视觉测量关键技术及在自动检测中的应用
|
摘要
随着计算机视觉技术和光电技术的飞速发展,视觉测量技术得到了迅速发展和广泛应用,其作为一种非接触测量手段已经越来越引起人们的重视。
本文深入研究了基于计算机视觉测量技术的系统方案、软硬件设计,对视觉检测的图像获取、图像处理、亚像素定位技术及系统标定、调焦的关键技术进行了深入分析,并实现了视觉测量在喷油器底座工件自动检测系统中的应用。
喷油器底座是汽车油路中的重要部件,由金属精密冲压、内圆磨削而成。该类零件主要用于与柱形零件进行精密配合焊接装配,为保证装配精度,需要对零件的内尺寸进行精密测量。喷油器底座呈碗形,内壁表面是强反射表面,碗口处与圆倒角相连,底部与碗底的曲面连接。采用视觉测量的方法,以内壁口处边缘的投影作为被测边缘,建立了工件视觉自动检测系统,提高了工件测量的精度和速度。
本文研究的主要内容有:
1.基于视觉测量技术建立了喷油器底座内尺寸自动检测系统,完成了视觉系统、软件系统和控制执行系统的软硬件设计。强反射表面的检测是视觉检测的难题,通过对工件反射性能的分析,设计了发光强度连续可调的均匀散射LED背光光源,使得被测边缘在图像中真实体现出来,实现了工件强反射内表面的视觉检测,提高了测量精度。设计了工件的自动上料、自动定位及自动分选机构,真正实现了工件的全自动化测量,提高了检测效率。
2.对视觉测量系统的图像处理算法进行了研究。研究了视觉测量系统中图像预处理、阈值分割的算法;对常用边缘检测算法进行分析,根据本系统测量图像边缘简单、对比度高的特点,提出了基于阈值分割及链码跟踪的边缘检测算法;分析了二次曲线拟合法、多项式拟合法、空间矩、灰度矩等亚像素算法,并进行了实验研究。
3.对视觉测量系统的标定技术进行了研究。分析了二维视觉测量系统的摄像机成像的数学模型;设计了精密平面网格靶标,提出了基于灰度统计分布的图像分割方法进行特征点提取;提出基于图像的测量平面与光轴垂直度的快速调整方法;对该测量系统用实验分析了现有的标定方法,并提出分区线性标定方法,将测量图像分成多个小区域,对每个区域分别进行线性标定,减小了标定误差。
4.对视觉测量系统的调焦技术进行实验研究。对常用的调焦评价函数进行了对比性实验,分析了调焦区域、边缘点数及光源强度对调焦函数的影响。用实验分析了调焦精度对标定结果的影响。提出了一种基于特征边缘跟踪的调焦评价方法,解决了被测工件图像中边缘在高度上不共面时普通调焦函数无法进行正确调焦定位的问题,提高了工件的调焦精度。
5.分析了曲线拟合特征参数的计算方法。对工件测量系统进行了实验研究和误差分析。
With the rapid development of computer vision technology and photovoltaic technology, computer vision based precision measurement technology has been well developed and widely applied in various fields. As a non-contact measurement approach, computer vision measurement technique is playing a more and more significant role.
The thesis has deeply investigated a series of relevant key topics, including system scheme of precision measurement based on the computer vision, design of software and hardware system, acquisition and processing of the measurement images, sub-pixel positioning, calibration of the measurement system, the key technology of focusing. Furthermore, the built computer vision measurement system is successfully applied in the automatic measurement system for injector base.
The injector base, fabricated by metal casting and stamping, is an important part in automobile oil circuits. Such parts are mainly used for welding assembly with cylinder parts. In order to ensure the accuracy of assembly, the inside dimension of the parts are required to be measured accurately. The injector base displays as a bowl shape, and the inner surface is a strong reflecting surface. The edge of the base is connected with the circular bevel, and the bottom surface is linked with the curved face of the base. The projection of the inner surface edge is employed as the measurement object. With the built automatic computer vision precise measurement system, the accuracy and speed of the part measurement are greatly improved.
The main contributions of the thesis include:
1. An automatic computer-vision based system for the precise measurement of the injector base inner dimension is designed and built. The relevant designs of computer-vision system, software system, controlling and actuating system are completed. The detection of strong reflecting surface is always a challenging topic in the field of computer vision based measurement technique. Through the analysis on the reflecting feature of the object part, we design a LED back lighting source with uniform scattering, hence, the edge in the measurement image is greatly enhanced. Consequently, the vision measurement of the inner surface of the part is completed with a higher accuracy. Additionally, the automatic charging of the parts, automatic positioning, and automatic sorting mechanism are design to realize a genuine automatic measurement and further enhance the efficiency of measurement.
2. The imaging processing algorithms for the computer vision based measurement system are studied. The preprocessing and threshold segmentation algorithms are investigated. Through the analysis of common edge detection algorithms and the simple edge, high-contrast characteristics of the measurement image, we propose a novel edge detection algorithm based on the edge segmentation and the chain code tracking. In addition, several sub-pixel algorithms, including the conic curve fitting, polynomial fitting, space mement, grey moment, are studied both theoretically and experimentally.
3. The calibration technique for the computer vision based measurement system is studied. The mathematic model of camera imaging is analyzed, and the appropriate plane grid target for the experiment is designed. Furthermore, a rapid adjustment method based on the image measurement plane and the verticality of optical axis is proposed. According to the existing calibration approach for the measurement system, we present a novel method using linear calibration for different zones. The method put the measurement image into several zones so that the linear calibration can work for different zones respectively. As a result, the calibration errors are minimized.
