Abstract
Aiming at the problems of low accuracy of low resolution license plate recognition and long time consuming of recognition and registration in traditional methods, this paper proposes a low resolution license plate recognition method based on intelligent data processing and prediction algorithm. Firstly, the low resolution license plate is located, and the low resolution digital image of license plate is defined by the principle of image registration; Secondly, the doc scale space is constructed to determine the Gaussian pyramid and Gaussian difference pyramid model of low resolution license plate, and the RANSAC prediction algorithm is used to eliminate the mismatching of low resolution license plate and realize low resolution license plate recognition. The experimental results show that the proposed method can achieve fast recognition accuracy and recall rate of low resolution license plate, and the recognition time is low.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Zhu, Q., Liu, S., Guo, W.: Research on license plate detection based on FASTERR-CNN. Auto Ind. Res. 296(01), 59–62 (2019)
Tang, Y.: License plate recognition algorithm based on fusion of gradient operator and mathematical morphology. Electron. Technol. Softw. Eng. 187(17), 130–131 (2020)
Zheng, G., Wu, H.: Method of license plate location based on MSER feature and edge projection. Comput. Eng. Des. 40(01), 249–252 (2019)
Liu, N., Zhang, J.: Chinese license plate recognition system based on Haar features. J. Jimei Univ. (Nat. Sci.) 24(2), 139–144 (2019)
Wang, Z., Ma, X., Huang, W.: Vehicle license plate recognition based on wavelet transform and vertical edge matching. Int. J. Pattern Recognit. Artif. Intell. 34(06), 1134–1142 (2020)
Sathya, K.B., Vasuhi, S., Vaidehi, V.: Perspective vehicle license plate transformation using deep neural network on genesis of CPNet. Procedia Comput. Sci. 171(1), 1858–1867 (2020)
Onim, M., Akash, M.I., Haque, M., et al.: Traffic surveillance using vehicle license plate detection and recognition in Bangladesh (2020)
Swastika, W., Sakti, E., Subianto, M.: Vehicle images reconstruction using SRCNN for improving the recognition accuracy of vehicle license plate number. Jurnal Teknologi dan Sistem Komputer 8(4), 304–310 (2020)
Islam, R., Islam, M.R., Talukder, K.H.: An efficient method for extraction and recognition of Bangla characters from vehicle license plates. Multimed. Tools Appl. 79(27), 20107–20132 (2020)
Al-Shemarry, M.S., Li, Y., Abdulla, S.: An efficient texture descriptor for the detection of license plates from vehicle images in difficult conditions. IEEE Trans. Intell. Transp. Syst. 21(2), 553–564 (2020)
Liu, S., Liu, G., Zhou, H.: A robust parallel object tracking method for illumination variations. Mob. Netw. Appl. 24(1), 5–17 (2019)
Liu, S., Fu, W., He, L., Zhou, J., Ma, M.: Distribution of primary additional errors in fractal encoding method. Multimed. Tools Appl. 76(4), 5787–5802 (2014). https://doi.org/10.1007/s11042-014-2408-1
Liu, S., Bai, W., Liu, G., et al.: Parallel fractal compression method for big video data. Complexity 20(18), 1–16 (2018)
Luo, L.Z., Fei W.U., Cao, K., et al.: Application of image super-resolution in fuzzy license plate recognition system. Softw. Guide 18(05), 177–180+186 (2019)
Hu, X., Li, X.S., Li, Y., et al.: Research and implementation of blind restoration algorithm for moving fuzzy license plate image based on frequency-domain characteristics. Int. J. Pattern Recogn. Artif. Intell. 25(6), 36–40 (2021)
Chowdhury, M., Dhar, P.: License plate detection based on fuzzy rule. Int. J. Adv. Sci. Technol. 29(9), 8583–8590 (2020)
Funding
1. Project name: incomplete license plate recognition study based on generative adversarial network, project number: KJQN201905503
2. Project name: The work was supported by the Science and Technology Research Program of Chongqing Municipal Education Commission, project number: KJZD-K201801901
3. Project name: research and design of intelligent manufacturing cloud platform system based on Internet of things, project number: KJQN201801902.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Meng, M., He, Ch. (2022). Low Resolution License Plate Recognition Based on Intelligent Data Processing and Prediction Algorithm. In: Wang, S., Zhang, Z., Xu, Y. (eds) IoT and Big Data Technologies for Health Care. IoTCare 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 414. Springer, Cham. https://doi.org/10.1007/978-3-030-94185-7_24
Download citation
DOI: https://doi.org/10.1007/978-3-030-94185-7_24
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-94184-0
Online ISBN: 978-3-030-94185-7
eBook Packages: Computer ScienceComputer Science (R0)