期刊文献+

光纤传感器在纸币凹版印刷特征识别中的应用 被引量:2

Application of optical-fiber-sensor to recognizing the characters of intaglio printings on banknotes
下载PDF
导出
摘要 提出了两种用光纤传感器测试纸币凹版印刷的方案。其中动态检测方案利用了光纤位移传感器进行微位移测量的原理,静态检测方案利用了电磁波的散射原理,通过光纤表面粗糙度传感器来实现。按照实际要求,对两种方案的探测装置进行了设计,使其能更好地突出被测表面的特征。理论和实验结果都表明本文提出的两种方案是可行的,其中动态检测方案在一种新的专业级金融防伪设备中得到了应用,弥补了金融安全行业中机器识别凹版印刷特征的空白。 Two methods have been proposed to test the intaglio printings on banknotes by optical fiber sensors.The dynamic test is based on the theory of measurement of tiny displacernent by optical fiber sensors, while the electromagnetic scattering theory is used in static test using fiber surface roughness sensor. According to the actual requirements, we designed a detector of each method respectively to make the characters of tested surface clearer. Both theoretical and experimental result show that the two methods proposed in this paper are feasible, and the dynamic method has been used on a new professional financial anti-forgery workstation. This project will certainly make up the vacancy of machine identification of the characters of intaglio printing system in the financial security field.
出处 《中国测试技术》 2006年第2期82-85,共4页 CHINA MEASUREMENT & TESTING TECHNOLOGY
关键词 凹版印刷 光纤传感器 微位移 表面粗糙度 防伪 Intaglio printing Optical fiber sensor Tiny displacement Surface roughness Anti-forgery
  • 相关文献

参考文献6

二级参考文献5

  • 1苑立波.光源与纤端光场[J].光通信技术,1994,18(1):54-56. 被引量:40
  • 2Ding Z H, Wang G Y, Wang Z J. Microscopic interferometer for surface roughness measurement. Optical Engineering, 1996, 35(10): 2 956~2 961
  • 3Daniel M. Optical shop testing(2e). New York: John Wiley & Sons Inc., 1992.
  • 4Elster C, Weingartner I. Solution to the shearing problem. Applied Optics, 1999, 38(23): 5 024-5 031
  • 5程路.激光束在漫射表面上的散射——一种简化统计模型[J]物理学报,1978(06).

共引文献23

同被引文献17

  • 1张涛,王成儒.窗口纹理分析方法[J].仪器仪表学报,2006,27(z3):2289-2290. 被引量:4
  • 2尤佳,徐炜.流通人民币纸币的面值识别[J].仪器仪表学报,2003,24(z2):94-95. 被引量:15
  • 3唐春晖.人民币伪钞鉴别仪的鉴伪技术[J].仪表技术,2005(4):80-81. 被引量:12
  • 4中华人民共和国国家标准.产品几何技术规范、表面结构轮廓法、表面结构的术语、定义及参数(GB/T 3505-2009)[S].2009.
  • 5AKBARI A A,FARD A M,CHEGINI A G.An effective image based surface roughness estimation approach using neural network[J].World Automation Congress (WAC),Budapest,Hungary,2006(7):24-26.
  • 6FROSINI M,GORI P,PRIAMI P.A neural network-based model for paper currency recognition and verification[C].IEEE Transactions on Neural Network,1996(7):1482-1490.
  • 7ROSENFELD,TROY E B.Visual texture analysis[R].Technical Report of University of Maryland,College Park,1970:70-116.
  • 8JAIN A K,KARU K.Learning texture discrimination masks[C].IEEE Transactions on Pattern Analysis and Machine Intelligence,1996,18(2):195-205.
  • 9赵前程,罗晓莉,邓善熙.基于特征模型的形状误差估计新方法[J].仪器仪表学报,2007,28(9):1629-1634. 被引量:7
  • 10索双富,孙晋厚,肖丽英.点钞机鉴伪技术发展趋势[J].机械设计与制造,2007(12):199-201. 被引量:10

引证文献2

二级引证文献9

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部