基于微零件测量的自动对焦技术研究
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摘要
基于计算机视觉的精密测量技术具有操作简易、非接触、精度高等特点,广泛应用于工程领域,也适用于微零件装配的高精度在线测量。光学系统对所成图像的细节分辨能力是影响图像的视觉测量精度的主要因素:当图像对焦时才最清楚,具有更多的细节,便于后续的精密测量工作;而当图像离焦时,图像模糊,细节丢失,就无法对微零件进行形状或者位置的检测。因此如何获取对焦面就是基于计算机视觉精密测量的重要前提。
本论文叙述了自动对焦的历史背景,分析了图像离焦的具体原因,详细介绍了自动对焦的各种传统方法,并且对基于图像的自动对焦技术进行了深入的研究,这包括了图像的预处理技术、对焦区域的设计技术、清晰度评价函数的技术以及聚焦点搜索算法技术。
1)对图像的几种滤波去噪的方法进行了实验验证,分析了其对清晰度评价函数曲线的影响,综合考虑了滤波效果和算法速度,最终选择中值滤波作为本课题滤波方法;
2)对几种对焦区域的设计算法进行了实验验证,并且结合本课题,对柱腔的待测对象采用手动对焦区域设计算法、对低对比度下的微零件小球的待测对象采用环状区域设计算法;
3)研究了各种聚焦点搜索算法,对两种新型的搜索算法,通过仿真实验分析了其优缺点,并且将基于最优化理论的抛物线法设计为聚焦点的搜索算法,与其它几种常用的搜索算法进行了实验比较,说明了其耗时较少,对焦较准确的优点。
4)研究了各种常用的清晰度评价函数,对其进行了实验与分析,比较了各种函数的优劣性;针对低对比度环境下大多数清晰度评价函数失去理想特性的问题,提出了一种基于Zernike正交矩的清晰度评价函数,通过调节各阶矩的权重系数,可以适应不同对比度下的自动对焦。
5)搭建了自动对焦实验平台,对本文研究的自动对焦算法进行了系统实现。
Computer vision-based precision measurement technology with easy operation, strong anti-jamming, high precision, has been widely used in the engineering fields, applicable to micro-parts assembly process of high-precision measurement. the ability of imaging systems for optical images to distinguish details that affect the accuracy of digital image optical measurement: When the image is in focus, it is most clear with more detail, the precise measurement is easier; and when the image deviate from the focus, the image blur, detail is lost, detect the shape or location of micro-parts becoming more difficult. So how to get the focus area exactly has become a urgent problem to solve.
This paper studies the historical development of auto-focus, analyzed the specific reasons of out-of-focus image, described the various traditional methods of auto-focus in detail, and in-depth studied image-based autofocus technology, which including the image preprocessing technology ,focus area designing, autofocusing function and the focal point of the search algorithm technology.
1) Verified several image filtering denoising method through experiments , analyzed their impact on AF function curve, considering the filtering results and algorithms speed, finally chose median filtering as the subject filtering method;
2) Verified several focus area designing algorithms, combined with the issue, designed the algorithm with manual focus area for the column cavity, designed the algorithm with circular focus area for the micro-ball under low contrast;
3) Studied a variety of focal point searching algorithms, through simulation experiments, analyzed two new search algorithms’advantages and disadvantages, and designed a new focal point searching algorithm with parabolic method based on based on optimization theory, compared with several common searching algorithms, demonstrated its advantages of less time-consuming, focusing accurately;
4) Studied a variety of commonly used AF function, compared the advantages and disadvantages of various functions through analysis, and for the problem that the most AF functions losing their ideal characteristics under low-contrast environment , proposed an AF function based on Zernike orthogonal moments, by adjusting the weight coefficients of order moments, can adapt to the autofocus under different contrast;
5) Built an auto-focus experimental platform, achieved the AF algorithm of the paper studied through the system.
