Open Access
ARTICLE
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:
Journal on Artificial Intelligence 2020, 2(4), 167-175. https://doi.org/10.32604/jai.2020.012716
Received 30 August 2020; Accepted 19 October 2020; Issue published 31 December 2020
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.
Keywords
Cite This Article
Z. Chen, L. Yan, S. Yin and Y. Shi, "Vehicle license plate recognition system based on deep learning in natural scene,"
Journal on Artificial Intelligence, vol. 2, no.4, pp. 167–175, 2020. https://doi.org/10.32604/jai.2020.012716