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http://dx.doi.org/10.5302/J.ICROS.2013.13.9029

Shape Recognition of a BGA Ball using Ring Illumination  

Kim, Jong Hyeong (Department of Mechanical System Design Engineering, Seoul National University of Science and Technology)
Nguyen, Chanh D.Tr. (Division of Mechanical Engineering, KAIST)
Publication Information
Journal of Institute of Control, Robotics and Systems / v.19, no.11, 2013 , pp. 960-967 More about this Journal
Abstract
Shape recognition of solder ball bumps in a BGA (Ball Grid Array) is an important issue in flip chip bonding technology. In particular, the semiconductor industry has required faster and more accurate inspection of micron-size solder bumps in flip chip bonding as the density of balls has increased dramatically. The difficulty of this issue comes from specular reflection on the metal ball. Shape recognition of a metal ball is a very realproblem for computer vision systems. Specular reflection of the metal ball appears, disappears, or changes its image abruptly due to tiny movementson behalf of the viewer. This paper presents a practical shape recognition method for three dimensional (3-D) inspection of a BGA using a 5-step ring illumination device. When the ring light illuminates the balls, distinctive specularity images of the balls, which are referred to as "iso-slope contours" in this paper, are shown. By using a mathematical reflectance model, we can drive the 3-D shape information of the ball in aquantitative manner. The experimental results show the usefulness of the method for industrial application in terms of time and accuracy.
Keywords
specular reflection; ring illumination; iso-slope contour; hybrid reflectance model;
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1 K. W. Ko, H. S. Cho, J. H. Kim, and S.-K. Kim, "Solder joint inspection using a neural network and fuzzy rule-based classification method," Journal of control robotics and Systems, vol. 8, no. 6, pp. 710-718, 2000.
2 David McCann 2012, Advanced Packaging and Progress in 3D Integration, The ConFab 2012 Conference.
3 J. H. Kim, H. S. Cho, and S. Kim, "Pattern classification of solder joint images using a correlation neural network," Engineering Applications of Artificial Intelligence, vol. 9, no. 6, pp. 655-669, 1996.   DOI   ScienceOn
4 J. H. Kim and H. S. Cho, "Neural network-based inspection of solder joints using a circular illumination," Image and Vision Computing, vol. 13, pp. 479-490, 1995.   DOI   ScienceOn
5 E. N Colenman and R. Jain, "Obtaining 3-dimensional shape of textured ans specular surface using four-source photometry," Computer Vision, Graph, Image Process, vol. 18, no. 4, pp. 309- 328, 1982.   DOI
6 H. Saito, K. Omata, and S. Ozawa, "Recovery of shape and surface reflectance of specular object from relative rotation of light source," Image and Vision Computing, vol. 21, no. 9, pp. 777-787, 2003.   DOI   ScienceOn
7 C. Linder and F. Leon, "Model-based segmentation of surfaces using illumination series," IEEE Transactions on Instrumentation and Measurement, vol. 56, no. 4, pp. 1340-1346, 2007.   DOI   ScienceOn
8 P. Kim and S. Rhee, "Three-dimensional inspection of ball grid array using laser vision system," IEEE Transactions on Electronics Packaging Manufacturing, vol. 22, pp. 151-155, 1999.   DOI   ScienceOn
9 J. H. Kim, C. H. Kim, and H. S. Cho, "Obtaining shape of specular object using ring illumination," Journal of the Korean Society of Precision Engineering, vol. 2, pp. 78-87, 1995.
10 I. D. Yun, E. Jung, and S. U. Lee, "On the fast shape recovery technique using multiple ring lights," Pattern Recognition, vol. 30, pp. 883-893, 1997.   DOI   ScienceOn
11 D. J. Svetkoff, D. K. Rohner, D. A. Nohleti, and R. L. Jackson, "Method and system for triangulation-based, 3D imaging utilizing an angled scanning beam of radiant energy," U.S. Patent 5, pp. 617-209, 1997.
12 M. Yu, G.-Y. Jiang, S.-L. He, B.-K. Yu, and R.-D. Fu, "New approach to vision-based BGA package inspection," Proc. of the First International Conference on Machine Learning and Cybernetics, vol. 2, pp. 1107-1110, 2002.
13 S. K. Nayar, K. Ikeuchi, and T. Kanade, "Surface reflection: Physical and geometrical perspective," IEEE Trans. Pattern Analysic Mach. Intell., vol. 13, pp. 611-634, 1991.   DOI   ScienceOn
14 S. K. Nayar, K. Ikeuchi, and T. Kanade, "Determining shape and reflectance of hybrid surface by photometric sampling," IEEE Trans. On Robotics and Automation, vol. 6, pp. 418-431, 1990.   DOI   ScienceOn
15 R. Klette and K. Schluns, "Height data from gradient fields," Proc. of SPIE (the International Society for Optical Engineering) on Machine Vision Applications, Architectures, and Systems Integration, Boston, Massachusetts, USA. vol. 133, pp. 204-215, 1996.
16 J. H. Kim, J. H. Kim, S. M. Cho, H. H. Shim, M. G. Ji, S. Shin, S. H. Han, and C. D. Tr. Nguyen, "Study of 2D + 3D Visual Inspection for Tiny Object," Project Report: The Collaborative Research Program Among Industry, Academic and Research Institutes, 2012.
17 S. K. Nayer, A. C. Sanderson, L. E. Weiss, and D. D. Simmon, "Specular surface inspection using structured highlight and Gaussian image," IEEE Trans, on Robotics and Automation, vol. 6, no. 2, pp. 208-218, 1990.   DOI   ScienceOn