License Plate Recognition Algorithm Based on Radial Basis Function Neural Networks

• Published in: 2009 International Symposium on Intelligent Ubiquitous Computing and Education : 15-16 May 2009 pp. 38 - 41
• Main Author: Wang, Weihua
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.05.2009
• Subjects: classifier; license plate; License plate recognition; Monitoring; Neural networks; Pattern recognition; radial basis function; Radial basis function networks; recognition pattern; Sensor systems; Shape measurement; Target recognition; Vehicles
• ISBN: 9780769536194; 0769536190
• DOI: 10.1109/IUCE.2009.20

Automatic license plate recognition is an important form in the automatic target recognition. In recent years, there has a lot of research in license plate recognition, and many license plate recognition algorithms have been proposed and used. In this paper, a new license plate recognition approach is put forward based on the Radial Basis Function Neural Networks (RBFNN). Also discussed are the problem of feature of vehicle license plate feature, the input data pattern of the RBFNN, the architecture of the automatic recognition system, the problem of normalization of the image-size, and the problem of training algorithm of hidden layer's neural nodes. Experiments have been conducted for video monitored by vehicle monitor. The results show that compared with BP neural network, the RBF neural network can decrease the error recognition rate, the complexity of the system architecture, the training time, and the recognition time efficiently.