A Classification Method for the Dirty Factor of Banknotes Based on Neural Network with Sine Basis Functions

摘要：

The classification on the dirty factor of the new and used banknotes is an important function of the note sorter. This paper proposes a classification method based on neural network with sine basis functions. The gray level histogram of banknote image is used as the characteristic vector to train the neural network. The classification effect is satisfying by this method.

作者: Kexue HE Shurong PENG Shutao Li

作者单位: College of Electrical and Information Engineering, Changsha University of Science & Technology, 4100 College of Electrical and Information Engineering, Hunan University 410082 Changsha, Hunan Province,

会议类型: 国际会议

会议名称: International Conference on Intelligent Computation Technology and Automation(2008 智能计算技术与自动化国际会议 ICICTA 2008)

会议地点: 长沙

会议语种:英文

页码: 159-162

在线出版日期: 2008-10-20（万方平台首次上网日期，不代表论文的发表时间）