点钞机关键技术的研究及实施
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摘要
在市场经济高速发展的今天,纸币在市场流通领域扮演着一个重要的角色,而随着技术的发展,假币也越来越猖獗,假币的制作水平也越来越高。出现的某些新假币需要对原有系统进行改进才能有效识别。同时国家对流通人民币的新旧程度提出更高要求。
本文首先对纸币防伪原理进行了分析,选用了红外透射、荧光反应、安全线、磁分布等防伪手段,并对防伪手段进行了比较分析,选择了相应的传感器。以单片机作为处理器,设计了硬件和软件系统,实现了点钞、验钞功能。在此基础上针对市场上目前识别难度较高的假币进行了红外数据的采集与分析,确定了真币和假币的分界点。为识别假币提供了一个有效的方法。
图像识别技术的引入是为了对残损纸币和过旧纸币进行识别。针对残损纸币和新旧纸币的图像特征进行了分析,采用了直方图和阈值分割的方法进行了图像的处理,找到处理后图像的特点,确定有效数值体现纸币的新旧程度和残损级别。
As the China society’s rapid development, paper currency plays an important role in our market-economy. More and more spurious ones follow, too. The level of making false paper currency also improves. Some of the counterfeit paper currency made by modern technology can hardly identified. The cash counter need to be improved. Also the government requests the paper currency in use to maintain a certain degree of quality.
Firstly, a cash counter is designed and the identify methods are analyzed. After analyze the Anti-counterfeiting techniques of paper currency, we select infrared transmission technology, fluorescence response technology, safe-line technology and magnetism distributing to identify counterfeit paper currency. The sensors are selected. Hardware and software of control system is designed based on single chip computer, realize the functions of cash count and cash check. We use the machine been designed to collect some infrared transmission data of counterfeit paper currency that is difficult to recognize. After analyze the collected data of infrared transmission, the dividing line between real RMB and counterfeit RMB is founded. It makes the system works effectively.
As the paper currency in use has to be at certain degree of quality, the graph recognizes technology is inducted. There are two kinds of paper currency need to be callback, the broken ones and the old ones. To identify these two kinds of paper currency, use histogram and threshold image segmentation to analyze the image of these paper currencies. An effective way is discovered by find the character of processed image.
本文首先对纸币防伪原理进行了分析,选用了红外透射、荧光反应、安全线、磁分布等防伪手段,并对防伪手段进行了比较分析,选择了相应的传感器。以单片机作为处理器,设计了硬件和软件系统,实现了点钞、验钞功能。在此基础上针对市场上目前识别难度较高的假币进行了红外数据的采集与分析,确定了真币和假币的分界点。为识别假币提供了一个有效的方法。
图像识别技术的引入是为了对残损纸币和过旧纸币进行识别。针对残损纸币和新旧纸币的图像特征进行了分析,采用了直方图和阈值分割的方法进行了图像的处理,找到处理后图像的特点,确定有效数值体现纸币的新旧程度和残损级别。
As the China society’s rapid development, paper currency plays an important role in our market-economy. More and more spurious ones follow, too. The level of making false paper currency also improves. Some of the counterfeit paper currency made by modern technology can hardly identified. The cash counter need to be improved. Also the government requests the paper currency in use to maintain a certain degree of quality.
Firstly, a cash counter is designed and the identify methods are analyzed. After analyze the Anti-counterfeiting techniques of paper currency, we select infrared transmission technology, fluorescence response technology, safe-line technology and magnetism distributing to identify counterfeit paper currency. The sensors are selected. Hardware and software of control system is designed based on single chip computer, realize the functions of cash count and cash check. We use the machine been designed to collect some infrared transmission data of counterfeit paper currency that is difficult to recognize. After analyze the collected data of infrared transmission, the dividing line between real RMB and counterfeit RMB is founded. It makes the system works effectively.
As the paper currency in use has to be at certain degree of quality, the graph recognizes technology is inducted. There are two kinds of paper currency need to be callback, the broken ones and the old ones. To identify these two kinds of paper currency, use histogram and threshold image segmentation to analyze the image of these paper currencies. An effective way is discovered by find the character of processed image.
