微型零件高精度影像测量系统中关键技术研究
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摘要
随着计算机技术的飞速发展,影像测量技术凭借其非接触、高精度等优势已获得了广泛的应用。近年来由于工业工艺水平的不断进步,高精度微型零件的数量呈指数增长。然而,现有的影像测量仪受精度与视场矛盾的制约,测量效率低下,难以满足高精度、高效率的测量需求。本文对高精度影像测量系统中的关键技术进行了研究,包括硬件系统的搭建与调整、高精度的边缘定位技术、系统标定以及图像超分辨率重建技术等。以手表中精度最高的零件之一——擒纵轮为测量对象,完成了“擒纵轮视觉检测仪”,实现了不同规格擒纵轮高精度、高效率的测量,相对测量精度优于1/2000,并完成了工业现场的调试和验收。具体的工作和创新点主要包括:
1.以擒纵轮为测量对象,完成了高精度影像测量系统。主要包括:确定基于完整成像的测量模式;采用自行设计的物方远心光路,并在设计中将擒纵轮关键尺寸所处的环带区域(靠近视场边缘的部分)畸变矫正至最小;完成了照明设计。
2.对系统光轴与物面的垂直度和物面的对焦精度的高精度调节进行了研究。分别提出了基于图像区域清晰度的系统光轴垂直度评价方法和基于图像插值的清晰度评价方法,通过实验验证了方法的有效性,并实现了“擒纵轮视觉检测仪”中系统光轴与物面的垂直度和物面对焦精度的高精度调节。
3.研究了图像边缘的高精度定位技术。包括像素级的边缘提取,轮廓跟踪技术和亚像素级的边缘定位技术。提出了基于模板相关的亚像素定位算法,对不同类型的边缘建立不同的边缘模板,利用该模板和实际边缘进行相关运算,找出最佳的相关位置,从而实现边缘点亚像素级精度的定位。
4.完成了高精度的系统标定以及擒纵轮特征参数的计算和软件设计。实现了多种规格擒纵轮的11类参数的高精度、高效率测量,并完成了“擒纵轮视觉检测仪”的现场调试,通过测试验收,可靠、稳定的运行在工业现场。
5.研究了基于序列图像的超分辨率重建技术以提升原始图像的分辨率,从而提升测量精度。针对当前基于精确微位移的序列图像超分辨率重建技术中,精确微位移难以获取的难题,提出了基于随机微位移的超分辨率重建技术,并用于影像测量,提升了测量精度,设计实验证明了该方法的有效性。
With the development of computer techniques, image measuring techniques are widely used in the industry, by right of the advantages such as non-contact, high accuracy and so on. The number of high-precision subminiature accessory applied in the industry is exponential increasing year by year, due to the constant progress of industrial level. However, the existing image measuring instrument is difficult to meet the measurement demand of high accuracy and efficiency, for the measurement efficiency is low which is restricted by the contradiction between precision and field range. This thesis is studied on the key technology of high accuracy image measurement system, including the building and accurate adjustment of the hardware system, edge location technology of high accurate, system calibration, image super-resolution reconstruction and so on. The Vision Inspection Instrument for Escape Wheel(VIIEW) was built for the measurement of escape wheel which was one of the highest precision parts in the horological industry, and has realized the measurement of different specifications of escape wheel with more precise and efficient. Besides,The VIIEW, of wich the relative accuracy is better than 1/2000, also finished the debugging and acceptance in the industrial field. The main contributions and innovative points of the thesis include:
1. A high accuracy image measurement system for the precise measurement of the escape wheel is designed and built. It mainly includes: determined the measurement mode based on entire imaging; adopted the self-designed object telecentric lens, which make the distortion of annular area containing the key parameters of the escape wheel(area close to the field margin) minimum; finished the designing of lighting system.
2. The highly accurate adjustment of the verticality between optical axis and object plane and the focusing of object plane are studied. One kind of image definition criterion algorithm which is based on the image interpolation and the algorithm of detecting verticality based on regional image definition are proposed respectively. According to experiments, both of the methods are effective, and realized the highly accurate adjustment in the VIIEW.
3. The highly accurate location technology of image edge is studied, including edge detection of pixel level, contour tracking technique and edge location of sub-pixel level. A sub-pixel location algorithm based on matching template is proposed. By building relevant matching template considering the edge of different type, carrying correlation operation between matching template and the image edge, and finding the position of most correlation, high accurate edge location of sub-pixel is achieved.
4. System calibration with high precision, calculation of escape wheel's parameters and software designing are completed. Realizing the high precision and greater efficiency measurement of escape wheel's 11 parameters of many types, the VIIEW can work in the industrial field reliably and stablely after finishing field debugging and obtaining acceptance test.
5. The reconstruction technique of super-resolution based on image sequence is studied to improve the resolution of the original image, which helps to improve the measuring precision. In order to solve the problem that the micro-displacement of high accuracy is difficult to realize in the reconstruction of super-resolution based on precise micro-displacement, the reconstruction technique of super-resolution based on random micro-displacement is proposed. This method can promote the measuring precision when using in the image measurement which proves to be effective by designed experiment.
