Currency characteristic extraction and identification research based on PCA and BP neural network

被引：3

作者：

Cao, Bu-Qing ^{[1
]}

Liu, Jian-Xun ^{[1
]}

Wen, Bin ^{[2
]}

机构：

[1] School of Computer Science and Engineering, Key Laboratory of Knowledge Management and Network-based Manufacture, Hunan University of Science and technology, Xiangtan

[2] School of Information Science and Technology, Hainan Normal University, Haikou

来源：

Journal of Convergence Information Technology | 2012年 / 7卷 / 02期

关键词：

BP; Currency identification; PCA;

D O I：

10.4156/jcit.vol7.issue2.5

中图分类号：

学科分类号：

摘要：

In recent years, Principle Component Analysis is an extraction method for statistics characteristic, which has been more researched and widely used in the signal processing, pattern recognition, digital image processing and other fields. This paper mainly describe that original currency characteristic vectors will be carried the linear transform by Principle Component Analysis Method, and then reduced-dimension original currency characteristic vector is automatically classified by BP Neural Networks, and finally identification research experiment is made for different kinds of currency,such as 1 yuan, 5 yuan, 10 yuan and 20 yuan. The experiment results indicate that currency characteristic extraction and identification algorithm based on Principle Component Analysis and BP neural network has higher identification rate and better identification effect.

引用

页码：38 / 44

页数：6

共 12 条

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