4. The focusing technique for the measurement system is experimentally studied. The common evaluation functions for focusing are experimentally compared. And the influences resulting from the focusing region, number of edge point, and the intensity of light source are analyzed. And the influence on the calibration result due to the accuracy of focusing is experimentally analyzed. A focusing evaluation method based on the characteristic edge tracking is propose, with the result that the evaluation function can be correctly focusing and positioning even when the height of the edge in the part measurement image is not coplanar. Hence, the focusing accuracy is improved to a higher degree.
5. The characteristic parameters of the curve fitting method are analyzed. And the measurement system is experimentally studied and the relevant errors are investigated.
本文深入研究了基于计算机视觉测量技术的系统方案、软硬件设计,对视觉检测的图像获取、图像处理、亚像素定位技术及系统标定、调焦的关键技术进行了深入分析,并实现了视觉测量在喷油器底座工件自动检测系统中的应用。
喷油器底座是汽车油路中的重要部件,由金属精密冲压、内圆磨削而成。该类零件主要用于与柱形零件进行精密配合焊接装配,为保证装配精度,需要对零件的内尺寸进行精密测量。喷油器底座呈碗形,内壁表面是强反射表面,碗口处与圆倒角相连,底部与碗底的曲面连接。采用视觉测量的方法,以内壁口处边缘的投影作为被测边缘,建立了工件视觉自动检测系统,提高了工件测量的精度和速度。
本文研究的主要内容有:
1.基于视觉测量技术建立了喷油器底座内尺寸自动检测系统,完成了视觉系统、软件系统和控制执行系统的软硬件设计。强反射表面的检测是视觉检测的难题,通过对工件反射性能的分析,设计了发光强度连续可调的均匀散射LED背光光源,使得被测边缘在图像中真实体现出来,实现了工件强反射内表面的视觉检测,提高了测量精度。设计了工件的自动上料、自动定位及自动分选机构,真正实现了工件的全自动化测量,提高了检测效率。
2.对视觉测量系统的图像处理算法进行了研究。研究了视觉测量系统中图像预处理、阈值分割的算法;对常用边缘检测算法进行分析,根据本系统测量图像边缘简单、对比度高的特点,提出了基于阈值分割及链码跟踪的边缘检测算法;分析了二次曲线拟合法、多项式拟合法、空间矩、灰度矩等亚像素算法,并进行了实验研究。
3.对视觉测量系统的标定技术进行了研究。分析了二维视觉测量系统的摄像机成像的数学模型;设计了精密平面网格靶标,提出了基于灰度统计分布的图像分割方法进行特征点提取;提出基于图像的测量平面与光轴垂直度的快速调整方法;对该测量系统用实验分析了现有的标定方法,并提出分区线性标定方法,将测量图像分成多个小区域,对每个区域分别进行线性标定,减小了标定误差。
4.对视觉测量系统的调焦技术进行实验研究。对常用的调焦评价函数进行了对比性实验,分析了调焦区域、边缘点数及光源强度对调焦函数的影响。用实验分析了调焦精度对标定结果的影响。提出了一种基于特征边缘跟踪的调焦评价方法,解决了被测工件图像中边缘在高度上不共面时普通调焦函数无法进行正确调焦定位的问题,提高了工件的调焦精度。
5.分析了曲线拟合特征参数的计算方法。对工件测量系统进行了实验研究和误差分析。
With the rapid development of computer vision technology and photovoltaic technology, computer vision based precision measurement technology has been well developed and widely applied in various fields. As a non-contact measurement approach, computer vision measurement technique is playing a more and more significant role.
The thesis has deeply investigated a series of relevant key topics, including system scheme of precision measurement based on the computer vision, design of software and hardware system, acquisition and processing of the measurement images, sub-pixel positioning, calibration of the measurement system, the key technology of focusing. Furthermore, the built computer vision measurement system is successfully applied in the automatic measurement system for injector base.
The injector base, fabricated by metal casting and stamping, is an important part in automobile oil circuits. Such parts are mainly used for welding assembly with cylinder parts. In order to ensure the accuracy of assembly, the inside dimension of the parts are required to be measured accurately. The injector base displays as a bowl shape, and the inner surface is a strong reflecting surface. The edge of the base is connected with the circular bevel, and the bottom surface is linked with the curved face of the base. The projection of the inner surface edge is employed as the measurement object. With the built automatic computer vision precise measurement system, the accuracy and speed of the part measurement are greatly improved.
The main contributions of the thesis include:
1. An automatic computer-vision based system for the precise measurement of the injector base inner dimension is designed and built. The relevant designs of computer-vision system, software system, controlling and actuating system are completed. The detection of strong reflecting surface is always a challenging topic in the field of computer vision based measurement technique. Through the analysis on the reflecting feature of the object part, we design a LED back lighting source with uniform scattering, hence, the edge in the measurement image is greatly enhanced. Consequently, the vision measurement of the inner surface of the part is completed with a higher accuracy. Additionally, the automatic charging of the parts, automatic positioning, and automatic sorting mechanism are design to realize a genuine automatic measurement and further enhance the efficiency of measurement.
