电子束莫尔条纹的智能提取及其特征参数分析
|
摘要
电子束莫尔条纹的强度、角度、距离和线宽等特征参数是分析短磁聚焦分幅变像管成像性能,探讨像管空间分辨性能提升的重要信息.为提升莫尔条纹的提取和参数分析效率,采用巴特沃斯低通滤波器、阈值选取算法和区域匹配算法,通过Matlab的GUI界面对条纹提取和参数分析,实现了智能操作和批处理.研究结果显示,电子束莫尔条纹信息的提取时间为~12 s,莫尔条纹倾斜角度和间距的提取结果与人工操作的差异分别仅为~1.75%和~3.13%.该方法可实现条纹信息的批处理,有效提升海量信息中电子束莫尔条纹的提取及其参数分析效率,为研究短磁聚焦分幅变像管的空间分辨性能提供可靠数据.
The intensity,angle,interval,and linewidth of the electron beam moiré fringe are important characteristic parameters for analyzing the imaging performance of the short magnetic-focused framing tube and exploring the method of improving the spatial resolution of the tube. In order to improve the efficiency of the extraction and parameter analysis of the moiré fringe, Butterworth's low-pass filter, threshold selection algorithm and region matching algorithm are integrated in the Matlab GUI window for fringe extraction and parameter analysis,which enables an intelligent batch processing. The experimental results show that the extraction time of the moiré fringe information is about 12 s,and the differences between the extraction results of the angle and interval of the moiréfringes and the corresponding manual operation results are only about 1. 75% and 3. 13%,respectively. This method can realize the batch processing of the fringe information,effectively improve the extraction of the electron beam moiré fringes and the efficiency of parameter analysis in mass information,and provide reliable data for studying the spatial resolution characteristic of the short magnetic-focused framing tube.
The intensity,angle,interval,and linewidth of the electron beam moiré fringe are important characteristic parameters for analyzing the imaging performance of the short magnetic-focused framing tube and exploring the method of improving the spatial resolution of the tube. In order to improve the efficiency of the extraction and parameter analysis of the moiré fringe, Butterworth's low-pass filter, threshold selection algorithm and region matching algorithm are integrated in the Matlab GUI window for fringe extraction and parameter analysis,which enables an intelligent batch processing. The experimental results show that the extraction time of the moiré fringe information is about 12 s,and the differences between the extraction results of the angle and interval of the moiréfringes and the corresponding manual operation results are only about 1. 75% and 3. 13%,respectively. This method can realize the batch processing of the fringe information,effectively improve the extraction of the electron beam moiré fringes and the efficiency of parameter analysis in mass information,and provide reliable data for studying the spatial resolution characteristic of the short magnetic-focused framing tube.
引文
[1]HOLT D,WATSON J.A method for the positional measurement of a moiréfringe[J].Strain,1966,2(1):17-18.
[2]LI Nianhua,WU Wei,CHOU S Y.Sub-20-nm alignment in nanoimprint lithography using moiréfringe[J].Nano Letters,2006,6(11):2626-2629.
[3]WOO W H,RATNAM M M,YEN K S.Artificial neural network approach for moiréfringe center determination[J].Journal of Electronic Imaging,2015,24(6):063021.
[4]何春娟,刘绒霞,曹磊.莫尔条纹技术在微小位移测量中的应用[J].西安工业学院学报,2005,25(6):565-567.HE Chunjuan,LIU Rongxia,CAO Lei.Application of moire fringe technology in to measurement of micro replacement[J].Journal of Xi'an Institute of Technology,2005,25(6):565-567.(in Chinese)
[5]LIAO Yubo,LEI Yunfei,LIU Jinyaun,et al.Electron beam moiréfringes imaging by image converter tube with a magnetic lens[J].Journal of Applied Physics,2016,119(21):35-38.
[6]YAO S N,COLLINS T,JANCOVIC P.Hybrid method for designing digital Butterworth filters[J].Computers and Electrical Engineering,2012,38(4):811-818.
[7]ERER K S.Adaptive usage of the Butterworth digital filter[J].Journal of Biomechanics,2007,40(13):2934-2943.
[8]MELLO R G T,OLIVEIRA L F,NADAL J.Digital Butterworth filter for subtracting noise from low magnitude surface electromyogram[J].Computer Methods and Programs in Biomedicine,2007,87(1):28-35.
[9]周家玉,殷瑞祥.一种自适应去除振铃滤波新算法[J].现代电子技术,2010,33(4):58-60.ZHOU Jiayu,YIN Ruixiang.New adaptive deringing algorithm[J].Modern Electronics Technique,2010,33(4):58-60.(in Chinese)
[10]JIAO X,WU T.A visual consistent adaptive image thresholding method[J].The Imaging Science Journal,2016,64(1):34-49.
[11]MOGHADDAM R F,CHERIET M.Ad Otsu:An adaptive and parameterless generalization of Otsu's method for document image binarization[J].Pattern Recognition,2012,45(6):2419-2431.
[12]BATAINEH B,ABDULLAH S N H S,OMAR K.An adaptive local binarization method for document images based on a novel thresholding method and dynamic windows[J].Pattern Recognition Letters,2011,32(14):1805-1813.
[2]LI Nianhua,WU Wei,CHOU S Y.Sub-20-nm alignment in nanoimprint lithography using moiréfringe[J].Nano Letters,2006,6(11):2626-2629.
[3]WOO W H,RATNAM M M,YEN K S.Artificial neural network approach for moiréfringe center determination[J].Journal of Electronic Imaging,2015,24(6):063021.
[4]何春娟,刘绒霞,曹磊.莫尔条纹技术在微小位移测量中的应用[J].西安工业学院学报,2005,25(6):565-567.HE Chunjuan,LIU Rongxia,CAO Lei.Application of moire fringe technology in to measurement of micro replacement[J].Journal of Xi'an Institute of Technology,2005,25(6):565-567.(in Chinese)
[5]LIAO Yubo,LEI Yunfei,LIU Jinyaun,et al.Electron beam moiréfringes imaging by image converter tube with a magnetic lens[J].Journal of Applied Physics,2016,119(21):35-38.
[6]YAO S N,COLLINS T,JANCOVIC P.Hybrid method for designing digital Butterworth filters[J].Computers and Electrical Engineering,2012,38(4):811-818.
[7]ERER K S.Adaptive usage of the Butterworth digital filter[J].Journal of Biomechanics,2007,40(13):2934-2943.
[8]MELLO R G T,OLIVEIRA L F,NADAL J.Digital Butterworth filter for subtracting noise from low magnitude surface electromyogram[J].Computer Methods and Programs in Biomedicine,2007,87(1):28-35.
[9]周家玉,殷瑞祥.一种自适应去除振铃滤波新算法[J].现代电子技术,2010,33(4):58-60.ZHOU Jiayu,YIN Ruixiang.New adaptive deringing algorithm[J].Modern Electronics Technique,2010,33(4):58-60.(in Chinese)
[10]JIAO X,WU T.A visual consistent adaptive image thresholding method[J].The Imaging Science Journal,2016,64(1):34-49.
[11]MOGHADDAM R F,CHERIET M.Ad Otsu:An adaptive and parameterless generalization of Otsu's method for document image binarization[J].Pattern Recognition,2012,45(6):2419-2431.
[12]BATAINEH B,ABDULLAH S N H S,OMAR K.An adaptive local binarization method for document images based on a novel thresholding method and dynamic windows[J].Pattern Recognition Letters,2011,32(14):1805-1813.