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Vehicle License Plate Recognition System Based on Deep Learning in Natural Scene

Ze Chen, Leiming Yan*, Siran Yin, Yuanmin Shi

School of Computer & Software, Nanjing University of Information Science & Technology, Engineering Research Center of Digital Forensics, Ministry of Education, Nanjing, China

* Corresponding Author: Leiming Yan. Email: email

Journal on Artificial Intelligence 2020, 2(4), 167-175. https://doi.org/10.32604/jai.2020.012716

Abstract

With the popularity of intelligent transportation system, license plate recognition system has been widely used in the management of vehicles in and out of closed communities. But in the natural environment such as video monitoring, the performance and accuracy of recognition are not ideal. In this paper, the improved Alex net convolution neural network is used to remove the false license plate in a large range of suspected license plate areas, and then the projection transformation and Hough transformation are used to correct the inclined license plate, so as to build an efficient license plate recognition system in natural environment. The proposed system has the advantages of removing interference objects in a large area and accurately locating the license plate. The experimental results show that the localization success rate is 98%, and our system is feasible and efficient.

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APA Style
Chen, Z., Yan, L., Yin, S., Shi, Y. (2020). Vehicle license plate recognition system based on deep learning in natural scene. Journal on Artificial Intelligence, 2(4), 167-175. https://doi.org/10.32604/jai.2020.012716
Vancouver Style
Chen Z, Yan L, Yin S, Shi Y. Vehicle license plate recognition system based on deep learning in natural scene. J Artif Intell . 2020;2(4):167-175 https://doi.org/10.32604/jai.2020.012716
IEEE Style
Z. Chen, L. Yan, S. Yin, and Y. Shi "Vehicle License Plate Recognition System Based on Deep Learning in Natural Scene," J. Artif. Intell. , vol. 2, no. 4, pp. 167-175. 2020. https://doi.org/10.32604/jai.2020.012716



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