2. The imaging processing algorithms for the computer vision based measurement system are studied. The preprocessing and threshold segmentation algorithms are investigated. Through the analysis of common edge detection algorithms and the simple edge, high-contrast characteristics of the measurement image, we propose a novel edge detection algorithm based on the edge segmentation and the chain code tracking. In addition, several sub-pixel algorithms, including the conic curve fitting, polynomial fitting, space mement, grey moment, are studied both theoretically and experimentally.
3. The calibration technique for the computer vision based measurement system is studied. The mathematic model of camera imaging is analyzed, and the appropriate plane grid target for the experiment is designed. Furthermore, a rapid adjustment method based on the image measurement plane and the verticality of optical axis is proposed. According to the existing calibration approach for the measurement system, we present a novel method using linear calibration for different zones. The method put the measurement image into several zones so that the linear calibration can work for different zones respectively. As a result, the calibration errors are minimized.
4. The focusing technique for the measurement system is experimentally studied. The common evaluation functions for focusing are experimentally compared. And the influences resulting from the focusing region, number of edge point, and the intensity of light source are analyzed. And the influence on the calibration result due to the accuracy of focusing is experimentally analyzed. A focusing evaluation method based on the characteristic edge tracking is propose, with the result that the evaluation function can be correctly focusing and positioning even when the height of the edge in the part measurement image is not coplanar. Hence, the focusing accuracy is improved to a higher degree.
5. The characteristic parameters of the curve fitting method are analyzed. And the measurement system is experimentally studied and the relevant errors are investigated.
引文
[1]叶声华,王仲,精密测试技术展望,中国机械工程,2000,11(3):262～263
[2]殷纯永,仪器科学与技术发展建议,中国机械工程,2000,11(3):264～266
[3]朱铮涛,视觉测量技术及其在现代制造业中的应用,现代制造工程,2004,4:59～61
[4] N.Aleixos,J.Blasco,F.Navarron,Multispectral inspection of citrus in real-time using machine vision and digital signal processors,Computers and Electronics in Agriculture,2002,33:121～137
[5]王江枫,罗锡文,洪添胜等,计算机视觉技术在芒果重量及果面坏损检测中的应用,农业工程学报,1998,(4):186～189
[6]冯斌,汪懋华,基于计算机视觉的水果大小检测方法,农业机械学报,2003,34(1):73～75
[7]应义斌,景寒松,马俊福等,黄花梨品质检测机器视觉系统,农业机械学报,2000,31(2):113～115
[8]李庆中,汪娥华,农业生物模式识别中的计算机视觉技术,中国图像图形学报,1999,4(7):610～616
[9]张建平,吴守一,方如明等,烟叶自动分级模型的建立与训练,农业工程学报,1997,(4):179～183
[10] Kawamura S,Natsuga M,Takekura K,et al,Development of an automatic rice-quality inspection system,Transaction of the ASAE,2002,45(2):379～387
[11] Zhang Q,Yang W,Howard L,et al,Tracing fissure information by scanning electron microscopy characterization of naturally fissured surfaces of rice kernels,Transactions of the ASAE,2003,46(6):1583～1588
[12]应义斌,饶秀勤,赵匀等,机器视觉技术在农产品品质自动识别中的应用研究进展,农业工程学报,2000,16(3):4～7
[13]朱正德,谈“机器视觉”在汽车制造业中的应用,中国测试技术,2006,32(5):22～25
[14] W.A.Perkins,INSPECTOR:A Computer vision system which learn to inspect parts,IEEE Trans,PAMI-5,pp:584～592
[15] 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,pp:43～55
[16]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
[17] Tsatsoulis.C,Fu.K.S,A computer vision system for assembly inspection,Intelligent Robots and Computer Vision,1984:352～357
[18] Gregory.P.J,Taylor.C.J,Knowledge-based models for computer vision,Proceedings of the 4th International Conference on Robot Vision and Sensory Control,1988:325～330
[19] Franci Lahajnar,Machine vision system for inspecting electric plates,Computer in Industry,2002,47:113～122
[20] Keiichiro Kagawa,Koutaro Yasuoka,David C.Ng,Pulse-domain digital image processing for vision chips employing low-voltage operation in deep-submicrometer technologies,IEEE Journal of Selected Topics in Quantum Electronics,2004,10(4):816～828
