文章基本信息

标题：Banknote Image Defect Recognition Method Based on Convolution Neural Network
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作者：Wang Ke ; Wang Huiqin ; Shu Yue 等
期刊名称：International Journal of Security and Its Applications
印刷版ISSN：1738-9976
出版年度：2016
卷号：10
期号：6
页码：269-280
DOI：10.14257/ijsia.2016.10.6.26
出版社：SERSC
摘要：There are shortcomings in the currently used traditional CCD imaging system which can automatically recognize banknote image defect, such as the need to manually extract the defect characteristics and low accuracy rate of detection results. This paper briefly introduced the advantage of convolution Neural Network (CNN) in image classification and designed a image defect identification method based on convolutional neural network (CNN). The experimental results on data sets show that the identification accuracy rate of this method is 95.6%, which is significantly better than traditional identification method.
关键词：Convolution Neural Network; Defect Recognition; Banknote Image; Deep- ; learning