1.以擒纵轮为测量对象,完成了高精度影像测量系统。主要包括:确定基于完整成像的测量模式;采用自行设计的物方远心光路,并在设计中将擒纵轮关键尺寸所处的环带区域(靠近视场边缘的部分)畸变矫正至最小;完成了照明设计。
2.对系统光轴与物面的垂直度和物面的对焦精度的高精度调节进行了研究。分别提出了基于图像区域清晰度的系统光轴垂直度评价方法和基于图像插值的清晰度评价方法,通过实验验证了方法的有效性,并实现了“擒纵轮视觉检测仪”中系统光轴与物面的垂直度和物面对焦精度的高精度调节。
3.研究了图像边缘的高精度定位技术。包括像素级的边缘提取,轮廓跟踪技术和亚像素级的边缘定位技术。提出了基于模板相关的亚像素定位算法,对不同类型的边缘建立不同的边缘模板,利用该模板和实际边缘进行相关运算,找出最佳的相关位置,从而实现边缘点亚像素级精度的定位。
4.完成了高精度的系统标定以及擒纵轮特征参数的计算和软件设计。实现了多种规格擒纵轮的11类参数的高精度、高效率测量,并完成了“擒纵轮视觉检测仪”的现场调试,通过测试验收,可靠、稳定的运行在工业现场。
5.研究了基于序列图像的超分辨率重建技术以提升原始图像的分辨率,从而提升测量精度。针对当前基于精确微位移的序列图像超分辨率重建技术中,精确微位移难以获取的难题,提出了基于随机微位移的超分辨率重建技术,并用于影像测量,提升了测量精度,设计实验证明了该方法的有效性。
With the development of computer techniques, image measuring techniques are widely used in the industry, by right of the advantages such as non-contact, high accuracy and so on. The number of high-precision subminiature accessory applied in the industry is exponential increasing year by year, due to the constant progress of industrial level. However, the existing image measuring instrument is difficult to meet the measurement demand of high accuracy and efficiency, for the measurement efficiency is low which is restricted by the contradiction between precision and field range. This thesis is studied on the key technology of high accuracy image measurement system, including the building and accurate adjustment of the hardware system, edge location technology of high accurate, system calibration, image super-resolution reconstruction and so on. The Vision Inspection Instrument for Escape Wheel(VIIEW) was built for the measurement of escape wheel which was one of the highest precision parts in the horological industry, and has realized the measurement of different specifications of escape wheel with more precise and efficient. Besides,The VIIEW, of wich the relative accuracy is better than 1/2000, also finished the debugging and acceptance in the industrial field. The main contributions and innovative points of the thesis include:
1. A high accuracy image measurement system for the precise measurement of the escape wheel is designed and built. It mainly includes: determined the measurement mode based on entire imaging; adopted the self-designed object telecentric lens, which make the distortion of annular area containing the key parameters of the escape wheel(area close to the field margin) minimum; finished the designing of lighting system.
2. The highly accurate adjustment of the verticality between optical axis and object plane and the focusing of object plane are studied. One kind of image definition criterion algorithm which is based on the image interpolation and the algorithm of detecting verticality based on regional image definition are proposed respectively. According to experiments, both of the methods are effective, and realized the highly accurate adjustment in the VIIEW.
3. The highly accurate location technology of image edge is studied, including edge detection of pixel level, contour tracking technique and edge location of sub-pixel level. A sub-pixel location algorithm based on matching template is proposed. By building relevant matching template considering the edge of different type, carrying correlation operation between matching template and the image edge, and finding the position of most correlation, high accurate edge location of sub-pixel is achieved.
4. System calibration with high precision, calculation of escape wheel's parameters and software designing are completed. Realizing the high precision and greater efficiency measurement of escape wheel's 11 parameters of many types, the VIIEW can work in the industrial field reliably and stablely after finishing field debugging and obtaining acceptance test.
5. The reconstruction technique of super-resolution based on image sequence is studied to improve the resolution of the original image, which helps to improve the measuring precision. In order to solve the problem that the micro-displacement of high accuracy is difficult to realize in the reconstruction of super-resolution based on precise micro-displacement, the reconstruction technique of super-resolution based on random micro-displacement is proposed. This method can promote the measuring precision when using in the image measurement which proves to be effective by designed experiment.
