DocumentCode :
2498040
Title :
Based on Particle Swarm Optimization real-time license plate recognition
Author :
Zhou, Yan ; Duan, Qichang
Author_Institution :
Chongqing Univ., Chongqing
fYear :
2008
fDate :
25-27 June 2008
Firstpage :
7747
Lastpage :
7750
Abstract :
The traditional plate character recognition algorithm for the low recognition rate and identify the shortcomings of slow, the paper used PSO algorithm optimization neural network weights and threshold parameters, resulting in greatly improved the license plate character recognition rate and Recognition speed. The experimental results indicate that the PSO algorithm optimized for real-time neural network license plate recognition, the correct identification rate of 99 percent and above, the recognition time is 0.27 s, and the recognition rate and recognition speed is superior to other traditional identification methods, and basically meet the requirements of the application.
Keywords :
character recognition; neural nets; object recognition; particle swarm optimisation; traffic engineering computing; character recognition; license plate recognition; neural network; particle swarm optimization; Artificial intelligence; Artificial neural networks; Automation; Character recognition; Helium; Intelligent control; Licenses; Neural networks; Optimization methods; Particle swarm optimization; Artificial Neural Network (ANN); Particle Swarm Optimization; Real-Time License Plate Recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4244-2113-8
Electronic_ISBN :
978-1-4244-2114-5
Type :
conf
DOI :
10.1109/WCICA.2008.4594135
Filename :
4594135
Link To Document :
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