本论文叙述了自动对焦的历史背景,分析了图像离焦的具体原因,详细介绍了自动对焦的各种传统方法,并且对基于图像的自动对焦技术进行了深入的研究,这包括了图像的预处理技术、对焦区域的设计技术、清晰度评价函数的技术以及聚焦点搜索算法技术。
1)对图像的几种滤波去噪的方法进行了实验验证,分析了其对清晰度评价函数曲线的影响,综合考虑了滤波效果和算法速度,最终选择中值滤波作为本课题滤波方法;
2)对几种对焦区域的设计算法进行了实验验证,并且结合本课题,对柱腔的待测对象采用手动对焦区域设计算法、对低对比度下的微零件小球的待测对象采用环状区域设计算法;
3)研究了各种聚焦点搜索算法,对两种新型的搜索算法,通过仿真实验分析了其优缺点,并且将基于最优化理论的抛物线法设计为聚焦点的搜索算法,与其它几种常用的搜索算法进行了实验比较,说明了其耗时较少,对焦较准确的优点。
4)研究了各种常用的清晰度评价函数,对其进行了实验与分析,比较了各种函数的优劣性;针对低对比度环境下大多数清晰度评价函数失去理想特性的问题,提出了一种基于Zernike正交矩的清晰度评价函数,通过调节各阶矩的权重系数,可以适应不同对比度下的自动对焦。
5)搭建了自动对焦实验平台,对本文研究的自动对焦算法进行了系统实现。
Computer vision-based precision measurement technology with easy operation, strong anti-jamming, high precision, has been widely used in the engineering fields, applicable to micro-parts assembly process of high-precision measurement. the ability of imaging systems for optical images to distinguish details that affect the accuracy of digital image optical measurement: When the image is in focus, it is most clear with more detail, the precise measurement is easier; and when the image deviate from the focus, the image blur, detail is lost, detect the shape or location of micro-parts becoming more difficult. So how to get the focus area exactly has become a urgent problem to solve.
This paper studies the historical development of auto-focus, analyzed the specific reasons of out-of-focus image, described the various traditional methods of auto-focus in detail, and in-depth studied image-based autofocus technology, which including the image preprocessing technology ,focus area designing, autofocusing function and the focal point of the search algorithm technology.
1) Verified several image filtering denoising method through experiments , analyzed their impact on AF function curve, considering the filtering results and algorithms speed, finally chose median filtering as the subject filtering method;
2) Verified several focus area designing algorithms, combined with the issue, designed the algorithm with manual focus area for the column cavity, designed the algorithm with circular focus area for the micro-ball under low contrast;
3) Studied a variety of focal point searching algorithms, through simulation experiments, analyzed two new search algorithms’advantages and disadvantages, and designed a new focal point searching algorithm with parabolic method based on based on optimization theory, compared with several common searching algorithms, demonstrated its advantages of less time-consuming, focusing accurately;
4) Studied a variety of commonly used AF function, compared the advantages and disadvantages of various functions through analysis, and for the problem that the most AF functions losing their ideal characteristics under low-contrast environment , proposed an AF function based on Zernike orthogonal moments, by adjusting the weight coefficients of order moments, can adapt to the autofocus under different contrast;
5) Built an auto-focus experimental platform, achieved the AF algorithm of the paper studied through the system.
引文
[1]章毓晋,图像工程下册——图像理解与计算机视觉,北京:清华大学出版社,2000,29~30
[2] http://www3.xitek.com/papers/xitek/xitekoldpaper/afhistory.htm
