Research on paper currency recognition based on neural networks and genetic algorithm

被引：0

作者：

Zhang, EH ^{[1
]}

Jiang, B ^{[1
]}

Zhang, ZG ^{[1
]}

Hu, T ^{[1
]}

Xue, YX ^{[1
]}

机构：

[1] Xian Univ Technol, Dept Informat Sci, Xian 710048, Peoples R China

来源：

ISTM/2005: 6TH INTERNATIONAL SYMPOSIUM ON TEST AND MEASUREMENT, VOLS 1-9, CONFERENCE PROCEEDINGS | 2005年

关键词：

currency recognition; neural networks; genetic algorithm; feature extraction; edge detecting;

D O I：

暂无

中图分类号：

TH7 [仪器、仪表];

学科分类号：

0804 ; 080401 ; 081102 ;

摘要：

Paper currency recognition is widely applied in bank and automatic selling-goods system. How to extract high quality monetary feature vectors is a key problem for currency recognition. Aiming at the specialties of RMB currency, the linear gray transformation is firstly used to diminish the influence of background pattern and then use the simple statistics method to get binary image. By dividing the image in the width direction into different areas, getting the number of the edge pixels of different areas as input vectors to neural networks. The genetic algorithm with random mask is used to optimize the input vectors, carrying out sorting recognition by three layer BP neural networks. By experimental tests, the recognition rates for five kinds of RMB are all 100%.

引用

页码：1178 / 1181

页数：4

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