 2021.
DOI: 10.1142/S0218001421600089
DOI: 10.1142/S0218001421600089
A. Tourani, S. Soroori, A. Shahbahrami, and A. Akoushideh,
"Iranis: A Large-scale Dataset of Iranian Vehicles License Plate Characters,"
5th International Conference on Pattern Recognition and Image Analysis (IPRIA), pp.
1-5, Kashan, Iran, 2021.
DOI: 10.1109/IPRIA53572.2021.9483461
DOI: 10.1109/IPRIA53572.2021.9483461