引文
[1]朱铮涛,基于计算机视觉图像精密测量的关键技术研究,博士学位论文,华南理工大学,2004
[2]孙双花,视觉测量关键技术及在自动检测中的应用,博士学位论文,天津大学,2007
[3]Franci Lahajnar, et al,Machine vision system for inspecting electric plates, Computer in Industry,2002,47:113~122
[4]L Angrisani,P Daponte,A Pietrosanto,et al,An image-based measurement system for the characterisation of automotive gaskets, Measurement,1999, 25:169~181
[5]Kang T J,Choi S H,Kim S M.Automatic structure analysis and objective evaluation of woven fabric using image analysis,Textile Res,2001, 71(3):261~270
[6] W.A.Perkins, A Computer vision system which learn to inspect parts,IEEE Trans,PAMI-5:584~592
[7]刘君,郭晓然,晏克俊,基于IMAQ Vision的小模数直齿圆柱齿轮测量方法研究,仪器仪表学报,2008,29(5):1044~1048
[8]张进,完整成像测量方法中轮廓测量技术的研究,硕士学位论文,天津大学,2007
[9]张变莲,车辆牌照识别系统关键技术研,硕士学位论文,中国科学院西安光学精密机械研究所,2006
[10]高一凡,王选仓,条形码在交通管理中的应用,交通与计算机,1996,14(2):53~58
[11]顾妍午,李平,陶文华等,基于改进BP神经网络的手写邮政编码识别,辽宁石油化工大学学报,2008,28(1):52~54
[12]李超,基于视觉的合金圆锯片锯齿角度测量方法研究,硕士学位论文,天津大学,2009
[13]Franci Lahajnar,et al,Machine vision system for inspecting electric plates,Computer in Industry,2002,47:113~122
[14]张洪涛,钢板表面缺陷在线视觉检测系统关键技术研究,博士学位论文,天津大学,2008
[15]N Aleixos,J Blasco,F Navarron,et al,Multispectral inspection of citrus in real-time using machine vision and digital signal processors,Computers and Electronics in Agriculture,2002,33:121~137
[16]J J Eillis,W J Hill,Automatic inspection of cold rolled 5tee1 strip,Proc.IEEE Int.Conf.on Image Processing,1982:134~138
[17]W.S.Wilson,The role of vision in a dimensional control strategy,Proc.of the Society of Manufacturing Engineers Conf.on Vision Section 7,1985:43~55
[18]Bremner J F,Automatic vision inspection system for the inspection of shapes cut in sheet material,Pro.On Image Processing,1986:40~43
[19]M M Landman,S J Roberton,A flexible industrial system for automated three-dimensional inspection,SPIE,1986:203~209
[20]Q Dajle,On-line inspection of extruded profile geometry, Vision'90,1990:1~17
[21]Lu R S,On-line measurement of the straightness of seamless steel pipes using machine vision technique,Sensors and Actuators,2001,94:417~427
[22]Newman T S,Jain A K,A system for 3D cad-based inspection using range images,Pattern Recognition,1995,28(10):1555~1574
[23]Dimitrios,Kosmopoulos,et al,Automated inspection of gaps on the automobile production line through stereo vision and specular reflection,Computer in Industry,2001,46:49~63
[24]Mu-Chen Chen,Roundness measurement for discontinuous perimeters via machine vision,Computer in Industry,2002,4:185~197
[25]刘常杰,邾继贵,杨学友等,汽车白车身在线激光视觉检测站,仪器仪表学报,2004,25(4):671~672
[26]叶声华,王仲,精密测试技术展望,中国机械工程,2000,11(3):262~263
[27]单越康,卫力,毛谦敏,复杂几何形状零件自动检测,中国计量学院学报,1997,2:38~46
[28]段发阶,叶声华,王春和等,拔丝模孔形计算机视觉检测技术,光电工程,1996,23(3):72~76
[29]梁学军,洪迈生,贾文焕,螺纹紧固件的自动检测技术,计量技术,2002,(2):14~17
[30]王剑平,奚立峰,潘尔顺,基于机器视觉的齿轮缺陷快速检测,起重运输机械,2004,(5):41~43
[31]黄劼，周肇飞，机器视觉精密测量系统研究，光学技术，2004,30(4):491~494
[32]岳卫宏,计算机视觉在齿轮测量中的应用研究,硕士学位论文,武汉理工大学,2005
[33]贺秋伟,基于计算机视觉的微小尺寸精密检测理论与技术研究,博士学位论文,吉林大学,2007
[34]贾云得,机器视觉,北京:科学出版社,2000
[35]王政良,完整成像测量方法中拼接技术的研究,硕士学位论文,天津大学,2006
[36]陈向伟,机械零件计算机视觉检测关键技术的研究,博士学位论文,吉林大学,2005
[37]Liangyu Lei,Xiaojun Zhou,Mingqing Pan,Automated vision inspection system for the size measurement of workpieces,Instrumentation and measurement technology conference,2005,872~877