[3] Kay S M, Marple S L Jr, Spectrum Analysis-A Modern Perspective,Proceedings of the IEEE, 1981, 69(11):1380~1419
[4] Ingram M, Preston K J,Automatic analysis of blood cells,Scientific American, 1970, 223(5):72~82
[5] Mortimer L Mendelsohn, Brian H Mayall,Computer-Oriented analysis of human chromosomes—III. Focus, Computers in Biology and Medicine, 1972,2(2):137~150
[6] Jarvis RA, Focus optimization criteria for computer image processing,Microscope ,1976,24(2):163~180
[7] Richard A Muller, Andrew Buffington ,Real-time correction of atmospherically degraded telescope images through image sharpening, J. Opt. Soc. Am,1974,64(9):1200~1210
[8] Ahmed Erteza,Sharpness index and its application to focus control,Applied Optics,1976,15(4):877~ 881
[9] Ahmed Erteza, Depth of convergence of a sharpness index autofocus system,Applied Optics,1977,16(8):2273~ 2278
[10] Brenner JF, Dew BS, Horton JB, et al,An automated microscope for cytologic research a preliminary evaluation,Journal of Histochemistry & Cytochemistry,1976,24(1):100~ 111
[11] Lawrence Firestone, Kitty Cook, Kevin Culp ,et al,Comparison of Autofocus Methods for Automated Microscopy,Cytometry,1991,12(3):195~ 206
[12] Frans C A Groen, Ian T Young, Guido Ligthart, A comparison of different focus functions for use in autofocus algorithms, Cytometry ,1985,6(2):81~ 91
[13]白立芬,徐毓娴等,基于图像处理的显微镜自动调焦方法研究,仪器仪表学报,1999,12(6):612~ 614
[14]瞿蓬,林喜荣,一种基于图像处理的自动调焦系统,电子技术应用,2002,28(10):33~ 35
[15]李奇,冯华君,徐之海,面向自动对焦的图像预处理技术,光电工程,2004,31(9):66~ 68
[16]黄剑琪,徐之海,冯华君等,基于分辨力空间变化的自动对焦方法,光电工程,2001,28(l):22~ 26
[17]李奇,冯华君,徐之海,自动对焦系统中图像非均匀采样的实验研究,光子学报,2003,32(12): 1499~ 1501
[18]裴锡宇,冯华君,李奇等,一种基于频谱分析的离焦深度自动对焦法,光电工程,2003,30(5):62~ 65
[19]刘义鹏,裴锡宇,冯华君等,一种基于DFD的自动对焦算法,2005,27(4):39~ 43
[20]康宗明,张利,谢攀,一种基于能量和熵的自动聚焦算法,2003,31(5):552~ 555
[21]谢攀,张利,康宗明等,一种基于尺度变化的DCT自动聚焦算法,清华大学学报,2003,43(l): 55~ 58
[22]符冉迪,易文娟,郁梅等,基于Hadamard变换的数码显微成像自动对焦新方法, 2008,19(12):1690~ 1693
[23]郑玉珍,吴勇,倪旭翔,实时自动对焦的研究,光电工程,2004,31(4):64~ 66
[24]陈晓彬,基于小波的自动对焦算法研究,通信技术,2010,43(6):210~ 212
[25]刘文耀,光电图像处理,北京:电子工业出版社,2000
[26] M Subbarao, Tae-Sun Choi, Arman Nikzad.Focusing Techniques,Optical Engineering ,32(11): 2824~2836
[27] M Subbarao,Efficient depth recovery through inverse optics,Machine Vision for Inspection and Measurement, Academic Press ,1989:101~126
[28] M Subbarao, Determining Distance from Defocused Images of Simple Objects,Tech. Report No. 89.07.20, Computer Vision Laboratory, Dept. of Electrical Engineering, State University of New York, Stony Brook, NY 11794-2350,1989
[29]田万成,朴宗根,电视摄象机光学镜头自动聚焦的研究,电视技术,1987,4:8~13
[30]安文化,现代照相机技术,北京:北京理工大学出版社,1992
[31]李奇,数字自动对焦技术的理论及实现方法研究,博士学位论文,杭州:浙江大学,2004
[32]李奇,冯华君,徐之海,用于全数字对焦的点扩散函数性能分析与评价,浙江大学学报(工学版),2006,40(6):1093~ 1096
[33]丁明全,自动对焦技术在舌像采集系统中的应用研究,硕士学位论文,广州:广东工业大学,2011
[34] Sang Ku Kim, Joon Ki Paik,Out-of-focus blur estimation and restoration for digital auto-focusing system, Electronics Letters,1998,34(12): 1217– 1219
[35]姜三平,混合傅立叶—小波图像降噪及激光测速靶信号处理,博士学位论文,太原:中北大学,2008
[36] Norbert Wiener,Extrapolation, interpolation, and smoothing of stationary time series: with engineering applications,Journal of the American Statistical Association,1949,47(258):319
