An Improved PSO-SVM Algorithm for License Plate Recognition
Mathematics and Computer Science
Volume 1, Issue 1, May 2016, Pages: 1-4
Received: Mar. 7, 2016; Accepted: Mar. 16, 2016; Published: Apr. 10, 2016
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Authors
Weichao Jiao, College of Mathematic and Information, China West Normal University, Nanchong Sichuan, China
Junfei Dong, College of Mathematic and Information, China West Normal University, Nanchong Sichuan, China
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Abstract
Support vector machine is a machine learning algorithm with good performance, its parameters have an important influence on accuracy of classification, and parameters selection is becoming one of the main research areas of machine learning. This paper adopt support vector machine to recognize the characters of license plate. But in order to get good parameters of support vector machine, this paper has proposed a modified particles warm optimization algorithm to obtain the parameters of support vector machine. Experiments show that the proposed algorithm has higher recognition accuracy than others, the character recognition accuracy of training set is 99.95%, and character recognition accuracy of test set reaches 98.87%.
Keywords
Support Vector Machine, Particle Swarm Optimization Algorithm, Parameter Optimization, Character Recognition
To cite this article
Weichao Jiao, Junfei Dong, An Improved PSO-SVM Algorithm for License Plate Recognition, Mathematics and Computer Science. Vol. 1, No. 1, 2016, pp. 1-4. doi: 10.11648/j.mcs.20160101.11
Copyright
Copyright © 2016 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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