阵列式自动光学检测方法研究
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摘要
AOI(Automated Optical Inspection)为自动光学检测,是用高性能数码相机(camera)摄取影像,而影像是由像素组成,系统将实际影像进行分析,与标准影像比对之后,即可判定是通过或错误,称为pixel grid processing,属于一种外观检验的方式。随着产业工艺进化,元件微型化趋势不断推进,AOI在SMT(表面贴装技术)业内蓬勃发展,新的元件规格对原有的AOI系统的处理精度及速度提出了挑战,而另一种AOI系统架构更显优势:阵列影像侦测系统。
针对影像模组,为适应里面的硬件式编和各存储器大小的限制,提出了图像数值化的检测方法,是用图像的几项特征值代表图像本身进行检测。
对于PC本身,提出了图像对比方法,这时一种模版匹配方法,是计算检测图与模版图(标准图)的相似程度一种检测方法。在检测前,进行了放缩与模糊的操作。
针对元件、电路板上的文字本身,提出了文字投射检测方法,这是用文字进行投影后,计算投影曲线与标准曲线的差异程度来检测的方法。在检测前,进行收缩膨胀、图像增强的预处理操作。
这些方法适用于阵列式AOI的各个部分,可以在各自的地方进行检测工作,以达到全部检测的目的。
AOI is short for Automated Optical Inspection,using high-performance digital camera to take images, while the images are formed by the pixels.This system analysis the actual image ,compared with standard imaging features, after, you can determine this is right or wrong.This process is known as the pixel grid processing ,belong the appearance test approach.. With the development of the industry techniques, AOI is flourished and progressing quickly. Facing the challenge, which from the new part specification, another AOI system architecture is brought forward, that is Array, arranged Image System.
For the image module, In order to meet the hardware-based series inside and the memory size limit, we make the image values method .This detection method is using several image characteristic values as the image itself , then use they to test.
For the PC itself, we make the method of image compare, one of a template matching method . It is a method that calculate degree of similitude between the inspect image and the template image(standard image) .Before that we can use zoom operation and fuzzy operaton as pretreatement.
For the text on components and circuit board. We make the character text projection inspect method . After project character, we calculate the degree of difference between text projection cruve and the standard projection cruve. Before that we use corrosion expansion operation and image enhance operation as pretreatement.
These methods applied to various parts of AOI array and can be tested in their respective areas of work in order to achieve the purpose of all inspection.
针对影像模组,为适应里面的硬件式编和各存储器大小的限制,提出了图像数值化的检测方法,是用图像的几项特征值代表图像本身进行检测。
对于PC本身,提出了图像对比方法,这时一种模版匹配方法,是计算检测图与模版图(标准图)的相似程度一种检测方法。在检测前,进行了放缩与模糊的操作。
针对元件、电路板上的文字本身,提出了文字投射检测方法,这是用文字进行投影后,计算投影曲线与标准曲线的差异程度来检测的方法。在检测前,进行收缩膨胀、图像增强的预处理操作。
这些方法适用于阵列式AOI的各个部分,可以在各自的地方进行检测工作,以达到全部检测的目的。
AOI is short for Automated Optical Inspection,using high-performance digital camera to take images, while the images are formed by the pixels.This system analysis the actual image ,compared with standard imaging features, after, you can determine this is right or wrong.This process is known as the pixel grid processing ,belong the appearance test approach.. With the development of the industry techniques, AOI is flourished and progressing quickly. Facing the challenge, which from the new part specification, another AOI system architecture is brought forward, that is Array, arranged Image System.
For the image module, In order to meet the hardware-based series inside and the memory size limit, we make the image values method .This detection method is using several image characteristic values as the image itself , then use they to test.
For the PC itself, we make the method of image compare, one of a template matching method . It is a method that calculate degree of similitude between the inspect image and the template image(standard image) .Before that we can use zoom operation and fuzzy operaton as pretreatement.
For the text on components and circuit board. We make the character text projection inspect method . After project character, we calculate the degree of difference between text projection cruve and the standard projection cruve. Before that we use corrosion expansion operation and image enhance operation as pretreatement.
These methods applied to various parts of AOI array and can be tested in their respective areas of work in order to achieve the purpose of all inspection.
