Vehicle Number Plate Detection and Categorization Using CNNs

This paper demonstrates the use of haar-clasifier and CNN to automatically detect number plates (Bangldeshi) from vehicles.

M. Atikuzzaman, M. Asaduzzaman and M. Z. Islam, "Vehicle Number Plate Detection and Categorization Using CNNs," 2019 International Conference on Sustainable Technologies for Industry 4.0 (STI), Dhaka, Bangladesh, 2019, pp. 1-5, doi: 10.1109/STI47673.2019.9068049.

Abstract:

Real-Time Vehicle Number Plate Recognition (ANPR) has been a recurrent subject of research study as a result of many real-world implementations. Yet, numerous of todayâs works are still not Full-bodied and consistent in real-world circumstances and rely on various constraints. Our proposed method to detect and recognize license plates in real-time that is particularly designed to work on videos captured by a camera. It is a distinct approach that is composed of three main phases like plate detection, class letter segmentation, and recognition. These phases are completed by adopting a HAAR Feature-based Classifier to detect license plate, class letter extractor with a proposed method, and Convolution Neural Network for recognizing class letters. Our given method achieved captivating results in our collected dataset. Our dataset composed of 5500 license plates and it achieved a successful recognition rate of 91.38% with approximately 30 frames/second. We evaluate our License Plate Detection system performance with 390 test images and we get 96.92% accuracy and Class Letter Segmentation has achieved 94.61% with the same size of data. We achieved an overall successful recognition rate of 90.90% with real-time performance.

URL: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9068049&isnumber=9067972

Dataset used: Download Dataset

Demo Vehicle Number Plate detection and Categorization:

Cite This:

M. Atikuzzaman, M. Asaduzzaman and M. Z. Islam, "Vehicle Number Plate Detection and Categorization Using CNNs," 2019 International Conference on Sustainable Technologies for Industry 4.0 (STI), Dhaka, Bangladesh, 2019, pp. 1-5, doi: 10.1109/STI47673.2019.9068049.

Or

@INPROCEEDINGS{atikuzzaman2019vehicle, author={M. {Atikuzzaman} and M. {Asaduzzaman} and M. Z. {Islam}}, booktitle={2019 International Conference on Sustainable Technologies for Industry 4.0 (STI)}, title={Vehicle Number Plate Detection and Categorization Using CNNs}, year={2019}, volume={}, number={}, pages={1-5}, doi={10.1109/STI47673.2019.9068049}}