An Improved PSO-SVM Algorithm for License Plate Recognition

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%.