[21]罗志勇,刘栋玉,罗新宇,新型高温钢坯长度在线测量系统,光电工程,1995,22(5):32～40
[22]胡亮,线阵CCD实现钢板表面缺陷在线检测关键技术及其应用研究:[博士学位论文],天津:天津大学,2005
[23]张建荣,姜昱明,CCD成像在线测量玻璃棒直径的方法研究,应用光学,2004,25(3):53～56
[24] J.Lassoe,Future vision system for glass works,Glass Technology,1997,38(2):43～45
[25] 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
[26]杨敏,基于机器视觉的发动机气门杆直径及圆度检测研究:[博士学位论文],广州:华南理工大学,2004
[27]王建民,浦昭邦,晏磊等,大尺寸弧长图像测量系统及其图像处理方法的研究,宇航计测技术,2000,5:51～56
[28]洪海涛,赵辉,图像技术用于零件尺寸测量的研究,仪器仪表学报,2001,22(3):214～218
[29] Liangyu Lei,Xiaojun Zhou,Mingqing Pan,Automated vision inspection system for the size measurement of workpieces , Instrumentation and measurement technology conference,2005,872～877
[30]王仲春,高岳,黄粤熙等,显微成像检测表面粗糙度,光学技术,1998,5:46～48
[31]白素平,车英,周建民,火炮内膛表面粗糙度检测技术,长春光学精密机械学院学报,2000,24(1):12～14
[32]左奇,史忠科,基于胶囊完整性检测系统研究,西安交通大学学报,2002,(12):1262～1265
[33] Jome Derganc, Bostjan Likar, Rok Bernard,Real-time automated visual inspection of color tablets in phamaceutical blisters,Real-Time Imaging,2003,9:113～124
[34] Melvyn L,Smith, Richard J.Stamp,Automated inspection of textured ceramic tiles,Computers in Industry,2000,43:73～82
[35] Costas Boukouvalas,ASSIST: automatic system for surface inspection and sorting of tiles Journal of Materials Processing Technology,1998,82:179～188
[36] Bento B Correin,A computer vision system for the automatic measurement of volumes of wood,SPIE,1993:206～214
[37]李立轻,基于计算机视觉的织物疵点自动检测研究:[博士学位论文],上海:东华大学,2003
[38]崔扬,图像检测技术在皮革缺陷检测中的应用研究:[博士学位论文],杭州:浙江大学,2004
[39]赵辉,浦昭邦,刘国栋等,小孔径超精测量方法的研究,激光杂志,2000,21(6):28～29
[40]李斐,郭辉,孙长库等,薄孔壁厚和小孔径测量系统,天津大学学报,2004,37(10):914～917
[41]岳晓峰,栾宝剑,韩立强,不规则圆形视觉检测方法研究,机械,2004,31(11):55～58
[42]张广军,贺俊吉,基于圆结构光的内表面三维视觉检测模型,仪器仪表学报,2004,25(4):481～484
[43]梁鸿生,王新房,汤晓君等,金属工件孔径电涡流非接触在线测量的研究,陕西工学院学报,2001,16(3):14～17
[44]何学军,熊昌友,李华峰等,光电显微镜在孔径测量中的应用,航空计测技术,2002,22(6):11～12、46
[45]李岩,花国梁,精密测量技术,北京:中国计量出版社,2001
[46]王丽,小尺寸孔径测量的研究:[硕士学位论文],西安:西安工业学院,2001
[47] www.lusterlighttech.com
[48] www.kjk.com.cn
[49] www.china-image.cn
[50]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,2005
[51]唐向阳,张勇,李江有等,机器视觉关键技术的现状及应用展望,昆明理工大学学报,2004,29(2):36～39
[52]张广军,光电测试技术,北京:中国计量出版社,2003
[53]王庆有,CCD应用技术,天津:天津大学出版社,2000
[54] J.S.Kane,光学设计是机器视觉系统的关键,红外,1999,(8):37～39
[55]浦昭邦,光电测试技术,北京:机械工业出版社,2005
[56]浦昭邦,屈玉福,王亚爱,视觉检测系统中照明光源的研究,仪器仪表学报,2003,24(3):438～439
[57]康华光,电子技术基础,北京:高等教育出版社,1997
[58]钱小龙,曲兴华,陈勇等,可连续调节亮度均匀照明光源设计及在表面缺陷检测中的应用,制造业自动化,2005,27(12):43～45、54
[59]郁道银,谈恒英,工程光学,北京:机械工业出版社,1999
[60]方佩敏,高效、恒流驱动LED控制器MAX1698,无线电,2003,(5):49
[61]章毓晋,图像分析,北京:清华大学出版社,2005
[62] 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
[63]杨丽凤,面阵CCD高精度测量应用技术:[硕士学位论文],太原:太原理工大学, 2002
[64]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],广州:华南理工大学,2004
[65]何斌,马天予,王运坚等,Visual C++数字图像处理,北京:人民邮电出版社,2001
[66]贺忠海,王宝光,理想边缘产生方法的研究,光学精密工程,2002,10(1):89～93
[67] C Atae-Allah,M Cabrerizo-Vilchez,J F Gomez-Lopera,Measurement of surface tension and contact angle using entropic edge detection,Measurement Science and Technology,2001,12:288～298
[68]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],长春:吉林大学,2005
[69]陈勇,基于机器视觉的表面缺陷检测系统的算法研究及软件设计:[硕士学位论文],天津:天津大学,2006
[70] Pakkanen J,Iivarinen J,A novel self-organizing neural network for defect image classification , Neural Networks , Proceedings. 2004 IEEE International Joint Conference,2004,4:2553～2556
[71]季虎,孙即祥,邵晓芳等,图像边缘提取方法及展望,计算机工程与应用,2004,(14):70～73
[72] Roberts L G,Machine Perception of Three-dimensional Solids,Optical and Electrooptical Information processing,MIT Press,1965
[73] Prewitt.J,Object enhancement and extraction,Academic Press,New York,1970
[74] Kirsch.R,Computer determination of the constituent structure of biological images,Computer and Biomedical Research,1971,14(3)
[75] Rosenfeld.A,Thurston.M,Edge and curve detection for visual scene analysis,IEEE Trans,1971,C-20(5)
[76] Berzins V,Accuracy of Laplacian detections,CVGIP,1984,27(2):195～210
[77]吴炯,张秀彬,张峰等,数字图像中边缘算法的实验研究,上海交通大学学报,2003
[78] Steve R.Gunn,On the discrete representation of the Laplacian of Gaussian,Pattern Recognition,1999,32(8):1463～1472
[79] Illingworth J,Kittler J,A survey of the Hough transform,Computer Vision,Graphics Image Process,1988,44:87～116