[38]Jurgen Acker , Dominik Henrich , Manipulating deformable linear objects:Characteristic features for Vision-based detection of contact state transitions,In Proceedings of the IEEE International Symposium on Assembly and Task Planning,2003,204~209
[39]Fernandez-Canque Hernando,Hintea Sorin,Csipkes Gabor,et al,Machine vision application to the detection of micro-organism in drinking water,Knowledge-Based Intelligent Information and Engineering Systems-12th International Conference,KES 2008,5179LNAI(PART 3):302~309
[40]贺秋伟,王龙山,刘庆民等,基于支持向量回归的小尺寸零件精密测量,光学精密工程,2007,15(04):557~563
[41]余厚云,微型零件在线检测系统的研究,硕士学位论文,合肥工业大学,2003
[42]李乔天,数字图像处理技术在光电影像测量仪中的应用,硕士学位论文,长春理工大学,2009
[43]尼康光学计量仪器,http://www.cnnikon.com/PRODUCT/18.htm
[44]意大利LTF S.p.A.公司,http://www.ltf.it/scheda.php?id=1885
[45]张俊杰,完整成像测量仪技术研究,硕士学位论文,天津大学,2007
[46]株式会社ミツトヨ,http://www.mitutoyo.co.jp
[47]操晶晶,完整成像法微型零件轮廓自动测量与评定技术研究,硕士学位论文,天津大学,2008
[48]W.A.Perkins,A Computer vision system which learn to inspect parts,IEEE Trans,PAMI-5:584~592
[49]杨丽凤,韩冀皖,李元宗,面阵CCD高精度测量技术的应用,太原理工大学学报,2001,32(5):455~458
[50]相机之家,http://www.xiangji.cn/school/20073221334497341.html
[51]T.T.E.Yeo,S.H.Ong,Jayasooriah,et al,Autofocusing for Tissue Microscopy,Image and Vision Computing,1993,11(10):629~630
[52]欧迪光学,http://hi.baidu.com/odie365/blog/item
[53]章毓晋,图像分析,北京:清华大学出版社,2005
[54]Jing Xiaojun , Fu Yali , Huo Xiuli , Image filtering based on multi-criterion of boundary point judgment , Chinese Journal of Electronics,2005,14(3):498~502
[55]HIDENORI T,TOSHIMITSU K,Image registration using subpixel-shifted images for super-resolution,IEEE International Conference on Image Processing,ICIP 2008:2404~2407
[56]G.S.Robinson,Edge Detection by Compass Gradient Masks,1977,CGIP6(5): 492~501
[57]D.Marr,E.Hildreth,Theory of edge detection,Proceeding of Royal Soc. London,1980,B207:187~217
[58]L.G.Roberts,Machine perception of Three-Dimension Solids,Ph.D Thesis, MIT, 1963
[59]L.Sobel, Camera models and machine perception, Ph. D thesis, Stanford University, 1970
[60]J.Canny,A Computational Approach to Edge Detection,IEEE Trans, Pattern Analysis and Machine Intelligence,1986:679~698
[61]梁友,图像处理及特征识别方法研究,华北电力大学,硕士学位论文,2008
[62]袁野,摄像机标定方法及边缘检测和轮廓跟踪算法研究,博士学位论文,大连理工大学,2002
[63]Wong K K,Mendonca P R S,Cipolla R,Camera calibration from surfaces of revolution,IEEE Transactions on PAMI,2003,25(2):147~161
[64]王建民,浦昭邦,鲁振智等,一种新的二维图像测量系统标定方法,计量学报,2000,21(4):241~247
[65]方亦元等,机械零部件测绘,东北大学出版社,2000
[66]天津大学精仪系“机械计时仪器”编写组,机械计时仪器,天津人民出版社,1974
[67]图像和机器视觉产品手册,北京凌云光视数字图像技术有限公司
[68]王庆友,图像传感器应用技术,北京:电子工业出版社,2003,78~99
[69]152801Manual Adimec-4000m-4020m,36~37
[70]郁道银,谈恒英,工程光学,北京:机械工业出版社,2002
[71]张以谟,应用光学,北京:机械工业出版社,1982
[72]张立昆,擒纵轮半自动视觉检测系统的设备构建与调整,硕士学位论文,天津大学,2009
[73]2009版微视凌志|代理机器视觉|产品大全,北京微视凌志图像技术有限公司
[74]龚昊,吕乃光,娄小平等,二维视觉测量中光轴与载物台垂直度调节方法,北京机械工业学院学报,2006,21(3):35~38
[75]牟丽,杨敏,垂直度的计算机视觉检测算法研究,现代制造工程,2007,3:101~103
[76]杨再华,李玉和,李庆祥等,基于边缘特征提取的图像清晰度评价函数,计算机工程与应用,2005,10:35~37
[77]朱孔凤,姜威,王端芳等,一种新的图像清晰度评价函数,红外与激光工程,2005,34(4):464~468
[78]倪军,袁家虎,吴钦章,基于边缘特征的光学图像清晰度判定,中国激光,2009,36(1):172~176
[79]Jian Li,Renbiao Wu,Victor C.Chen,Robust autofocus algorithm for ISAR imaging of moving targets,IEEE Transactions on Aerospace and Electronic Systems,2001,37(3):1056~1069
[80]S.Jutamulia , T.Asakura , R.D.Bahuguna , Autofocusing based on power-spectra analysis,Appl.Optics,1994,33(26):6210~6212
[81]包学诚,摄影镜头的光学原理及应用技巧,上海:上海交通大学出版社,1999
