Advances in light microscope stereo vision
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The increasing research focus on small-scale mechanical systems has generated a need for deformation and strain measurement systems for microscale applications. Optical measurement systems, such as digital image correlation, present an obvious choice due to their non-contacting nature. However, the transfer of measurement technology developed for macroscale applications to the microscale presents unique challenges due to the differences in the required highmagnification optics. In this paper we illustrate the problems involved in calibrating a stereo microscope using traditional techniques and present a novel methodology for acquiring accurate, three-dimensional surface shape and deformation data on small-scale specimens.
Experimental results demonstrate that stereo microscope systems can be accurately and reliably calibrated using a priori distortion estimation techniques in combination with traditional bundle-adjustment. The unique feature of the present methodology is that it does not require a precision calibration target but relies solely on point correspondences obtained by image correlation. A variety of experiments illustrate the measurement performance of a stereo microscope system. It is shown that the surface strains obtained from the full-field, three-dimensional measurements on tensile specimens undergoing large rigid-body motions are within ±50 microstrain of strain gage measurements for strains ranging from 0 to 2000 microstrain.
- Sutton, M.A., Wolters, W.J., Peters, W.H., Ranson, W.F., andMcNeill, S.R., “Determination of Displacements Using an Improved Digital Correlation Method,”Image Vision Comput.,21,133–139 (1983). CrossRef
- Khan-Jetter, Z.L. andChu, T.C., “Three-dimensional Displacement Measurements Using Digital Image Correlation and Photogrammic Analysis” EXPERIMENTAL MECHANICS,30 (1),10–16 (1990). CrossRef
- Luo, P.F., Chao, Y.J., Sutton, M.A., andPeters, W.H., “Accurate Measurement of Three-dimensional Deformable and Rigid Bodies Using Computer Vision,” EXPERIMENTAL MECHANICS,33 (2),123–132 (1993). CrossRef
- Luo, P.F., Chao, Y.I., andSutton, M.A., “Application of Stereo Vision to 3D Deformation analysis in Fracture Mechanics,”Opt. Eng.,33,981 (1994). CrossRef
- Helm, J.D., McNeill, S.R., andSutton, M.A., “Improved 3D Image Correlation for Surface Displacement Measurement,”Opt. Eng.,35 (7),1911–1920 (1996). CrossRef
- Orteu, J.-J., Garric, V., and Devy, M., “Camera Calibration for 3D Reconstruction: Application to the Measure of 3D Deformations on Sheet Metal Parts,” in European Symposium on Lasers, Optics and Vision in Manufacturing, Munich, Germany, June (1997).
- Synnergren, P. andSjödahl, M., “A Stereoscopic Digital Speckle Photography System for 3D Displacement Field Measurements,”Opt. Lasers Eng.,31,425–443 (1999). CrossRef
- Galanulis, K. and Hofimann, A., “Determination of Forming Limit Diagrams Using An Optical Measurement System,” in International Conference on Sheet Metal, Erlangen, Germany, September, 245–252 (1999).
- Sutton, M.A. McNeill, S.R., Helm, J.D., and Schreier, H.W., “Computer Vision Applied to Shape and Deformation Measurement”, in International Conference on Trends in Optical Non-Destructive Testing and Inspection, Lugano, Switzerland, 571–589 (2000).
- Hemmled, M. and Schubert, M., “Digital Microphotogrammetry—Determination of the Topography of Microstructures by Scanning Electron Microscope,” in Second Turkish-German Joint Geodetic Days, Berlin, Germany, May, 745–752 (1997).
- Lacey, A.J., Thacker, S., Crossley, S., andYates, R.B., “A Multi-Stage Approach to the Dense Estimation of Disparity from Stereo SEM Images,”Image Vision Comput.,16,373–383 (1998). CrossRef
- Pouchou, J.-L., “Prises de vues stéréographiques au MEB: difficultés pratiques, sources d'erreur,” in Colloque de la Société Française des Microscopies, Saclay, France, June (1999).
- Richards, R.G., Wieland, M., andTextor, M., “Advantages of Stereo Imaging of Imaging of Metallic Surfaces with Lois Voltage Backscattered Electrons in a Field Emission Scanning Electron Microscope,”J. Microscopy,199,115–123 (2000). CrossRef
- Vignon, F., Le Besnerais, G., Boivin, D., Pouchou, J.L., and Quan, L., “3D Reconstruction from Scanning Electron Miscroscopy Using Stereovision and Self-calibration,” in Physics in Signal and Image Processing, Marseille, France, January (2001).
- Sutton, M.A., Chae, T.L., Turner, J.L., and Bruck, H.A., “Development of a Computer Vision Methodology for the Analysis of Surface Deformations in Magnified Images,” in MiCon 90: Advances in Video Technology for Microstructural Control, ASTM STP 1094. Philadelphia, PA, 109–132 (1990).
- Mazza, E., Danuser, G., andDual, J., “Light Optical Measurements in Microbars with Nanometer Resolution,”Microsyst. Technol.,2,83–91 (1996). CrossRef
- Mitchell, H.L., Kniest, H.T., andWon-Jin, O., “Digital Photogrammetry and Microscope Photographs,”Photogrammetric Record,16 (94),695–704 (1999). CrossRef
- Faugeras, O., Three-dimensional Computer Vision: A Geometric Viewpoint, MIT Press, Cambridge, MA (1993).
