Study Of Convolutional Neural Network And Its Applications In License Plate Recognition

Artificial Neural Network(ANN) is a promising network. It simulates human being's cerebrum. Convolutional Neural Network(CNN) is one kind of them, which has the advantages of global solutions, good adaptability, high generalization ability and maturity in theory. Both ANN and CNN are hot spots in the field of machine learning nowadays. With the development of communication, information and electronic technology and computer network, License Plate Recognition System(LPR) attracts much more attentions.In this paper, we introduce CNN to the field of LPR. The main work is described as follows:(1) We summarize the latest research achievements and development of ANN, present the conceptions and the principles of it;(2) As one of ANN, CNN is studied in detail. We summarize the development and latest research achievements of it. Furthermore, we expatiate on its basic principles, analyze its structure and parameters.(3) Then we use CNN to settle the certain tasks. Firstly, we use it to solve the shape recognition problem. In the stage of test, the generalization ability of CNN is better than other methods. Secondly, CNN is used in the problem of license plate recognition. Because the gray of the region of license changes rapidly, we make use of this characteristic to locate the license first, and then vertical projection is used to segment the characters in this paper, in the stage of character recognition we adopt CNN method and the result is satisfied.