[82]张进,王仲,李霞,微型零件中圆孔的高精度定位方法,电子测量与仪器学报,2008,22(3):47~50
[83]周贤,姜威,基于图像边缘能量的自动聚焦算法,光学技术,2006,32(2):213~216
[84]李霞,基于模板的微型零件完整成像测量方法的研究,硕士学位论文,天津大学,2007
[85]贡力,基于完整图像的微型零件精密测试技术研究,硕士学位论文,天津大学,2009
[86]Kozo Ohtani,Mitsuru Baba,A Fast edge location measurement with subpixel accuracy using a CCD image,IEEE Instrumentation and Measurement Technology Conference,2001:2087~2092
[87]Venkatachalam.V , Wasserman R.M , Comprehensive investigation of subpixel edge detection schemes in metrology,Proceedings of the SPIE - The International Society for Optical Engineering,2003:200~211
[88]乔辉,亚像素边缘检测算法及集成块管脚外观检测系统的研究,硕士学位论文],南开大学,2003
[89]Tabatabai A J,Mitchell O R,Edge location to subpixel values in digital imagery,IEEE Trans on Pattem Analysis and Machine Intelligence,1984, 6(2):188~201
[90]Lyvers E P,Mitchell O R,et al,Subpixel measurements using a moment-based edge operator,IEEE Trans. on PAMI,1989,11(12): 1293~1309
[91]刘亚威,杨丹,张小洪,基于空间矩的亚像素边缘定位技术的研究,计算机应用,2003,23(2):47~49
[92]张永宏,胡德金,徐俊杰,基于视觉图像的机加工零部件亚像素边缘定位,机械工程学报,2004,40(6):179~182
[93]Ghosal S,Mehrotra R,Edge detection using orthogonal moment-based operators,IEEE Trans. on PAMI,1992,7(12):413~417
[94]曾绍标,熊洪允,毛云英,应用数学基础(下册),天津:天津大学出版社,1994,22~24
[95]苏步青,刘鼎元,计算几何,上海:上海科学技术出版社,1981,149~156
[96]Zhang.J,Wang.Z,Yang C,et al,Sub-pixel Edge Estimation Based on Matching Template,International Conference on Optical Instruments and Technology, 2008, 71602A-1~71602A-9
[97]周智浩,基于序列图像的二维超分辨率重构技术研究,硕士学位论文,浙江大学,2006
[98]LEUNG K.T,TONG C.S,Effective use of low resolution images for super-resolution reconstruction,1st International Congress on Image and Signal Processing,2008: 320~325
[99]XIAO Q,DING X H,QIAN K,et al,A new method for multi-frame super-resolution reconstruction,Proceedings of the 2009 International Joint Conference on Computational Sciences and Optimization,2009:892~895
[100]覃凤清,何小海,陈为龙等,一种图像配准的超分辨率重建,光学精密工程,2009,17(2):409~416
[101]徐正平,翟林培,葛文奇等,亚像元的CCD几何超分辨方法,光学精密工程,2008,16(12):2447~2452
[102]黄战华,蔡怀宇,张以谟等,基于半像素错位的多幅图像重建高分辨率图像技术研究,光学技术,2002,28(5):389~394
[103]王凌,张平,冯华君等,用多次移位成像提高CCD成像分辨力的反演解析法,光电工程,2003,30(3):62~65
[104]杜娟,余英林,谢胜利,基于半像素运动信息的快速超分辨率图像重构算法,华南理工大学学报(自然科学版),2005,33(5):53~58
[105]曹聚亮,图像超分辨率处理、成像及其相关技术研究,博士学位论文,国防科学技术大学,2004
[106]费业泰,误差理论与数据处理,北京:机械工业出版社,2000
[107]袁野,摄像机标定方法及边缘检测和轮廓跟踪算法研究,博士学位论文,大连理工大学,2002
[108]屈玉福,视觉坐标测量机三维动态测量技术的研究,博士学位论文,哈尔滨工业大学,2004
[109]朱铮涛,黎绍发,镜头畸变及其校正技术,光学技术,2005,1(31):136~138
[110]R.K.Lenz,R.Y.Tsai,Techniques for calibration of the scale factor and image center for high accuracy 3D machine vision metrology,IEEE Trans. on PAMI,1998,10(5):713~720
[111]高满屯,曲仕如,李西琴,计算机视觉研究中的投影理论和方法,西安:西北工业大学出版社,1998
[112]Rafael Kelly,Fernando Reyes,On vision systems identification with application to Fixed-Camera robotic systems , IEEE Trans Robotics Automation,2000,11:170~180
[113]I.Sobel,On calibrating computer controlled cameras for perceiving 3-D scenes,Artificial Intelligence,1974,5(2):185~188
[114]Tsai R.Y,An efficient and accurate camera calibration technique for 3D machine vision,Proc.CVPR’86,New York: IEEE,1986:363~374
[115]杨纯,擒纵轮视觉检测仪测量系统研究,硕士学位论文,天津大学,2010
[116]朱诗生,张惠珍,人机交互软件界面设计,信息技术,2009,(5):36~39
[117]杨宝华,袁志树,文昌辞,应用软件人际界面优化的研究,电脑知识与技术,2009,(5):4817~4818
[118]VC知识库文章:http://www.vckbase.com/document/viewdoc/?id=518
[119]VC知识库文章:http://www.vckbase.com/document/viewdoc/?id=519