[80]刘勋,毋立芳,林娟,一种改进的Hough变换提取圆的方法,信号处理,2004,20(6):623～627
[81] Remy Bulot,Jean-Marc Boi,Contour segmentation using Hough transform,Image Processing,1996 Proceedings,1996,3:583～586
[82]崔屹,图像处理与分析—数学形态学方法及应用,北京:科学出版社,2000
[83] Bhabatosh Chanda , Malay K Kundu , Y Vani Padmaja , A multi-scale morphologic edge detector,Pattern Pecognition,1998,31(10):146
[84]徐震浩,雷志勇,基于数学形态学的弹丸边缘检测技术,西安工业学院学报,2002,22(2):136～140
[85] Fei-Long Chen,Shianr When Lin,Subpixel estimation of circle parameters using prthogonal circular detector,Computer Vision and image understanding,2000:206～221
[86]范生红,黄桂平,陈继华等,Canny算子对人工标志中心的亚像素精度定位,测绘科学技术学报,2006,23(1):76～78
[87]郑南宁,计算机视觉与模式识别,北京:国防工业出版社,1998
[88]贺忠海,王宝光,廖怡白等,利用曲线拟合方法的亚像素提取算法,仪器仪表学报,2003,24(2):195～197
[89]张洪涛,段发阶,叶声华,一种快速亚像素边缘检测方法研究,计量学报,2002,23(4):263～265、270
[90]刘力双,电子摄像式刀具预调测量仪的研究:[博士学位论文],天津:天津大学,2006
[91] 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
[92] Venkatachalam.V,Wasserman R.M,Comprehensive investigation of subpixel edge detection schemes in metrology,Proceedings of the SPIE - The International Society for Optical Engineering,2003,5011:200-11
[93]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],天津:南开大学,2003
[94] Tababai A.J,and Mitchell.O.E,Edge location to subpixel values in digital imagery,IEEE Trans. On Pami,1984,6( 2):188～201
[95]张永宏,胡德金,张凯等,基于灰度矩的CCD图像亚像素边缘检测算法研究,光学技术,2004,30(6):693～695、698
[96]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:大连理工大学,2002
[97]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:哈尔滨工业大学,2004
[98]孙长库,叶声华,激光测量技术,天津:天津大学出版社,2001
[99] S.Ganapaphy,Decomposition of transformation matrics for robot rision,Proc. Int. Conf. Robotics and Automation,1984:130～139.
[100]高立志,方勇,林志航等,高精度立体视觉测量中的一种通用的摄像机标定技术,机械科学与技术,1998,17(5):809～811
[101] 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
[102]张艳珍,欧宗瑛,一种新的摄像机线性标定方法,中国图像图形学报,2001,6(8):727～731
[103] Rafael Kelly,Fernando Reyes,On vision systems ldentification with application to Fixed-Camera robotic systems,IEEE Trans Robotics Automation,2000,11:170～180
[104] I.Sobel,On calibrating computer controlled cameras for perceiving 3-D scenes,Artificial Intelligence,1974,5(2):185～188
[105] Tsai R.Y,An efficient and accurate camera calibration technique for 3D machine vision,Proc.CVPR’86,New York: IEEE,1986:363～374
[106] Yonghuai Liu,Automatic 3d free form shape matching using the graduated assignment algorithm,Pattern Recognition,2005,38:1615～1631
[107] Lenz R.K,Tsai R.Y,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
[108]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
[109] Zhang.Z,A flexible new technique for camera calibration,Microsoft Corporation:Technical Report MSR-TR-98-71,1998
[110]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
[111] Fadi Dornaika,Christophe Garcia. Pose estimation using point and line correspondences,Real-Time Imaging,1999,5(5):215～230
[112] Ma Songde,A self-calibration technique for active vision systems,IEEE Transactions on robotics and automation,1996,12(1):114～120
[113]雷成,吴福朝,胡占义,一种新的基于主动视觉系统的摄像机自标定方法,计算机学报,2000,23(11):1130～1139
[114]李华,吴福朝,胡占义,一种新的线性摄像机自标定方法,计算机学报,2000,23(11):1121～1129
[115] Richard I.Hartley , Self-calibration of stationary cameras. International journal of computer vision,1997,22(1):5～23
[116] Lourdes Agapito,E.Hayman,I.Reid,Self-calibration of rotating and zooming cameras,International journal of computer vision,2001,45(2):107～127
[117] Wong K K,Mendonca P R S,Cipolla R,Camera calibration from surfaces of revolution,IEEE Transactions on PAMI,2003,25(2):147～161
[118] Zhengyou Zhang,A flexible new technique for camera calibration,IEEE Transactions on PAMI,2000,22(11):1330～1334
[119]杨长江,孙凤梅,胡占义,基于二次曲线的纯旋转摄像机自标定,自动化学报,2001,27(3):310～317
[120]张洪涛,荫罩板计算机视觉检测系统研究:[硕士学位论文],天津:天津大学,2002
[121]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
[122]鲍歌堂,视觉检测系统中快速自动调焦技术的研究:[硕士学位论文],上海:上海交通大学,2005
[123]廖延彪,光学原理与应用,北京:电子工业出版社,2006
[124]郭彦珍,邱宗明,李信等,图像测量技术中一种调焦的判别方法,西安理工大学学报,2001,17(1):40～42
[125] 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
[126]赵辉,鲍歌堂,陶卫,图像测量中自动调焦函数的实验研究与分析,光学精密工程,2004,12(5):531～536