引文
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[16] 陈树根,江和平,周高杯.基于荧光光谱分析的钞票识别研究[J].红外与激光工程.2001,8.177~179
[17] Atmel Corporation.8Bit Microcontroller with 8K bytes In-system Programmable Flash AT89S52.2001
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[19] 党国顺.人民币研究[J].西安金融.2002,10.58~63
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[23] 刘豹.现代控制理论[M].机械工业出版社.2000,5.64~72
[24] 李俊儒.两钞口纸币清分机软件系统的设计与实现[D].哈尔滨工业大学硕士论文.2006
[25] 付小全.低分辨率下纸币的识别与污损检测[D].哈尔滨工业大学硕士论文.2006
[26] 罗浩斐.纸币清分机图像处理系统的研究[D].浙江大学硕士论文.2005
[27] 娄小冬.智能纸币清分机系统设计及其实现策略研究[D].浙江大学硕士论文.2005
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[29] 朱秀昌,刘峰,胡栋.数字图像处理与图像通信[M].北京邮电大学出版社.2002.16~20
[30] 方子文,沈庭芝.数字图像处理及模式识别[M].北京理工大学出版社.1998
[31] Takeda F,Nishikage T,Matsumoto Y.Characteristics extraction of paper currency using symmetrical masks optimized by GA and neuro-recognition of multi-national paper currency Neural Networks Proceedings.1998.IEEE World Congress on Computational Intelligence.The1998 IEEE International Joint Conference on,Volume1,4-9 May 1998.634~639
[32] Aauro Barini,Rossana Gualtieri.A new possibalistic clustering algorithm for line detection in real world image. Pattern Recognition, Vo1.32, No.ll,Nov.1999
[33] J.Illing Worth,J.Kittler.A Survey of the Hough transform.Computer Vision and Image Process, 1988.87~116
[34] VF. Leavers.Which Hough Transform.Compute Vision and Image Process.1993
[35] 罗 军 辉 , 冯 平 . Matlab7.0 在 图 像 处 理 中 的 应 用 [M] . 机 械 工 业 出 版社.2005.169~192
[36] 诸静.图像边缘检测和图像匹配研究及应用[D].浙江大学博士论文.2003.7~8
[37] 姜长生.基于神经网络的目标图像识别方法研究[D].南京航空航天大学硕士论文.2004.3~7
[38] 张桂林.基于主成分分析的图像识别方法研究[D].华中科技大学硕士论文,2002. 5~6
[39] 高品贤.数字图像识别在测控系统中的应用[D].西南交通大学硕士论文.2002.20~21
[2] 刘栋嫣.基于图像识别技术的智能点钞机设计[D].哈尔滨理工大学硕士论文.2005.1~4
[3] 许明纪.人民币防伪点钞机市场函待加强管理[J].工作研究与交流.2000,11.32
[4] 齐成.钞票印刷防伪技术[J].包装技术.2004 年 10 月.32~33
[5] 朱杨.印钞中的纸张及其防伪技术[J].防伪技术与管理.2005,1.52
[6] 陈树根,江和平,周高杯.基于荧光光谱分析的钞票识别研究[J].2001,8.第30 第 4 期.174~177
[7] 张书彬,肖梦兰.从假钞案看防伪技术及其发展趋势[J].中国包装工业.2002,2.54~55
[8] 刘庆东.第五套人民币磁性检测技术用于辨伪点钞机[J].技术前沿
[9] 贾云得.机器视觉[M].科学出版社.2000.1~10
[10] 柳忠良.趣话人民币[M].百花文艺出版社.2004.54~78
[11] 彭明强.货币·点钞·防伪[M].立信会计出版社.2003,20~34
[12] 王宗明.实用红外光谱学[M].石油工业出版社.1990.26~32
[13] 梁治齐.红外光谱在真伪鉴别上的应用[J].北京联合大学学报.2000,6.第 14卷第 2 期.69~74
[14] 刘庆东.点钞机的辨伪原理[J].技术前沿.2002.第 1 期.56~57
[15] 刘连浩,罗安,王加阳,邓宏贵.智能型点钞机的研制.机电一体化.2003.第1 期
[16] 陈树根,江和平,周高杯.基于荧光光谱分析的钞票识别研究[J].红外与激光工程.2001,8.177~179
[17] Atmel Corporation.8Bit Microcontroller with 8K bytes In-system Programmable Flash AT89S52.2001
[18] National Semiconductor.ADC0820.1999
[19] 党国顺.人民币研究[J].西安金融.2002,10.58~63
[20] 曾宪干.如何提高计算机工业过程控制系统的可靠性[J].计算技术与自动化.1995,1.48~52
[21] 马忠梅,籍顺心,张凯,马岩.单片机的 C 语言应用程序设计(修订版)[M].北京航空航天大学出版社.2001.21~25
[22] 曹巧媛.单片机原理及应用[M].电子工业出版社.1997.87~91
[23] 刘豹.现代控制理论[M].机械工业出版社.2000,5.64~72
[24] 李俊儒.两钞口纸币清分机软件系统的设计与实现[D].哈尔滨工业大学硕士论文.2006
[25] 付小全.低分辨率下纸币的识别与污损检测[D].哈尔滨工业大学硕士论文.2006
[26] 罗浩斐.纸币清分机图像处理系统的研究[D].浙江大学硕士论文.2005
[27] 娄小冬.智能纸币清分机系统设计及其实现策略研究[D].浙江大学硕士论文.2005
[28] 卡斯尔曼 (Castleman, Kenneth R.),朱志刚,林学訚,石定机.数字图像处理[M].电子工业出版社.1998.21~42
[29] 朱秀昌,刘峰,胡栋.数字图像处理与图像通信[M].北京邮电大学出版社.2002.16~20
[30] 方子文,沈庭芝.数字图像处理及模式识别[M].北京理工大学出版社.1998
[31] Takeda F,Nishikage T,Matsumoto Y.Characteristics extraction of paper currency using symmetrical masks optimized by GA and neuro-recognition of multi-national paper currency Neural Networks Proceedings.1998.IEEE World Congress on Computational Intelligence.The1998 IEEE International Joint Conference on,Volume1,4-9 May 1998.634~639
[32] Aauro Barini,Rossana Gualtieri.A new possibalistic clustering algorithm for line detection in real world image. Pattern Recognition, Vo1.32, No.ll,Nov.1999
[33] J.Illing Worth,J.Kittler.A Survey of the Hough transform.Computer Vision and Image Process, 1988.87~116
[34] VF. Leavers.Which Hough Transform.Compute Vision and Image Process.1993
[35] 罗 军 辉 , 冯 平 . Matlab7.0 在 图 像 处 理 中 的 应 用 [M] . 机 械 工 业 出 版社.2005.169~192
[36] 诸静.图像边缘检测和图像匹配研究及应用[D].浙江大学博士论文.2003.7~8
[37] 姜长生.基于神经网络的目标图像识别方法研究[D].南京航空航天大学硕士论文.2004.3~7
[38] 张桂林.基于主成分分析的图像识别方法研究[D].华中科技大学硕士论文,2002. 5~6
[39] 高品贤.数字图像识别在测控系统中的应用[D].西南交通大学硕士论文.2002.20~21