Radial Wavelet Neural Network with a Novel Self-Creating Disk-Cell-Splitting Algorithm for License Plate Character Recognition

Entropy

Rong Cheng¹  Yanping Bai¹  Hongping Hu¹  Xiuhui Tan¹ 

[1] School of Science, North University of China, Taiyuan 030051, Shanxi, China; E-Mails:

关键词: radial wavelet neural network;    self-creating disk-cell-splitting;    character recognition;   

DOI  :  10.3390/e17063857

来源: mdpi

【 摘 要 】

In this paper, a novel self-creating disk-cell-splitting (SCDCS) algorithm is proposed for training the radial wavelet neural network (RWNN) model. Combining with the least square (LS) method which determines the linear weight coefficients, SCDCS can create neurons adaptively on a disk according to the distribution of input data and learning goals. As a result, a disk map is made for input data as well as a RWNN model with proper architecture and parameters can be decided for the recognition task. The proposed SCDCS-LS based RWNN model is employed for the recognition of license plate characters. Compared to the classical radial-basis-function (RBF) network with K-means clustering and LS, the proposed model can make a better recognition performance even with fewer neurons.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland