The week's pick
Reseach Article
License Plate Recognition System based on Improved BP Neural Network
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 176 - Number 21 |
| Year of Publication: 2020 |
| Authors: Tingyu Ma, Tao Wang, Jinchao Shi |
10.5120/ijca2020920204
|
Tingyu Ma, Tao Wang, Jinchao Shi . License Plate Recognition System based on Improved BP Neural Network. International Journal of Computer Applications. 176, 21 ( May 2020), 27-34. DOI=10.5120/ijca2020920204
Abstract
With the increase in the number of vehicles, the license plate recognition system has gradually become a hot spot in scientific research. In this paper, we address the shortcomings of BP neural networks and combine it with the image processing technology of license plate characters, propose a license plate recognition system based on improved BP neural network for license plate recognition. The system mainly includes four modules: license plate image preprocessing, license plate positioning, character segmentation and classification recognition. Firstly, image preprocessing is implemented through image graying, gray stretching, and image binarization. Secondly, edge detection and morphological processing are used to determine the license plate area. Thirdly, the character string of the license plate is segmented. Finally, two corresponding BP neural networks are designed to classify and recognize the license plate characters based on the characteristics of the license plates in China to obtain the recognition results.
References
- Guo, K.X., Wang, G.W.（2010）. License plate location algorithm based on dynamic HSV threshold. Big technology· Technology World:116-119.
- Wu, Y.J., Liu, S.X., Wang. (2013). License plate location method based on texture and color. IEEE、IEEE Beijing Section. Proceedings of 2013 IEEE 4th International Conference on Software Engineering and Service Science. IEEE、IEEE Beijing Section: IEEE BEIJING SECTION.
- Yang, C.X., Zhang, Z.H. (2019). Research on License Plate Recognition Algorithm Based on Particle Swarm Optimization. Journal of Guizhou University (Natural Science Edition), 36(06),42-45.
- Li, Y.W., Tong, J.Y., Hu, X.D., Zhang, C.B., Li, H.L. (2018). Automatic license plate recognition based on BP neural network algorithm. Industrial control computer.
- Wang, X.F. (2019). Research on License Plate Detection and Recognition Based on Deep Learning. Nanjing University of Posts and Telecommunications.
- Wu, S.W. (2019). Study the main technologies and application prospects of artificial intelligence in the field of transportation. Communication World.
- Yu, X.Y., Zhang, Y., Xu, Y. (2020). A Canny algorithm with improved adaptive threshold. Machinery and Electronics.
- Huang, Y.G., Zhang, Y.S. (2020). Handwritten digit recognition system based on BP neural network. Electromechanical Engineering Technology.
- Cheng, D., Lu, H.C., Gao, W.G. (2019). License Plate Location Algorithm Based on Improved Canny Operator Edge Detection and Mathematical Morphology. Journal of Heilongjiang Institute of Technology.
- Ministry of Public Security of the People's Republic of China. (2014).GA36-2014 The People's Republic of China Motor Vehicle License Plate Public Safety Industry Standard.
- Qiu, W. (2018). Research on Character Recognition of License Plate Based on GABP Neural Network. Jilin University.
- Yin, G.G. (2019). Study on the Number of Hidden Layer Nodes in Neural Network. Dalian University of Technology.
- Wang, R.B., Xu, H.Y., Li, B., Feng, Y. (2017). Research on the Method of Determining the Number of Hidden Layer Nodes in BP Neural Network. Computer Technology and Development.
- Shen, J. (2013). Research on License Plate Recognition Technology Based on BP Neural Network. Hebei University of Technology.
- Yang, W.L., Xiao, C.W. (2019). An Algorithm Implementation of BP Network with Adaptive Momentum Factor. Computer and Digital Engineering.
- Chen, Z., Ding, S., Wang, J.L. (2015). BP Neural Network Model Prediction and Analysis of National Private Vehicle Ownership——BP Method Based on Combination of Additional Momentum and Adaptive Learning Rate. Journal of Xi'an University of Finance and Economic.
Index Terms
Keywords