DocumentCode
3310592
Title
Character Recognition System Based on Back-Propagation Neural Network
Author
Li, Fuliang ; Gao, Shuangxi
fYear
2010
fDate
24-25 April 2010
Firstpage
393
Lastpage
396
Abstract
According to the characteristics of vehicle license plate, recognition algorithm was proposed based on back-propagation (BP) neural network. Classifier was divided into Chinese characters classifier, English letters classifier, English letters and numbers mixed classifier, and digital classifier these four kinds of classifier in the algorithm. This neural network design can effectively simplify the network structure, improved recognition accuracy and speed. BP algorithm went along improvement as the defects of the standard BP algorithm which had slow convergence and easy to fall into local minimum points. Through simulation experiments, the character recognition system not only has a higher recognition rate, but also has better neural network robustness to decrease failures, that is having good robustness characteristics.
Keywords
Artificial neural networks; Backpropagation algorithms; Character recognition; Educational institutions; Feedforward neural networks; Licenses; Multi-layer neural network; Neural networks; Neurons; Vehicles; BP network; character recognition; ehicle license plate;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Vision and Human-Machine Interface (MVHI), 2010 International Conference on
Conference_Location
Kaifeng, China
Print_ISBN
978-1-4244-6595-8
Electronic_ISBN
978-1-4244-6596-5
Type
conf
DOI
10.1109/MVHI.2010.185
Filename
5532900
Link To Document