[2]孙双花,视觉测量关键技术及在自动检测中的应用,博士学位论文,天津大学,2007
[3]Franci Lahajnar, et al,Machine vision system for inspecting electric plates, Computer in Industry,2002,47:113~122
[4]L Angrisani,P Daponte,A Pietrosanto,et al,An image-based measurement system for the characterisation of automotive gaskets, Measurement,1999, 25:169~181
[5]Kang T J,Choi S H,Kim S M.Automatic structure analysis and objective evaluation of woven fabric using image analysis,Textile Res,2001, 71(3):261~270
[6] W.A.Perkins, A Computer vision system which learn to inspect parts,IEEE Trans,PAMI-5:584~592
[7]刘君,郭晓然,晏克俊,基于IMAQ Vision的小模数直齿圆柱齿轮测量方法研究,仪器仪表学报,2008,29(5):1044~1048
[8]张进,完整成像测量方法中轮廓测量技术的研究,硕士学位论文,天津大学,2007
[9]张变莲,车辆牌照识别系统关键技术研,硕士学位论文,中国科学院西安光学精密机械研究所,2006
[10]高一凡,王选仓,条形码在交通管理中的应用,交通与计算机,1996,14(2):53~58
[11]顾妍午,李平,陶文华等,基于改进BP神经网络的手写邮政编码识别,辽宁石油化工大学学报,2008,28(1):52~54
[12]李超,基于视觉的合金圆锯片锯齿角度测量方法研究,硕士学位论文,天津大学,2009
[13]Franci Lahajnar,et al,Machine vision system for inspecting electric plates,Computer in Industry,2002,47:113~122
[14]张洪涛,钢板表面缺陷在线视觉检测系统关键技术研究,博士学位论文,天津大学,2008
[15]N Aleixos,J Blasco,F Navarron,et al,Multispectral inspection of citrus in real-time using machine vision and digital signal processors,Computers and Electronics in Agriculture,2002,33:121~137
[16]J J Eillis,W J Hill,Automatic inspection of cold rolled 5tee1 strip,Proc.IEEE Int.Conf.on Image Processing,1982:134~138
[17]W.S.Wilson,The role of vision in a dimensional control strategy,Proc.of the Society of Manufacturing Engineers Conf.on Vision Section 7,1985:43~55
[18]Bremner J F,Automatic vision inspection system for the inspection of shapes cut in sheet material,Pro.On Image Processing,1986:40~43
[19]M M Landman,S J Roberton,A flexible industrial system for automated three-dimensional inspection,SPIE,1986:203~209
[20]Q Dajle,On-line inspection of extruded profile geometry, Vision'90,1990:1~17
[21]Lu R S,On-line measurement of the straightness of seamless steel pipes using machine vision technique,Sensors and Actuators,2001,94:417~427
[22]Newman T S,Jain A K,A system for 3D cad-based inspection using range images,Pattern Recognition,1995,28(10):1555~1574
[23]Dimitrios,Kosmopoulos,et al,Automated inspection of gaps on the automobile production line through stereo vision and specular reflection,Computer in Industry,2001,46:49~63
[24]Mu-Chen Chen,Roundness measurement for discontinuous perimeters via machine vision,Computer in Industry,2002,4:185~197
[25]刘常杰,邾继贵,杨学友等,汽车白车身在线激光视觉检测站,仪器仪表学报,2004,25(4):671~672
[26]叶声华,王仲,精密测试技术展望,中国机械工程,2000,11(3):262~263
[27]单越康,卫力,毛谦敏,复杂几何形状零件自动检测,中国计量学院学报,1997,2:38~46
[28]段发阶,叶声华,王春和等,拔丝模孔形计算机视觉检测技术,光电工程,1996,23(3):72~76
[29]梁学军,洪迈生,贾文焕,螺纹紧固件的自动检测技术,计量技术,2002,(2):14~17
[30]王剑平,奚立峰,潘尔顺,基于机器视觉的齿轮缺陷快速检测,起重运输机械,2004,(5):41~43
[31]黄劼，周肇飞，机器视觉精密测量系统研究，光学技术，2004,30(4):491~494
[32]岳卫宏,计算机视觉在齿轮测量中的应用研究,硕士学位论文,武汉理工大学,2005
[33]贺秋伟,基于计算机视觉的微小尺寸精密检测理论与技术研究,博士学位论文,吉林大学,2007
[34]贾云得,机器视觉,北京:科学出版社,2000
[35]王政良,完整成像测量方法中拼接技术的研究,硕士学位论文,天津大学,2006
[36]陈向伟,机械零件计算机视觉检测关键技术的研究,博士学位论文,吉林大学,2005
[37]Liangyu Lei,Xiaojun Zhou,Mingqing Pan,Automated vision inspection system for the size measurement of workpieces,Instrumentation and measurement technology conference,2005,872~877
