DocumentCode :
2146117
Title :
A Vehicle License Plate Recognition Method Based on Neural Network
Author :
Zhang, Xing-Wang ; Liu, Xian-Gui ; Zhao, Jia
Author_Institution :
Nanchang Inst. of Technol., Nanchang, China
fYear :
2010
fDate :
14-16 Aug. 2010
Firstpage :
845
Lastpage :
847
Abstract :
It is of great significance how to identify car licence rapidly and accurately in the modern urban traffic management system. Hopfield NN is a feedback network with association function. It can figure out the weight of network according to some rules and update every nerve cell´s state constantly in curse of the network evolvement. This paper presents a method identifying noise of vehicle license plate with dispersed Hopfield NN programming calculating and simulating in MATLAB and that validating the method correct. It provides a new fast and effective method for the vehicle licence identification.
Keywords :
Hopfield neural nets; character recognition; road traffic; road vehicles; traffic engineering computing; MATLAB; association function; feedback network; hopfield NN; nerve cell state; network evolvement; neural network; urban traffic management system; vehicle license plate recognition; Artificial neural networks; Hopfield neural networks; Licenses; MATLAB; Mathematical model; Noise; Vehicles; Neural Network; Recognition; Vehicle License Plate;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Granular Computing (GrC), 2010 IEEE International Conference on
Conference_Location :
San Jose, CA
Print_ISBN :
978-1-4244-7964-1
Type :
conf
DOI :
10.1109/GrC.2010.126
Filename :
5576100
Link To Document :
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