3D image based modelling for inspection of objects with micro-features, using inaccurate calibration patterns: an experimental contribution
In this report, the authors give a contribution to the study of the influence of inaccuracy of the shape and the position of calibration targets, on the accuracy of Photogrammetry in digitizing micro-features. In a machine vision, camera calibration is performed with planar patterns printed on common papers. When the pattern is small, inaccuracies are experienced. This limitation is overcome by using a coordinate measuring machine to measure the pattern and improve the calibration data. After the calibration improvement, the photogrammetric results are comparable with the existing and more expensive accurate techniques. The use of photogrammetry or computer vision for measuring objects with micro features is a promising research field, yet unexplored. When calibrating cameras for small fields of view is gained, the inaccuracies of the pattern affect the calibration accuracy. A few research papers are available about camera calibration with inaccurate patterns, but no industrial approaches are presented to solve the problem with consequent industrial applications. In the present report, these issues are overcome with a practical method applied to two case studies.
Keywords3D Inspection Micro Photogrammetry Camera calibration Inaccurate pattern Image based modelling
The first work-piece used as a case-study was kindly shared by Dr. Francesco Modica and Dr. Gianluca Trotta from the Institute for Industrial Technologies and Automation of the Italian National Research Council.
- 2.Minguez, R., Arias, A., Etxaniz, O., Solaberrieta, E., Barrenetxea, L.: Framework for verification of positional tolerances with a 3D non-contact measurement method. Int. J. Interact. Des. Manuf., pp. 1–9 (2014) doi: 10.1007/s12008-014-0214-7
- 6.Maté González, M.Á, Yravedra, J., González-Aguilera. D., Palomeque-González, JF., Domínguez-Rodrigo, M.: Micro-photogrammetric characterization of cut marks on bones. J Archaeol Sci 62,128–42 (2015). doi: 10.1016/j.jas.2015.08.006
- 7.Rodríguez-martín, M., Lagüela, S., González-aguilera, D., Rodríguez-gonzálvez, P.: Optics and laser technology procedure for quality inspection of welds based on macro-photogrammetric three-dimensional reconstruction 73, 54–62 (2015)Google Scholar
- 10.Galantucci, L.M., Pesce, M., Lavecchia, F.: A stereo photogrammetry scanning methodology, for precise and accurate 3D digitization of small parts with sub-millimeter sized features. CIRP Ann. Manuf. Technol. 64, 10–507 (2015). doi: 10.1016/j.cirp.2015.04.016
- 11.Albarelli, A., Rodolà, E., Torsello, A.: Robust camera calibration using inaccurate targets. Procedings Br. Mach. Vis. Conf. 2010, British Machine Vision Association, pp. 16.1–16.10 (2010). doi: 10.5244/C.24.16
- 13.Strobl, K.H., Hirzinger, G.: More accurate pinhole camera calibration with imperfect planar target. 2011 IEEE Int. Conf. Comput. Vis. Work. (ICCV Work). IEEE, pp. 75–1068 (2011). doi: 10.1109/ICCVW.2011.6130369
- 14.Brown, D.C.: Close-range camera calibration. Photogramm. Eng. 37, 66–855 (1971)Google Scholar
- 15.Ricolfe-Viala, C., Sanchez-Salmeron, A.: Lens distortion models evaluation. Appl. Opt. 49, 28–5914 (2010). doi: 10.1364/AO.49.005914
- 16.Bradski, G.: The OpenCV Library. Dr Dobb’s J Softw Tools (2000)Google Scholar