[127] S.Jutamulia , T.Asakura , R.D.Bahuguna , Autofocusing based on power-spectra analysis,Appl.Optics,1994,33(26):6210～6212
[128] J.R.Fienup,Detecting moving targets in SAR imagery by focusing,IEEE Transactions on Aerospace and Electronic Systems,2001,37(3):794～809
[129]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):35-36、161
[130]胡涛,陈世哲,刘国栋等,大范围自动调焦快速搜索算法,光电子.激光,2006,17(4):464～467
[131] I.Kharitonenko , X.Zhang , Digital focus detector for mobile video communicators,IEEE Transactions on Consumer Electronics,2000,46(1):237～240
[132]费业泰,误差理论与数据处理,北京:机械工业出版社,2000
[2]殷纯永,仪器科学与技术发展建议,中国机械工程,2000,11(3):264～266
[3]朱铮涛,视觉测量技术及其在现代制造业中的应用,现代制造工程,2004,4:59～61
[4] N.Aleixos,J.Blasco,F.Navarron,Multispectral inspection of citrus in real-time using machine vision and digital signal processors,Computers and Electronics in Agriculture,2002,33:121～137
[5]王江枫,罗锡文,洪添胜等,计算机视觉技术在芒果重量及果面坏损检测中的应用,农业工程学报,1998,(4):186～189
[6]冯斌,汪懋华,基于计算机视觉的水果大小检测方法,农业机械学报,2003,34(1):73～75
[7]应义斌,景寒松,马俊福等,黄花梨品质检测机器视觉系统,农业机械学报,2000,31(2):113～115
[8]李庆中,汪娥华,农业生物模式识别中的计算机视觉技术,中国图像图形学报,1999,4(7):610～616
[9]张建平,吴守一,方如明等,烟叶自动分级模型的建立与训练,农业工程学报,1997,(4):179～183
[10] Kawamura S,Natsuga M,Takekura K,et al,Development of an automatic rice-quality inspection system,Transaction of the ASAE,2002,45(2):379～387
[11] Zhang Q,Yang W,Howard L,et al,Tracing fissure information by scanning electron microscopy characterization of naturally fissured surfaces of rice kernels,Transactions of the ASAE,2003,46(6):1583～1588
[12]应义斌,饶秀勤,赵匀等,机器视觉技术在农产品品质自动识别中的应用研究进展,农业工程学报,2000,16(3):4～7
[13]朱正德,谈“机器视觉”在汽车制造业中的应用,中国测试技术,2006,32(5):22～25
[14] W.A.Perkins,INSPECTOR:A Computer vision system which learn to inspect parts,IEEE Trans,PAMI-5,pp:584～592
[15] 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,pp:43～55
[16]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
[17] Tsatsoulis.C,Fu.K.S,A computer vision system for assembly inspection,Intelligent Robots and Computer Vision,1984:352～357
[18] Gregory.P.J,Taylor.C.J,Knowledge-based models for computer vision,Proceedings of the 4th International Conference on Robot Vision and Sensory Control,1988:325～330
[19] Franci Lahajnar,Machine vision system for inspecting electric plates,Computer in Industry,2002,47:113～122
[20] Keiichiro Kagawa,Koutaro Yasuoka,David C.Ng,Pulse-domain digital image processing for vision chips employing low-voltage operation in deep-submicrometer technologies,IEEE Journal of Selected Topics in Quantum Electronics,2004,10(4):816～828
[21]罗志勇,刘栋玉,罗新宇,新型高温钢坯长度在线测量系统,光电工程,1995,22(5):32～40
[22]胡亮,线阵CCD实现钢板表面缺陷在线检测关键技术及其应用研究:[博士学位论文],天津:天津大学,2005
[23]张建荣,姜昱明,CCD成像在线测量玻璃棒直径的方法研究,应用光学,2004,25(3):53～56
[24] J.Lassoe,Future vision system for glass works,Glass Technology,1997,38(2):43～45
[25] 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
[26]杨敏,基于机器视觉的发动机气门杆直径及圆度检测研究:[博士学位论文],广州:华南理工大学,2004
[27]王建民,浦昭邦,晏磊等,大尺寸弧长图像测量系统及其图像处理方法的研究,宇航计测技术,2000,5:51～56
[28]洪海涛,赵辉,图像技术用于零件尺寸测量的研究,仪器仪表学报,2001,22(3):214～218
[29] Liangyu Lei,Xiaojun Zhou,Mingqing Pan,Automated vision inspection system for the size measurement of workpieces , Instrumentation and measurement technology conference,2005,872～877
[30]王仲春,高岳,黄粤熙等,显微成像检测表面粗糙度,光学技术,1998,5:46～48
[31]白素平,车英,周建民,火炮内膛表面粗糙度检测技术,长春光学精密机械学院学报,2000,24(1):12～14
[32]左奇,史忠科,基于胶囊完整性检测系统研究,西安交通大学学报,2002,(12):1262～1265
[33] Jome Derganc, Bostjan Likar, Rok Bernard,Real-time automated visual inspection of color tablets in phamaceutical blisters,Real-Time Imaging,2003,9:113～124
[34] Melvyn L,Smith, Richard J.Stamp,Automated inspection of textured ceramic tiles,Computers in Industry,2000,43:73～82
[35] Costas Boukouvalas,ASSIST: automatic system for surface inspection and sorting of tiles Journal of Materials Processing Technology,1998,82:179～188
[36] Bento B Correin,A computer vision system for the automatic measurement of volumes of wood,SPIE,1993:206～214
[37]李立轻,基于计算机视觉的织物疵点自动检测研究:[博士学位论文],上海:东华大学,2003
[38]崔扬,图像检测技术在皮革缺陷检测中的应用研究:[博士学位论文],杭州:浙江大学,2004
[39]赵辉,浦昭邦,刘国栋等,小孔径超精测量方法的研究,激光杂志,2000,21(6):28～29
[40]李斐,郭辉,孙长库等,薄孔壁厚和小孔径测量系统,天津大学学报,2004,37(10):914～917
[41]岳晓峰,栾宝剑,韩立强,不规则圆形视觉检测方法研究,机械,2004,31(11):55～58
[42]张广军,贺俊吉,基于圆结构光的内表面三维视觉检测模型,仪器仪表学报,2004,25(4):481～484