引文
[1]陆国权.世界电子元件现状与发展趋势.世界产品与技术, 2003, (12): 34-41
[2]罗兵,曾歆懿,季秀霞. SMT产品缺陷及相应的AOI检测方法.电子质量, 2006, 4(6): 35-37
[3] F Martn Rodrguez, M. Garca Saburido, J L Alba Castro. New methods for the automatic reading of vehicle license plates. Heraklion Creta Greece, 2002: 67-72
[4]陈传波,金先级.数字图像处理.北京:华中科技大学出版社, 2004: 267-271
[5]刘中合,王瑞雪,王锋德.数字图像处理技术现状与展望.计算机时代, 2005, 8(9): 6-8
[6]卡斯特曼.数字图像处理.北京:电子工业出版社, 2002: 126-130
[7] Yamaguchi A, Komuro O. Characterization of line edge roughness in resist patterns by Fourier analysis and auto-correlation function. Microprocesses and Nanotechnology Conference, Digest of Papers.Microprocesses and Nanotechnology, 2002(10): 80-81
[8]于殿泓.图像检测与处理技术.西安:西安电子科技大学出版社, 2006: 246-250
[9] Neal B Gallagher. Multivariate Image Analysis Past Present and Future-A Biased View. Eigenvector Research Inc, 2000: 42-46
[10] Jean-Marc Peallat and Mark J Norris. Aoi: Facing The Challenges Of 0201. Vi Technology, LLC Haverhill MA, 2002: 11-13
[11] Mark J Norris. Advances in Automatic Optical Inspection: Gray Scale Correlation vs Vectoral Imaging. IEEE Computer, 2000(8): 13-15
[12] Dahnoun N. Digital Signal Processing Implementation using the TMS320C6000DSP Platform. Prentice Hall, 2000: 50-53
[13] Michael J Smith, Keith Fairchild. Understanding the Costs Benefits and ROI of adding AXI Versus AOI to an ICT Line. IEEE Computer, 1998(2): 06-09
[14] Kenneth R Castleman. Digital Image Processing.北京:北京电子工业出版社, 1999: 31-34
[15]孙即祥.模式识别中的特征提取与计算机视觉不变量.北京:国防工业出版社, 2001: 248-250
[16] Jacky Baltes. Efficient Image Processing for Increased Resolution and Color Correctness of CMOS Image Sensors. Lecture Notes in Computer Science Volume 2377/2002 Robot Soccer World Cup, 2001: 92-93
[17]郭艳萍.检测自动化中的数字图像处理及识别: [硕士学位论文].河海:河海大学图书馆, 2002
[18] Zhang C. Optical Profilometry and its Applications. Ph D Thesis, State University of New York at Stony Brook, 2001: 28-32
[19] Egidijus Paliulis, Raimondas Zemblys, Gintautas daunys. Image analysis Problems in aoi systems. Issn 1392 C 124X Information Technologyand Control, 2008: 37-39
[20] F Mohanna. Performance evaluation of corner detectors using consistency and accuracy. Computer Vision and Image Understanding measures, 2006: 81-94
[21] Q. Gao, L Zhang, D Zhang, J Yang. Comments on On Image Matrix Based Feature Extraction Algo rithms. IEEE Transactions on Systems Man and Cybernetics, 2007: 06-11
[22] Dr Antonius,B Wijanarto. Image enhancement Fundamental Remote Sensing, 2002: 19-23
[23] John Wiley, Sons Ltd. Computer processing of remotely sensed images:an introduction 3rd. Mather, Paul M, 2004: 32-36
[24] Robinson. Measuring the ocean from space:the principles and methods of satellite oceanography .Ian S, 2004: 669-670
[25]陈从颜.结构光投影法在三维检测和物象重建系统中的应用.计算机应用与研究, 1999(7): 78-79
[26]罗兵,张云. SMT焊膏印刷质量自动光学检测.电子质量报, 2005(12): 30-32.