[38]Jurgen Acker , Dominik Henrich , Manipulating deformable linear objects:Characteristic features for Vision-based detection of contact state transitions,In Proceedings of the IEEE International Symposium on Assembly and Task Planning,2003,204~209
[39]Fernandez-Canque Hernando,Hintea Sorin,Csipkes Gabor,et al,Machine vision application to the detection of micro-organism in drinking water,Knowledge-Based Intelligent Information and Engineering Systems-12th International Conference,KES 2008,5179LNAI(PART 3):302~309
[40]贺秋伟,王龙山,刘庆民等,基于支持向量回归的小尺寸零件精密测量,光学精密工程,2007,15(04):557~563
[41]余厚云,微型零件在线检测系统的研究,硕士学位论文,合肥工业大学,2003
[42]李乔天,数字图像处理技术在光电影像测量仪中的应用,硕士学位论文,长春理工大学,2009
[43]尼康光学计量仪器,http://www.cnnikon.com/PRODUCT/18.htm
[44]意大利LTF S.p.A.公司,http://www.ltf.it/scheda.php?id=1885
[45]张俊杰,完整成像测量仪技术研究,硕士学位论文,天津大学,2007
[46]株式会社ミツトヨ,http://www.mitutoyo.co.jp
[47]操晶晶,完整成像法微型零件轮廓自动测量与评定技术研究,硕士学位论文,天津大学,2008
[48]W.A.Perkins,A Computer vision system which learn to inspect parts,IEEE Trans,PAMI-5:584~592
[49]杨丽凤,韩冀皖,李元宗,面阵CCD高精度测量技术的应用,太原理工大学学报,2001,32(5):455~458
[50]相机之家,http://www.xiangji.cn/school/20073221334497341.html
[51]T.T.E.Yeo,S.H.Ong,Jayasooriah,et al,Autofocusing for Tissue Microscopy,Image and Vision Computing,1993,11(10):629~630
[52]欧迪光学,http://hi.baidu.com/odie365/blog/item
[53]章毓晋,图像分析,北京:清华大学出版社,2005
[54]Jing Xiaojun , Fu Yali , Huo Xiuli , Image filtering based on multi-criterion of boundary point judgment , Chinese Journal of Electronics,2005,14(3):498~502
[55]HIDENORI T,TOSHIMITSU K,Image registration using subpixel-shifted images for super-resolution,IEEE International Conference on Image Processing,ICIP 2008:2404~2407
[56]G.S.Robinson,Edge Detection by Compass Gradient Masks,1977,CGIP6(5): 492~501
[57]D.Marr,E.Hildreth,Theory of edge detection,Proceeding of Royal Soc. London,1980,B207:187~217
[58]L.G.Roberts,Machine perception of Three-Dimension Solids,Ph.D Thesis, MIT, 1963
[59]L.Sobel, Camera models and machine perception, Ph. D thesis, Stanford University, 1970
[60]J.Canny,A Computational Approach to Edge Detection,IEEE Trans, Pattern Analysis and Machine Intelligence,1986:679~698
[61]梁友,图像处理及特征识别方法研究,华北电力大学,硕士学位论文,2008
[62]袁野,摄像机标定方法及边缘检测和轮廓跟踪算法研究,博士学位论文,大连理工大学,2002
[63]Wong K K,Mendonca P R S,Cipolla R,Camera calibration from surfaces of revolution,IEEE Transactions on PAMI,2003,25(2):147~161
[64]王建民,浦昭邦,鲁振智等,一种新的二维图像测量系统标定方法,计量学报,2000,21(4):241~247
[65]方亦元等,机械零部件测绘,东北大学出版社,2000
[66]天津大学精仪系“机械计时仪器”编写组,机械计时仪器,天津人民出版社,1974
[67]图像和机器视觉产品手册,北京凌云光视数字图像技术有限公司
[68]王庆友,图像传感器应用技术,北京:电子工业出版社,2003,78~99
[69]152801Manual Adimec-4000m-4020m,36~37
[70]郁道银,谈恒英,工程光学,北京:机械工业出版社,2002
[71]张以谟,应用光学,北京:机械工业出版社,1982
[72]张立昆,擒纵轮半自动视觉检测系统的设备构建与调整,硕士学位论文,天津大学,2009
[73]2009版微视凌志|代理机器视觉|产品大全,北京微视凌志图像技术有限公司
[74]龚昊,吕乃光,娄小平等,二维视觉测量中光轴与载物台垂直度调节方法,北京机械工业学院学报,2006,21(3):35~38
[75]牟丽,杨敏,垂直度的计算机视觉检测算法研究,现代制造工程,2007,3:101~103
[76]杨再华,李玉和,李庆祥等,基于边缘特征提取的图像清晰度评价函数,计算机工程与应用,2005,10:35~37
[77]朱孔凤,姜威,王端芳等,一种新的图像清晰度评价函数,红外与激光工程,2005,34(4):464~468
[78]倪军,袁家虎,吴钦章,基于边缘特征的光学图像清晰度判定,中国激光,2009,36(1):172~176
[79]Jian Li,Renbiao Wu,Victor C.Chen,Robust autofocus algorithm for ISAR imaging of moving targets,IEEE Transactions on Aerospace and Electronic Systems,2001,37(3):1056~1069
[80]S.Jutamulia , T.Asakura , R.D.Bahuguna , Autofocusing based on power-spectra analysis,Appl.Optics,1994,33(26):6210~6212
[81]包学诚,摄影镜头的光学原理及应用技巧,上海:上海交通大学出版社,1999
