Automatic recognition of serial numbers in bank notes
Feng, Bo-Yuan1; Ren, Mingwu1; Zhang, Xu-Yao2; Suen, Ching Y.3
2014-08-01
发表期刊PATTERN RECOGNITION
卷号47期号:8页码:2621-2634
文章类型Article
摘要This paper presents a new topic of automatic recognition of bank note serial numbers, which will not only facilitate the prevention of forgery crimes, but also have a positive impact on the economy. Among all the different currencies, we focus on the study of RMB (renminbi bank note, the paper currency used in China) serial numbers. For evaluation, a new database NUST-RMB2013 has been collected from scanned RMB images, which contains the serial numbers of 35 categories with 17,262 training samples and 7000 testing samples in total. We comprehensively implement and compare two classic and one newly merged feature extraction methods (namely gradient direction feature, Gabor feature, and CNN trainable feature), four different types of well-known classifiers (SVM, LDF, MQDF, and CNN), and five multiple classifier combination strategies (including a specially designed novel cascade method). To further improve the recognition accuracy, the enhancements of three different kinds of distortions have been tested. Since high reliability is more important than accuracy in financial applications, we introduce three rejection schemes of first rank measurement (FRM), first two ranks measurement (FTRM) and linear discriminant analysis based measurement (LDAM). All the classifiers and classifier combination schemes are combined with different rejection criteria. A novel cascade rejection measurement achieves 100% reliability with less rejection rate compared with the existing methods. Experimental results show that MQDF reaches the accuracy of 99.59% using the gradient direction feature trained with gray level normalized data; the cascade classifier combination achieves the best performance of 99.67%. The distortions have been proved to be very helpful because the performances of CNNs boost at least 0.5% by training with transformed samples. With the cascade rejection method, 100% reliability has been obtained by rejecting 1.01% test samples. (C) 2014 Elsevier Ltd. All rights reserved.
关键词Bank Note Serial Number Recognition Cascade Rejection Synthetic Training Samples Multiple Classifier System
WOS标题词Science & Technology ; Technology
关键词[WOS]SUPPORT VECTOR MACHINES ; HANDWRITTEN DIGIT RECOGNITION ; CHARACTER-RECOGNITION ; FEATURE-EXTRACTION ; FILTERS
收录类别SCI
语种英语
WOS研究方向Computer Science ; Engineering
WOS类目Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS记录号WOS:000336341200005
引用统计
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/8019
专题模式识别国家重点实验室_模式分析与学习
作者单位1.Nanjing Univ Sci & Technol, Dept Comp Sci, Nanjing 210094, Jiangsu, Peoples R China
2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
3.Concordia Univ, Ctr Pattern Recognit & Machine Intelligence, Montreal, PQ H3G 1M8, Canada
推荐引用方式
GB/T 7714
Feng, Bo-Yuan,Ren, Mingwu,Zhang, Xu-Yao,et al. Automatic recognition of serial numbers in bank notes[J]. PATTERN RECOGNITION,2014,47(8):2621-2634.
APA Feng, Bo-Yuan,Ren, Mingwu,Zhang, Xu-Yao,&Suen, Ching Y..(2014).Automatic recognition of serial numbers in bank notes.PATTERN RECOGNITION,47(8),2621-2634.
MLA Feng, Bo-Yuan,et al."Automatic recognition of serial numbers in bank notes".PATTERN RECOGNITION 47.8(2014):2621-2634.
条目包含的文件
条目无相关文件。
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Feng, Bo-Yuan]的文章
[Ren, Mingwu]的文章
[Zhang, Xu-Yao]的文章
百度学术
百度学术中相似的文章
[Feng, Bo-Yuan]的文章
[Ren, Mingwu]的文章
[Zhang, Xu-Yao]的文章
必应学术
必应学术中相似的文章
[Feng, Bo-Yuan]的文章
[Ren, Mingwu]的文章
[Zhang, Xu-Yao]的文章
相关权益政策
暂无数据
收藏/分享
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。