[27] B K P Horn. Shape from Shading. A Method for Obtaining the Shape of a Smooth Opaque Object from one View. PhD thesis,Department of Electrical Engineering, MIT, 1999: 3-9
[28]刘继胜,钟良.机器视觉技术在质量检测中的应用.现代制造工程, 2004(2): 99-101
[29] Akuta T, Ngistit Y. Development of an automatic 3-D shape measuring system using a new auto-focusing method. Measurement, 1991, 9(3): 98-103
[30] John A. Pearce. Biomedical Image Processing with Morphology-Based Nonlinear Filters . Rebecca Richards-Kortum, 2000: 45-46
[31] J Song and E J Delp. A study of the generalized morphological filter. Circuits Syst Signal Process, 1992: 110-113
[32] Sangwine SJ, Horne REN. The color Image Processing Handbook. M Chapman& Hall London, 1998: 76-83
[33] C.Vonesch, F.Aguet. The Colored revolution of bioimaging. IEEE signal processing magazine, 2006: 20-21
[34] R C Gonzales, R E Woods. Digital Image processing using Matlab. Pearson/Merrill/ Prentice Hall, 2004: 213-221
[35] E Meijering, I Smal, G Danuser. Tracking imolecular bio imaging. IEEE signal processing magazine, 2006(6): 9-15
[36] J De Bock, W Philips. Line segment based water shed segmentation. Third International Conference, 2007: 203-205
[37] Jonas De Vylder, Wilfried Philips. Automatic Detection Of Fluorescent markers. Ibbt-Image Processing and Interpretation Pieters nieuw straat 419000 Ghent Belgium, 2003: 315-317
[38]章毓晋.基于内容的视觉信息检索.北京:科学出版社, 2003: 98-102
[39]阮秋琦.数字图像处理学.北京:电子工业出版社, 2001: 65-68
[40] Milan Sonka, Vaclav Hlavac, Roger Boyle. Image Processing, Analysis, and Machine Vision. Thomson Press, 2002: 423-430
[41] Fan J, David K Y Yau, Ahmed K Elmagarmid, Walid G Aref. Automatic Image Segmentation by Integrating Color-Edge Extraction and Seeded Region Growing. IEEE Transaction on Image Processing, 2001: 454-466
[42] Richard O Duda, Peter E Hart, David G. Stork Pattern classification. John& Sons press, 2000: 23-34
[2]罗兵,曾歆懿,季秀霞. SMT产品缺陷及相应的AOI检测方法.电子质量, 2006, 4(6): 35-37
[3] F Martn Rodrguez, M. Garca Saburido, J L Alba Castro. New methods for the automatic reading of vehicle license plates. Heraklion Creta Greece, 2002: 67-72
[4]陈传波,金先级.数字图像处理.北京:华中科技大学出版社, 2004: 267-271
[5]刘中合,王瑞雪,王锋德.数字图像处理技术现状与展望.计算机时代, 2005, 8(9): 6-8
[6]卡斯特曼.数字图像处理.北京:电子工业出版社, 2002: 126-130
[7] Yamaguchi A, Komuro O. Characterization of line edge roughness in resist patterns by Fourier analysis and auto-correlation function. Microprocesses and Nanotechnology Conference, Digest of Papers.Microprocesses and Nanotechnology, 2002(10): 80-81
[8]于殿泓.图像检测与处理技术.西安:西安电子科技大学出版社, 2006: 246-250
[9] Neal B Gallagher. Multivariate Image Analysis Past Present and Future-A Biased View. Eigenvector Research Inc, 2000: 42-46
[10] Jean-Marc Peallat and Mark J Norris. Aoi: Facing The Challenges Of 0201. Vi Technology, LLC Haverhill MA, 2002: 11-13
[11] Mark J Norris. Advances in Automatic Optical Inspection: Gray Scale Correlation vs Vectoral Imaging. IEEE Computer, 2000(8): 13-15
[12] Dahnoun N. Digital Signal Processing Implementation using the TMS320C6000DSP Platform. Prentice Hall, 2000: 50-53
[13] Michael J Smith, Keith Fairchild. Understanding the Costs Benefits and ROI of adding AXI Versus AOI to an ICT Line. IEEE Computer, 1998(2): 06-09
[14] Kenneth R Castleman. Digital Image Processing.北京:北京电子工业出版社, 1999: 31-34