[82]张进,王仲,李霞,微型零件中圆孔的高精度定位方法,电子测量与仪器学报,2008,22(3):47~50
[83]周贤,姜威,基于图像边缘能量的自动聚焦算法,光学技术,2006,32(2):213~216
[84]李霞,基于模板的微型零件完整成像测量方法的研究,硕士学位论文,天津大学,2007
[85]贡力,基于完整图像的微型零件精密测试技术研究,硕士学位论文,天津大学,2009
[86]Kozo Ohtani,Mitsuru Baba,A Fast edge location measurement with subpixel accuracy using a CCD image,IEEE Instrumentation and Measurement Technology Conference,2001:2087~2092
[87]Venkatachalam.V , Wasserman R.M , Comprehensive investigation of subpixel edge detection schemes in metrology,Proceedings of the SPIE - The International Society for Optical Engineering,2003:200~211
[88]乔辉,亚像素边缘检测算法及集成块管脚外观检测系统的研究,硕士学位论文],南开大学,2003
[89]Tabatabai A J,Mitchell O R,Edge location to subpixel values in digital imagery,IEEE Trans on Pattem Analysis and Machine Intelligence,1984, 6(2):188~201
[90]Lyvers E P,Mitchell O R,et al,Subpixel measurements using a moment-based edge operator,IEEE Trans. on PAMI,1989,11(12): 1293~1309
[91]刘亚威,杨丹,张小洪,基于空间矩的亚像素边缘定位技术的研究,计算机应用,2003,23(2):47~49
[92]张永宏,胡德金,徐俊杰,基于视觉图像的机加工零部件亚像素边缘定位,机械工程学报,2004,40(6):179~182
[93]Ghosal S,Mehrotra R,Edge detection using orthogonal moment-based operators,IEEE Trans. on PAMI,1992,7(12):413~417
[94]曾绍标,熊洪允,毛云英,应用数学基础(下册),天津:天津大学出版社,1994,22~24
[95]苏步青,刘鼎元,计算几何,上海:上海科学技术出版社,1981,149~156
[96]Zhang.J,Wang.Z,Yang C,et al,Sub-pixel Edge Estimation Based on Matching Template,International Conference on Optical Instruments and Technology, 2008, 71602A-1~71602A-9
[97]周智浩,基于序列图像的二维超分辨率重构技术研究,硕士学位论文,浙江大学,2006
[98]LEUNG K.T,TONG C.S,Effective use of low resolution images for super-resolution reconstruction,1st International Congress on Image and Signal Processing,2008: 320~325
[99]XIAO Q,DING X H,QIAN K,et al,A new method for multi-frame super-resolution reconstruction,Proceedings of the 2009 International Joint Conference on Computational Sciences and Optimization,2009:892~895
[100]覃凤清,何小海,陈为龙等,一种图像配准的超分辨率重建,光学精密工程,2009,17(2):409~416
[101]徐正平,翟林培,葛文奇等,亚像元的CCD几何超分辨方法,光学精密工程,2008,16(12):2447~2452
[102]黄战华,蔡怀宇,张以谟等,基于半像素错位的多幅图像重建高分辨率图像技术研究,光学技术,2002,28(5):389~394
[103]王凌,张平,冯华君等,用多次移位成像提高CCD成像分辨力的反演解析法,光电工程,2003,30(3):62~65
[104]杜娟,余英林,谢胜利,基于半像素运动信息的快速超分辨率图像重构算法,华南理工大学学报(自然科学版),2005,33(5):53~58
[105]曹聚亮,图像超分辨率处理、成像及其相关技术研究,博士学位论文,国防科学技术大学,2004
[106]费业泰,误差理论与数据处理,北京:机械工业出版社,2000
[107]袁野,摄像机标定方法及边缘检测和轮廓跟踪算法研究,博士学位论文,大连理工大学,2002
[108]屈玉福,视觉坐标测量机三维动态测量技术的研究,博士学位论文,哈尔滨工业大学,2004
[109]朱铮涛,黎绍发,镜头畸变及其校正技术,光学技术,2005,1(31):136~138
[110]R.K.Lenz,R.Y.Tsai,Techniques for calibration of the scale factor and image center for high accuracy 3D machine vision metrology,IEEE Trans. on PAMI,1998,10(5):713~720
[111]高满屯,曲仕如,李西琴,计算机视觉研究中的投影理论和方法,西安:西北工业大学出版社,1998
[112]Rafael Kelly,Fernando Reyes,On vision systems identification with application to Fixed-Camera robotic systems , IEEE Trans Robotics Automation,2000,11:170~180
[113]I.Sobel,On calibrating computer controlled cameras for perceiving 3-D scenes,Artificial Intelligence,1974,5(2):185~188
[114]Tsai R.Y,An efficient and accurate camera calibration technique for 3D machine vision,Proc.CVPR’86,New York: IEEE,1986:363~374
[115]杨纯,擒纵轮视觉检测仪测量系统研究,硕士学位论文,天津大学,2010
[116]朱诗生,张惠珍,人机交互软件界面设计,信息技术,2009,(5):36~39
[117]杨宝华,袁志树,文昌辞,应用软件人际界面优化的研究,电脑知识与技术,2009,(5):4817~4818
[118]VC知识库文章:http://www.vckbase.com/document/viewdoc/?id=518
[119]VC知识库文章:http://www.vckbase.com/document/viewdoc/?id=519