[37]李淑霞,王汝霖,李春梅等,基于噪声方差估计的小波阈值图像去噪新方法,计算机应用研究,2007,1:220~ 221
[38]朱孔凤,自动聚焦区域选择算法,安徽大学学报(自然科学版),2009,33(2):31~ 34
[39]王彦芳,姜威,应用于聚焦窗口自适应选择的人工鱼群算法改进,计算机工程与应用,2011,47(14):180~ 182
[40]田宜彬,数字成像系统的自动对焦算法研究,硕士学位论文,杭州:浙江大学,2002
[41] http://mathworld.wolfram.com/LorentzianFunction.html
[42] Siavash Yazdanfar, Kevin B Kenny, Krenar Tasimi, et a, Simple and robust image-based autofocusing for digital microscopy, OPTICS EXPRESS,2008,16(12):8670~8677
[43] Chen C M, Hong C M, Hsieh Y R, A Modeling Technique of Grey Prediction Model Using Discrete Difference Equation,The Journal of Grey System, 2000,12(1): 65~72
[44]解可新,韩建,林友联,最优化方法,天津:天津大学出版社,1997
[45] Yibin Tian, Kevin Shieh, Christine F Wildsoet,Performance of focus measures in the presence of nondefocus aberrations, J. Opt. Soc. Am,2007,24(12),165~173
[46]原育凯,光学系统的自动调焦方法,红外,2004,4:15~ 21
[47]李奇,冯华君,徐之海等,数字图象清晰度评价函数研究,光子学报,2002,31(6):736~ 738
[48] Gamadia M, Kehtarnavaz N, Roberts-Hoffman K,Low-Light Auto-Focus Enhancement for Digital and Cell-Phone Camera Image Pipelines,Consumer Electronics,IEEE Transactions on,2007,53(2):249 ~ 257
[49]王耀明,图像的矩函数:原理、算法及应用,上海:华东理工大学出版社,2002
[50] Teague M R, Image analysis via the general theory of moments,JOSA ,1980 ,70 (8) :920~930
[51] Ghosal S,Mehrotra R,Orthogonal moment operators for subpixel edge detection,Pattern Recognition,1993,26(2):295~306
[52]高世一,赵明扬,张雷等,基于Zernike正交矩的图像亚像素边缘检测算法改进,自动化学报,2008,34(9):1163~1168
[53]李蓉芳,微零件基本特征的测量技术研究,硕士学位论文,天津:天津大学,2009
[2] http://www3.xitek.com/papers/xitek/xitekoldpaper/afhistory.htm
[3] Kay S M, Marple S L Jr, Spectrum Analysis-A Modern Perspective,Proceedings of the IEEE, 1981, 69(11):1380~1419
[4] Ingram M, Preston K J,Automatic analysis of blood cells,Scientific American, 1970, 223(5):72~82
[5] Mortimer L Mendelsohn, Brian H Mayall,Computer-Oriented analysis of human chromosomes—III. Focus, Computers in Biology and Medicine, 1972,2(2):137~150
[6] Jarvis RA, Focus optimization criteria for computer image processing,Microscope ,1976,24(2):163~180
[7] Richard A Muller, Andrew Buffington ,Real-time correction of atmospherically degraded telescope images through image sharpening, J. Opt. Soc. Am,1974,64(9):1200~1210
[8] Ahmed Erteza,Sharpness index and its application to focus control,Applied Optics,1976,15(4):877~ 881
[9] Ahmed Erteza, Depth of convergence of a sharpness index autofocus system,Applied Optics,1977,16(8):2273~ 2278
[10] Brenner JF, Dew BS, Horton JB, et al,An automated microscope for cytologic research a preliminary evaluation,Journal of Histochemistry & Cytochemistry,1976,24(1):100~ 111
[11] Lawrence Firestone, Kitty Cook, Kevin Culp ,et al,Comparison of Autofocus Methods for Automated Microscopy,Cytometry,1991,12(3):195~ 206
[12] Frans C A Groen, Ian T Young, Guido Ligthart, A comparison of different focus functions for use in autofocus algorithms, Cytometry ,1985,6(2):81~ 91
[13]白立芬,徐毓娴等,基于图像处理的显微镜自动调焦方法研究,仪器仪表学报,1999,12(6):612~ 614
[14]瞿蓬,林喜荣,一种基于图像处理的自动调焦系统,电子技术应用,2002,28(10):33~ 35
[15]李奇,冯华君,徐之海,面向自动对焦的图像预处理技术,光电工程,2004,31(9):66~ 68