[43]梁鸿生,王新房,汤晓君等,金属工件孔径电涡流非接触在线测量的研究,陕西工学院学报,2001,16(3):14～17
[44]何学军,熊昌友,李华峰等,光电显微镜在孔径测量中的应用,航空计测技术,2002,22(6):11～12、46
[45]李岩,花国梁,精密测量技术,北京:中国计量出版社,2001
[46]王丽,小尺寸孔径测量的研究:[硕士学位论文],西安:西安工业学院,2001
[47] www.lusterlighttech.com
[48] www.kjk.com.cn
[49] www.china-image.cn
[50]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,2005
[51]唐向阳,张勇,李江有等,机器视觉关键技术的现状及应用展望,昆明理工大学学报,2004,29(2):36～39
[52]张广军,光电测试技术,北京:中国计量出版社,2003
[53]王庆有,CCD应用技术,天津:天津大学出版社,2000
[54] J.S.Kane,光学设计是机器视觉系统的关键,红外,1999,(8):37～39
[55]浦昭邦,光电测试技术,北京:机械工业出版社,2005
[56]浦昭邦,屈玉福,王亚爱,视觉检测系统中照明光源的研究,仪器仪表学报,2003,24(3):438～439
[57]康华光,电子技术基础,北京:高等教育出版社,1997
[58]钱小龙,曲兴华,陈勇等,可连续调节亮度均匀照明光源设计及在表面缺陷检测中的应用,制造业自动化,2005,27(12):43～45、54
[59]郁道银,谈恒英,工程光学,北京:机械工业出版社,1999
[60]方佩敏,高效、恒流驱动LED控制器MAX1698,无线电,2003,(5):49
[61]章毓晋,图像分析,北京:清华大学出版社,2005
[62] 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
[63]杨丽凤,面阵CCD高精度测量应用技术:[硕士学位论文],太原:太原理工大学, 2002
[64]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],广州:华南理工大学,2004
[65]何斌,马天予,王运坚等,Visual C++数字图像处理,北京:人民邮电出版社,2001
[66]贺忠海,王宝光,理想边缘产生方法的研究,光学精密工程,2002,10(1):89～93
[67] C Atae-Allah,M Cabrerizo-Vilchez,J F Gomez-Lopera,Measurement of surface tension and contact angle using entropic edge detection,Measurement Science and Technology,2001,12:288～298
[68]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],长春:吉林大学,2005
[69]陈勇,基于机器视觉的表面缺陷检测系统的算法研究及软件设计:[硕士学位论文],天津:天津大学,2006
[70] Pakkanen J,Iivarinen J,A novel self-organizing neural network for defect image classification , Neural Networks , Proceedings. 2004 IEEE International Joint Conference,2004,4:2553～2556
[71]季虎,孙即祥,邵晓芳等,图像边缘提取方法及展望,计算机工程与应用,2004,(14):70～73
[72] Roberts L G,Machine Perception of Three-dimensional Solids,Optical and Electrooptical Information processing,MIT Press,1965
[73] Prewitt.J,Object enhancement and extraction,Academic Press,New York,1970
[74] Kirsch.R,Computer determination of the constituent structure of biological images,Computer and Biomedical Research,1971,14(3)
[75] Rosenfeld.A,Thurston.M,Edge and curve detection for visual scene analysis,IEEE Trans,1971,C-20(5)
[76] Berzins V,Accuracy of Laplacian detections,CVGIP,1984,27(2):195～210
[77]吴炯,张秀彬,张峰等,数字图像中边缘算法的实验研究,上海交通大学学报,2003
[78] Steve R.Gunn,On the discrete representation of the Laplacian of Gaussian,Pattern Recognition,1999,32(8):1463～1472
[79] Illingworth J,Kittler J,A survey of the Hough transform,Computer Vision,Graphics Image Process,1988,44:87～116
[80]刘勋,毋立芳,林娟,一种改进的Hough变换提取圆的方法,信号处理,2004,20(6):623～627
[81] Remy Bulot,Jean-Marc Boi,Contour segmentation using Hough transform,Image Processing,1996 Proceedings,1996,3:583～586
[82]崔屹,图像处理与分析—数学形态学方法及应用,北京:科学出版社,2000
[83] Bhabatosh Chanda , Malay K Kundu , Y Vani Padmaja , A multi-scale morphologic edge detector,Pattern Pecognition,1998,31(10):146
[84]徐震浩,雷志勇,基于数学形态学的弹丸边缘检测技术,西安工业学院学报,2002,22(2):136～140
[85] Fei-Long Chen,Shianr When Lin,Subpixel estimation of circle parameters using prthogonal circular detector,Computer Vision and image understanding,2000:206～221
[86]范生红,黄桂平,陈继华等,Canny算子对人工标志中心的亚像素精度定位,测绘科学技术学报,2006,23(1):76～78
[87]郑南宁,计算机视觉与模式识别,北京:国防工业出版社,1998
[88]贺忠海,王宝光,廖怡白等,利用曲线拟合方法的亚像素提取算法,仪器仪表学报,2003,24(2):195～197
[89]张洪涛,段发阶,叶声华,一种快速亚像素边缘检测方法研究,计量学报,2002,23(4):263～265、270
[90]刘力双,电子摄像式刀具预调测量仪的研究:[博士学位论文],天津:天津大学,2006
[91] 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
[92] Venkatachalam.V,Wasserman R.M,Comprehensive investigation of subpixel edge detection schemes in metrology,Proceedings of the SPIE - The International Society for Optical Engineering,2003,5011:200-11
[93]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],天津:南开大学,2003
[94] Tababai A.J,and Mitchell.O.E,Edge location to subpixel values in digital imagery,IEEE Trans. On Pami,1984,6( 2):188～201
[95]张永宏,胡德金,张凯等,基于灰度矩的CCD图像亚像素边缘检测算法研究,光学技术,2004,30(6):693～695、698
[96]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:大连理工大学,2002
[97]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:哈尔滨工业大学,2004
[98]孙长库,叶声华,激光测量技术,天津:天津大学出版社,2001
[99] S.Ganapaphy,Decomposition of transformation matrics for robot rision,Proc. Int. Conf. Robotics and Automation,1984:130～139.
