Persian Banknote Recognition Using Wavelet and Neural Network

摘要：

In this paper a new Persian banknote recognition system using wavelet transform and neural network has been proposed. The required images for the selected banknotes are obtained using a scanner. The color images are first converted to gray scale images, and then the discrete wavelet transform (I)WT) is applied on the selected images and features are extracted. Finally, a multi layered Perceptron (MLP) Neural Network (NN) is presentedto classify eight classes of interest, which are 50, 100, 200, 500, 1000, 2000, 5000 and 10000 toman notes. The system was implemented and tested using a data set of 320 samples of Persian banknotes; 40 images for each sign (from both sides). The experiments showed excellent classification results. The system was able to recognize more than 99％ of all data, correctly.

关键词： Persian banknote pattern recognition wavelet transform neural network

作者: F.PoorAhangaryan T.Mohammadpour A.kianisarkaleh

作者单位: Sama technical and vocational training college Islamic Azad University, Tonekabon Branch Tonekabon,Iran

会议类型: 国际会议

会议名称: 2012 International Conference on Computer Science and Electronic Engineering(2012 IEEE计算机科学与电子工程国际会议 ICCSEE 2012)

会议地点: 杭州

会议语种:英文

页码: 679-684

在线出版日期: 2012-03-23（万方平台首次上网日期，不代表论文的发表时间）