[16]黄剑琪,徐之海,冯华君等,基于分辨力空间变化的自动对焦方法,光电工程,2001,28(l):22~ 26
[17]李奇,冯华君,徐之海,自动对焦系统中图像非均匀采样的实验研究,光子学报,2003,32(12): 1499~ 1501
[18]裴锡宇,冯华君,李奇等,一种基于频谱分析的离焦深度自动对焦法,光电工程,2003,30(5):62~ 65
[19]刘义鹏,裴锡宇,冯华君等,一种基于DFD的自动对焦算法,2005,27(4):39~ 43
[20]康宗明,张利,谢攀,一种基于能量和熵的自动聚焦算法,2003,31(5):552~ 555
[21]谢攀,张利,康宗明等,一种基于尺度变化的DCT自动聚焦算法,清华大学学报,2003,43(l): 55~ 58
[22]符冉迪,易文娟,郁梅等,基于Hadamard变换的数码显微成像自动对焦新方法, 2008,19(12):1690~ 1693
[23]郑玉珍,吴勇,倪旭翔,实时自动对焦的研究,光电工程,2004,31(4):64~ 66
[24]陈晓彬,基于小波的自动对焦算法研究,通信技术,2010,43(6):210~ 212
[25]刘文耀,光电图像处理,北京:电子工业出版社,2000
[26] M Subbarao, Tae-Sun Choi, Arman Nikzad.Focusing Techniques,Optical Engineering ,32(11): 2824~2836
[27] M Subbarao,Efficient depth recovery through inverse optics,Machine Vision for Inspection and Measurement, Academic Press ,1989:101~126
[28] M Subbarao, Determining Distance from Defocused Images of Simple Objects,Tech. Report No. 89.07.20, Computer Vision Laboratory, Dept. of Electrical Engineering, State University of New York, Stony Brook, NY 11794-2350,1989
[29]田万成,朴宗根,电视摄象机光学镜头自动聚焦的研究,电视技术,1987,4:8~13
[30]安文化,现代照相机技术,北京:北京理工大学出版社,1992
[31]李奇,数字自动对焦技术的理论及实现方法研究,博士学位论文,杭州:浙江大学,2004
[32]李奇,冯华君,徐之海,用于全数字对焦的点扩散函数性能分析与评价,浙江大学学报(工学版),2006,40(6):1093~ 1096
[33]丁明全,自动对焦技术在舌像采集系统中的应用研究,硕士学位论文,广州:广东工业大学,2011
[34] Sang Ku Kim, Joon Ki Paik,Out-of-focus blur estimation and restoration for digital auto-focusing system, Electronics Letters,1998,34(12): 1217– 1219
[35]姜三平,混合傅立叶—小波图像降噪及激光测速靶信号处理,博士学位论文,太原:中北大学,2008
[36] Norbert Wiener,Extrapolation, interpolation, and smoothing of stationary time series: with engineering applications,Journal of the American Statistical Association,1949,47(258):319
[37]李淑霞,王汝霖,李春梅等,基于噪声方差估计的小波阈值图像去噪新方法,计算机应用研究,2007,1:220~ 221
[38]朱孔凤,自动聚焦区域选择算法,安徽大学学报(自然科学版),2009,33(2):31~ 34
[39]王彦芳,姜威,应用于聚焦窗口自适应选择的人工鱼群算法改进,计算机工程与应用,2011,47(14):180~ 182
[40]田宜彬,数字成像系统的自动对焦算法研究,硕士学位论文,杭州:浙江大学,2002
[41] http://mathworld.wolfram.com/LorentzianFunction.html
[42] Siavash Yazdanfar, Kevin B Kenny, Krenar Tasimi, et a, Simple and robust image-based autofocusing for digital microscopy, OPTICS EXPRESS,2008,16(12):8670~8677
[43] Chen C M, Hong C M, Hsieh Y R, A Modeling Technique of Grey Prediction Model Using Discrete Difference Equation,The Journal of Grey System, 2000,12(1): 65~72
[44]解可新,韩建,林友联,最优化方法,天津:天津大学出版社,1997
[45] Yibin Tian, Kevin Shieh, Christine F Wildsoet,Performance of focus measures in the presence of nondefocus aberrations, J. Opt. Soc. Am,2007,24(12),165~173
[46]原育凯,光学系统的自动调焦方法,红外,2004,4:15~ 21
[47]李奇,冯华君,徐之海等,数字图象清晰度评价函数研究,光子学报,2002,31(6):736~ 738
[48] Gamadia M, Kehtarnavaz N, Roberts-Hoffman K,Low-Light Auto-Focus Enhancement for Digital and Cell-Phone Camera Image Pipelines,Consumer Electronics,IEEE Transactions on,2007,53(2):249 ~ 257
[49]王耀明,图像的矩函数:原理、算法及应用,上海:华东理工大学出版社,2002
[50] Teague M R, Image analysis via the general theory of moments,JOSA ,1980 ,70 (8) :920~930
[51] Ghosal S,Mehrotra R,Orthogonal moment operators for subpixel edge detection,Pattern Recognition,1993,26(2):295~306
[52]高世一,赵明扬,张雷等,基于Zernike正交矩的图像亚像素边缘检测算法改进,自动化学报,2008,34(9):1163~1168
[53]李蓉芳,微零件基本特征的测量技术研究,硕士学位论文,天津:天津大学,2009