[100]高立志,方勇,林志航等,高精度立体视觉测量中的一种通用的摄像机标定技术,机械科学与技术,1998,17(5):809～811
[101] 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
[102]张艳珍,欧宗瑛,一种新的摄像机线性标定方法,中国图像图形学报,2001,6(8):727～731
[103] Rafael Kelly,Fernando Reyes,On vision systems ldentification with application to Fixed-Camera robotic systems,IEEE Trans Robotics Automation,2000,11:170～180
[104] I.Sobel,On calibrating computer controlled cameras for perceiving 3-D scenes,Artificial Intelligence,1974,5(2):185～188
[105] Tsai R.Y,An efficient and accurate camera calibration technique for 3D machine vision,Proc.CVPR’86,New York: IEEE,1986:363～374
[106] Yonghuai Liu,Automatic 3d free form shape matching using the graduated assignment algorithm,Pattern Recognition,2005,38:1615～1631
[107] Lenz R.K,Tsai R.Y,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
[108]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
[109] Zhang.Z,A flexible new technique for camera calibration,Microsoft Corporation:Technical Report MSR-TR-98-71,1998
[110]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
[111] Fadi Dornaika,Christophe Garcia. Pose estimation using point and line correspondences,Real-Time Imaging,1999,5(5):215～230
[112] Ma Songde,A self-calibration technique for active vision systems,IEEE Transactions on robotics and automation,1996,12(1):114～120
[113]雷成,吴福朝,胡占义,一种新的基于主动视觉系统的摄像机自标定方法,计算机学报,2000,23(11):1130～1139
[114]李华,吴福朝,胡占义,一种新的线性摄像机自标定方法,计算机学报,2000,23(11):1121～1129
[115] Richard I.Hartley , Self-calibration of stationary cameras. International journal of computer vision,1997,22(1):5～23
[116] Lourdes Agapito,E.Hayman,I.Reid,Self-calibration of rotating and zooming cameras,International journal of computer vision,2001,45(2):107～127
[117] Wong K K,Mendonca P R S,Cipolla R,Camera calibration from surfaces of revolution,IEEE Transactions on PAMI,2003,25(2):147～161
[118] Zhengyou Zhang,A flexible new technique for camera calibration,IEEE Transactions on PAMI,2000,22(11):1330～1334
[119]杨长江,孙凤梅,胡占义,基于二次曲线的纯旋转摄像机自标定,自动化学报,2001,27(3):310～317
[120]张洪涛,荫罩板计算机视觉检测系统研究:[硕士学位论文],天津:天津大学,2002
[121]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
[122]鲍歌堂,视觉检测系统中快速自动调焦技术的研究:[硕士学位论文],上海:上海交通大学,2005
[123]廖延彪,光学原理与应用,北京:电子工业出版社,2006
[124]郭彦珍,邱宗明,李信等,图像测量技术中一种调焦的判别方法,西安理工大学学报,2001,17(1):40～42
[125] 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
[126]赵辉,鲍歌堂,陶卫,图像测量中自动调焦函数的实验研究与分析,光学精密工程,2004,12(5):531～536
[127] S.Jutamulia , T.Asakura , R.D.Bahuguna , Autofocusing based on power-spectra analysis,Appl.Optics,1994,33(26):6210～6212
[128] J.R.Fienup,Detecting moving targets in SAR imagery by focusing,IEEE Transactions on Aerospace and Electronic Systems,2001,37(3):794～809
[129]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):35-36、161
[130]胡涛,陈世哲,刘国栋等,大范围自动调焦快速搜索算法,光电子.激光,2006,17(4):464～467
[131] I.Kharitonenko , X.Zhang , Digital focus detector for mobile video communicators,IEEE Transactions on Consumer Electronics,2000,46(1):237～240
[132]费业泰,误差理论与数据处理,北京:机械工业出版社,2000
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |