@Article{jai.2020.012716,
AUTHOR = {Ze Chen, Leiming Yan, Siran Yin, Yuanmin Shi},
TITLE = {Vehicle License Plate Recognition System Based on Deep Learning in Natural  Scene},
JOURNAL = {Journal on Artificial Intelligence},
VOLUME = {2},
YEAR = {2020},
NUMBER = {4},
PAGES = {167--175},
URL = {http://www.techscience.com/jai/v2n4/41106},
ISSN = {2579-003X},
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.},
DOI = {10.32604/jai.2020.012716}
}