[15]孙即祥.模式识别中的特征提取与计算机视觉不变量.北京:国防工业出版社, 2001: 248-250
[16] Jacky Baltes. Efficient Image Processing for Increased Resolution and Color Correctness of CMOS Image Sensors. Lecture Notes in Computer Science Volume 2377/2002 Robot Soccer World Cup, 2001: 92-93
[17]郭艳萍.检测自动化中的数字图像处理及识别: [硕士学位论文].河海:河海大学图书馆, 2002
[18] Zhang C. Optical Profilometry and its Applications. Ph D Thesis, State University of New York at Stony Brook, 2001: 28-32
[19] Egidijus Paliulis, Raimondas Zemblys, Gintautas daunys. Image analysis Problems in aoi systems. Issn 1392 C 124X Information Technologyand Control, 2008: 37-39
[20] F Mohanna. Performance evaluation of corner detectors using consistency and accuracy. Computer Vision and Image Understanding measures, 2006: 81-94
[21] Q. Gao, L Zhang, D Zhang, J Yang. Comments on On Image Matrix Based Feature Extraction Algo rithms. IEEE Transactions on Systems Man and Cybernetics, 2007: 06-11
[22] Dr Antonius,B Wijanarto. Image enhancement Fundamental Remote Sensing, 2002: 19-23
[23] John Wiley, Sons Ltd. Computer processing of remotely sensed images:an introduction 3rd. Mather, Paul M, 2004: 32-36
[24] Robinson. Measuring the ocean from space:the principles and methods of satellite oceanography .Ian S, 2004: 669-670
[25]陈从颜.结构光投影法在三维检测和物象重建系统中的应用.计算机应用与研究, 1999(7): 78-79
[26]罗兵,张云. SMT焊膏印刷质量自动光学检测.电子质量报, 2005(12): 30-32.
[27] B K P Horn. Shape from Shading. A Method for Obtaining the Shape of a Smooth Opaque Object from one View. PhD thesis,Department of Electrical Engineering, MIT, 1999: 3-9
[28]刘继胜,钟良.机器视觉技术在质量检测中的应用.现代制造工程, 2004(2): 99-101
[29] Akuta T, Ngistit Y. Development of an automatic 3-D shape measuring system using a new auto-focusing method. Measurement, 1991, 9(3): 98-103
[30] John A. Pearce. Biomedical Image Processing with Morphology-Based Nonlinear Filters . Rebecca Richards-Kortum, 2000: 45-46
[31] J Song and E J Delp. A study of the generalized morphological filter. Circuits Syst Signal Process, 1992: 110-113
[32] Sangwine SJ, Horne REN. The color Image Processing Handbook. M Chapman& Hall London, 1998: 76-83
[33] C.Vonesch, F.Aguet. The Colored revolution of bioimaging. IEEE signal processing magazine, 2006: 20-21
[34] R C Gonzales, R E Woods. Digital Image processing using Matlab. Pearson/Merrill/ Prentice Hall, 2004: 213-221
[35] E Meijering, I Smal, G Danuser. Tracking imolecular bio imaging. IEEE signal processing magazine, 2006(6): 9-15
[36] J De Bock, W Philips. Line segment based water shed segmentation. Third International Conference, 2007: 203-205
[37] Jonas De Vylder, Wilfried Philips. Automatic Detection Of Fluorescent markers. Ibbt-Image Processing and Interpretation Pieters nieuw straat 419000 Ghent Belgium, 2003: 315-317
[38]章毓晋.基于内容的视觉信息检索.北京:科学出版社, 2003: 98-102
[39]阮秋琦.数字图像处理学.北京:电子工业出版社, 2001: 65-68
[40] Milan Sonka, Vaclav Hlavac, Roger Boyle. Image Processing, Analysis, and Machine Vision. Thomson Press, 2002: 423-430
[41] Fan J, David K Y Yau, Ahmed K Elmagarmid, Walid G Aref. Automatic Image Segmentation by Integrating Color-Edge Extraction and Seeded Region Growing. IEEE Transaction on Image Processing, 2001: 454-466
[42] Richard O Duda, Peter E Hart, David G. Stork Pattern classification. John& Sons press, 2000: 23-34