- Beyer, H.A., “Accurate Calibration of CCD Cameras,” in Conference on Computer Vision and Pattern Recognition (1992).
- Weng, J., Cohen, P., andHerniou, M., “Camera Calibration with Distortion Models and Accuracy Evaluation,”IEEE Trans. Pattern Anal. Mach. Intell.,14 (10),965–980 (1992). CrossRef
- Faugeras, O. and Toscani, G., “Camera Calibration for 3D Computer Vision,” in International Workshop on Machine Vision and Machine Intelligence, Tokyo, Japan, February, 240–247 (1987).
- Devy, M., Garric, V., and Orteu, J.J., “Camera Calibration from Multiple Views of a 2D Object Using a Global Nonlinear Minimization Method,” in International Conference on Intelligent Robots and Systems, Grenoble, France, September (1997).
- Zhang, Z., “A Flexible New Technique for Camera Calibration,” Technical Report MSR-TR-98-71, Microsoft Research, December (1998). Updated March 1999.
- Garcia, D., Orteu, J.-J., and Devy, M., “Accurate Calibration of a Stereovision Sensor: Comparison of Different Approaches,” in Workshop on Vision, Modeling, and Visualization, Saarbrücken, Germany, November, 25–32 (2000).
- Triggs, B., McLauchlan, P., Hartley, R., and Fitzgibbon, A., “Bundle Adjustment—A Modern Synthesis,” in Vision Algorithms, Corfu, Greece (1999).
- Li, M., andLavest, J.-M., “Some Aspects of Zoom Lens Camera Calibration,”IEEE Trans. Pattern Anal. Mach. Intell.,18 (10),1105–1110 (1996).
- Ravn, O., Andersen, N.A., and Sorensen, A.T., “Auto-calibration in Automation Systems using Vision,“ in International Symposium on Experimental Robotics, Japan, 206–218 (1993).
- Peuchot, B., “Camera Virtual Equivalent Model −0.01 Pixel Detector,” in International Conference IEEE EMBS, Satellite Symposium on 3D Advanced Image Processing in Medicine, Rennes, France, November, 41–45 (1992).
- Brand, P., “Reconstruction Tridimensionnelle à partir d'une caméra en mouvement: de l'influence de la précision”,Ph.D. Thesis, Claude Bernard University, Lyon I, France, October (1995).
- Schreier, H.W., “Calibrated Sensor and Method for Calibrating Same,” Patent Pending, November (2002).
- Ayache, N. and Hansen, C., “Rectification of Images for Binocular and Trinocular Stereovision,” in International Conference on Pattern Recognition, Rome, Italy, 11–16 (1988).
- Correlates Solutions Inc. and Garcia, D., Vic2D and Vic3D softwares, http://www.correlatedsolutions.com (2002).
- Brown, D.C., “The Bundle Adjustment—Progress and Prospects,”Int Archives Photogrammetry,21 (3) (1976).
- Kraus, K., Photogrammetry, Vol. 1: Fundamentals and Standard Processes, Dümmler, Bonn (1997).
- Kraus, K., Photogrammetry, Vol. 2: Advanced Methods and Applications, Dümmler, Bonn (1997).
- Lavest, J.-M., Viala, M., and Dhome, M., “Do we Really Need An Accurate Calibration Pattern to Achieve a Reliable Camera Calibration?” in European Conference on Computer Vision, Freiburg, Germany, 158–174 (1998).
- Hartley, R.L. andSturm, P., “Triangulation,”Comput. Vision Image Understanding,68 (2),146–157 (1997). CrossRef
- Helm, J.D., McNeill, S.R., andSutton, M.A., “Deformations in Wide, Center-notched, Thin Panels, Part I: Three-dimensional Shape and Deformation Measurements by Computer Vision”,Opt. Eng.,42 (5),1293–1305 (2003). CrossRef
- Helm, J.D., McNeill, S.R., andSutton M.A., “Deformations in Wide, Center-notched, Thin Panels, Part II: Finite Element Analysis and Comparison to Measurements,”Opt. Eng.,42 (5),1306–1320 (2003). CrossRef
- Schreier, H.W. andSutton, M.A., “Effect of Higher-order Displacement Fields on Digital Image Correlation Displacement Component Estimates,” EXPERIMENTAL MECHANICS,42 (3),303–311 (2002).
- Sowerby, R., Duncan, J.L., andChu, E., “The Modelling of Sheet Metal Stamping,”Int. J. Mech. Sci.,28 (7),415–430 (1986). CrossRef
- Marciniak, Z. andDuncan, J.L., The Mechanics of Sheet Metal Forming, Edward Arnold.London (1992).
- Schreier, H., Braasch, J., andSutton, M.A., “Systematic Errors in Digital Image Correlation Caused by Intensity Interpolation,”Opt. Eng.,39 (11),2915–2921 (2000). CrossRef
- Garcia, D., “Mesure de formes et de champs de déplacements tridimensionnels par stéréo-corrélation d'images,” Ph.D. Thesis,Institut National Polytechnique de Toulouse, France, December (2001).
- Advances in light microscope stereo vision
Volume 44, Issue 3 , pp 278-288
- Cover Date
- Print ISSN
- Online ISSN
- Kluwer Academic Publishers
- Additional Links
- Stereo microscope
- stereo vision
- accurate stereo calibration procedure
- digital image correlation
- three-dimensional surface displacement measurement
- Industry Sectors