Automatic System Recognition of License Plates using Neural Networks
Автор: Kalid A.Smadi, Takialddin Al Smadi
Журнал: International Journal of Engineering and Manufacturing(IJEM) @ijem
Статья в выпуске: 4, 2017 года.
Бесплатный доступ
The urgency to increase the efficiency of recognition of car number plates on images with a complex background need the development of methods, algorithms and programs to ensure high efficiency, To solve the task the author has used the methods of the artificial Intelligence, identification and pattern recognition in images, theory of artificial neural networks, convolution neural networks, evolutionary algorithms, mathematical modeling and models characters were then statistics by using feed forward back propagated multi layered perception neural networks.. The proposed this work is to show a system that solves the practical problem of car identification for real scenes. All steps of the process, from image acquisition to optical character recognition are considered to achieve an automatic identification of plate.
Automatic System, Neural Networks, Recognition, of license plates
Короткий адрес: https://sciup.org/15014444
IDR: 15014444
Список литературы Automatic System Recognition of License Plates using Neural Networks
- Al Smadi, T.A. Computing Simulation for Traffic Control over Two Intersections, Journal of Advanced Computer Science and Technology Research 1 (2011) 10-24. https://www.sign-ific-ance.co.uk/index.php/JACSTR/article/viewFile/379/382
- Sonka, Milan, Vaclav Hlavac, and Roger Boyle. Image processing, analysis, and machine vision. Cengage Learning, 2014.
- Ibrahim, Nuzulha Khilwani, et al. "License plate recognition (LPR): a review with experiments for Malaysia case study." arXiv preprint arXiv: 1401.5559 (2014).
- Yan, Jianqiang, Jie Li, and Xinbo Gao. "Chinese text location under complex background using Gabor filter and SVM." Neurocomputing 74.17 (2011): 2998-3008.
- Wang, Runmin, et al. "License plate detection using gradient information and cascade detectors." Optik-International Journal for Light and Electron Optics125.1 (2014): 186-190.
- Uchida, Seiichi. "Text localization and recognition in images and video."Handbook of Document Image Processing and Recognition. Springer London, 2014. 843-883.
- Das, Kaushik, Dipjyoti Pathak, and Asish Datta. "Number Plate Recognition and Number Identification-A Survey." Communication, Cloud and Big Data: Proceedings of CCB 2014 (2014).
- Ashtari, Amir Hossein, Md Jan Nordin, and Mahmood Fathy. "An Iranian License Plate Recognition System Based on Color Features." (2014): 1-16.
- Giannoukos, Ioannis, et al. "Operator context scanning to support high segmentation rates for real time license plate recognition." Pattern Recognition43.11 (2010): 3866-3878.
- Sedighi, Amir, and Mansur Vafadust. "A new and robust method for character segmentation and recogni-tion in license plate images." Expert Systems with Applications 38.11 (2011): 13497-13504.
- Ibrahim, Nuzulha Khilwani, et al. "License plate recognition (LPR): a review with experiments for Malaysia case study." arXiv preprint arXiv: 1401.5559 (2014).
- Al-Hmouz, Rami, and Khalid Aboura. "License plate localization using a statistical analysis of Discrete Fourier Transform signal." Computers & Electrical Engineering 40.3 (2014): 982-992.
- Al Smadi, T.A. Design and Implementation of Double Base Integer Encoder of Term Metrical to Direct Binary, Journal of Signal and Information Processing, 4, 370. (2013) http://dx.doi.org/10.4236/jsip.2013.44047
- Takialddin Al Smadi Int. An Improved Real-Time Speech Signal in Case of Isolated Word Recognition. Journal of Engineering Research and Applications, 3, 1748-1754. http://www.ijera.com/papers/Vol3_issue5/KC3517481754.pdf
