The research and design of vehicle license plate recognition system in traffic management system

Author(s):  
Ronghui Fu
2015 ◽  
Vol 734 ◽  
pp. 646-649
Author(s):  
Zhong Hua Hu ◽  
Chen Tang

The vehicle license plate recognition system is the intelligent traffic management system based on the image and the character recognition technology, which is an important part of the intelligent transportation system. This paper introduces a method of vehicle license plate location based on edge detection and morphological operations, virtual instrument is combined with machine vision of the license plate recognition method [1]. Finally the license plate number of the vehicle is get. Experiment results show that such method can simplify the algorithm and has some correct location rate.


2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Zhichao Wang ◽  
Yu Jiang ◽  
Jiaxin Liu ◽  
Siyu Gong ◽  
Jian Yao ◽  
...  

The license plate recognition is an important part of the intelligent traffic management system, and the application of deep learning to the license plate recognition system can effectively improve the speed and accuracy of recognition. Aiming at the problems of traditional license plate recognition algorithms such as the low accuracy, slow speed, and the recognition rate being easily affected by the environment, a Convolutional Neural Network- (CNN-) based license plate recognition algorithm-Fast-LPRNet is proposed. This algorithm uses the nonsegment recognition method, removes the fully connected layer, and reduces the number of parameters. The algorithm—which has strong generalization ability, scalability, and robustness—performs license plate recognition on the FPGA hardware. Increaseing the depth of network on the basis of the Fast-LPRNet structure, the dataset of Chinese City Parking Dataset (CCPD) can be recognized with an accuracy beyond 90%. The experimental results show that the license plate recognition algorithm has high recognition accuracy, strong generalization ability, and good robustness.


2014 ◽  
Vol 556-562 ◽  
pp. 2623-2627
Author(s):  
Feng Ran ◽  
Fa Yu Zhang ◽  
Mei Hua Xu

Introduce a complete system of license plate recognition: using morphological processing and priori knowledge of license plate to discern the location of license plate, accomplishing tilt correction through Radon transform, then fulfilling character segmentation of accurate positioning license plate by projection, finishing character recognition through BP neural network which was improved by the use of adaptive learning rate and momentum factor. With the programming and verification on Matlab experimental platform, experimental results show that we can have a preferable recognition speed and accuracy.


Author(s):  
Weifang Zhai ◽  
Terry Gao ◽  
Juan Feng

The license plate recognition technology is an important part of the construction of an intelligent traffic management system. This paper mainly researches the image preprocessing, license plate location, and character segmentation in the license plate recognition system. In the preprocessing part of the image, the edge detection method based on convolutional neural network (CNN) is used for edge detection. In the design of the license plate location, this paper proposes a location method based on a combination of mathematical morphology and statistical jump points. First, the license plate area is initially located using mathematical morphology-related operations and then the location of the license plate is accurately located using statistical jump points. Finally, the plate with tilt is corrected. In the process of character segmentation, the border and delimiter are first removed, then the character vertical projection method and the character boundary are used to segment the character for actually using cases.


Computer ◽  
2015 ◽  
Vol 48 (8) ◽  
pp. 56-61 ◽  
Author(s):  
Hitesh Rajput ◽  
Tanmoy Som ◽  
Soumitra Kar

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