Experimental investigation on camera calibration for 3D photogrammetric scanning of micro-features for micrometric resolution

[EN] Recently, it has been demonstrated that photogrammetry can be used for the measurement of small objects with micro-features, with good results and lower cost, compared to other established techniques such as interferometry, conoscopic holography, and 3D microscopy. Calibration is a critical step in photogrammetry and the classical pinhole camera model has been tested for magnifications lower than 2×. At higher magnification levels, because of the reduction of the depth of field (DOF), images can lead to calibration data with low reprojection errors. However, this could lead to bad results in the 3D reconstruction. With the aim of verifying the possibility of applying the camera model to magnifications higher than 2×, experiments have been conducted using reflex cameras with 60 mm macro lens, equipped with the combination of three extension tubes, corresponding to 2.06, 2.23, and 2.4 magnification levels, respectively. Experiments consisted of repeating calibration five times for each configuration and testing each calibration model, measuring two artifacts with different geometrical complexity. The calibration results have shown good repeatability of a subset of the internal calibration parameters. Despite the differences in the calibration reprojection error (RE), the quality of the photogrammetric 3D models retrieved was stable and satisfying. The experiment demonstrated the possibilities of the photogrammetric system presented, equipped to very high magnification levels, to retrieve accurate 3D reconstruction of micro-features with uncertainties of few micrometers, comparable with industry s expensive state-of-the-art technologies.Percoco, G.; Guerra, MG.; Sánchez Salmerón, AJ.; Galantucci, LM. (2017). Experimental investigation on camera calibration for 3D photogrammetric scanning of micro-features for micrometric resolution. The International Journal of Advanced Manufacturing Technology. 91(9-12):2935-2947. https://doi.org/10.1007/s00170-016-9949-6S29352947919-12Uhlmann E, Mullany B, Biermann D, Rajurkar KP, Hausotte T, Brinksmeier E (2016) Process chains for high-precision components with micro-scale features. CIRP Ann - Manuf Technol 65:549–572. doi: 10.1016/j.cirp.2016.05.001Savio E, De Chiffre L, Schmitt R (2007) Metrology of freeform shaped parts. CIRP Ann - Manuf Technol 56:810–835. doi: 10.1016/j.cirp.2007.10.008Rodríguez-martín M, Lagüela S, González-aguilera D, Rodríguez-gonzálvez P (2015) Optics & Laser Technology Procedure for quality inspection of welds based on macro-photogrammetric three-dimensional reconstruction;73:54–62Xu Z, Toncich D, Stefani S (1999) Vision-based measurement of three-dimensional geometric workpiece properties. Int J Adv Manuf Technol 15:322–331. doi: 10.1007/s001700050074Galantucci LM, Lavecchia F, Percoco G (2013) Multistack close range photogrammetry for low cost submillimeter metrology. J Comput Inf Sci Eng 13:44501. doi: 10.1115/1.4024973Maté González, M.T., Yravedra, J., González-Aguilera, D., Palomeque-González, J.F., Domínguez-Rodrigo, M. Micro-photogrammetric characterization of cut marks on bones (2015) Journal of Archaeological Science, 62, pp. 128-142. doi: 10.1016/j.jas.2015.08.006Brown DC (1971) Close-range camera calibration. Photogramm Eng 37:855–866 doi:10.1.1.14.6358Tang R, Fritsch D (2013) Correlation analysis of camera self-calibration in close range photogrammetry. Photogramm Rec 28:86–95. doi: 10.1111/phor.12009Agisoft LLC (2011) Agisoft PhotoScan User Manual :37.Jcgm JCFGIM (2008) Evaluation of measurement data—guide to the expression of uncertainty in measurement- annex B "general metrological terms"- B.2.14. Int Organ Stand Geneva ISBN 50:134. doi: 10.1373/clinchem.2003.030528Yanagi, H., Chikatsu, H. Performance evaluation of macro lens in digital close range photogrammetry (2009) Proceedings of SPIE - The International Society for Optical Engineering, 7447, art. no. 74470J, doi: 10.1117/12.825817Galantucci LM, Pesce M, Lavecchia F (2015) A stereo photogrammetry scanning methodology, for precise and accurate 3D digitization of small parts with sub-millimeter sized features. CIRP Ann - Manuf Technol 64:507–510. doi: 10.1016/j.cirp.2015.04.016Galantucci LM, Pesce M, Lavecchia F (2015) A powerful scanning methodology for 3D measurements of small parts with complex surfaces and sub millimeter-sized features, based on close range photogrammetry. Precis Eng. doi: 10.1016/j.precisioneng.2015.07.010Percoco G, Sánchez Salmerón AJ (2015) Photogrammetric measurement of 3D freeform millimetre-sized objects with micro features: an experimental validation of the close-range camera calibration model for narrow angles of view. Meas Sci Technol 26:95203. doi: 10.1088/0957-0233/26/9/095203Gallo A, Muzzupappa M, Bruno F (2014) 3D reconstruction of small sized objects from a sequence of multi-focused images. J Cult Herit 15:173–182. doi: 10.1016/j.culher.2013.04.009Stamatopoulos C, Fraser CS, Cronk S (2010) On the self-calibration of long focal length lenses. Int Arch Photogramm Remote Sens Spat Inf Sci Newcastle upon Tyne, UK 2010 XXXVIII:560–564Atkinson KB (1996) Close range photogrammetry and machine vision. Whittles PublishingLuhmann T, Fraser C, Maas HG (2016) Sensor modelling and camera calibration for close-range photogrammetry. ISPRS J Photogramm Remote Sens 115:37–46. doi: 10.1016/j.isprsjprs.2015.10.006Tsai RY (1986) An efficient and accurate camera calibration technique for 3D machine vision. Proc IEEE Conf Comput Vis Pattern Recognition 1986Ricolfe-Viala C, Sanchez-Salmeron A-J (2011) Camera calibration under optimal conditions. Opt Express 19:10769–10775. doi: 10.1364/OE.19.010769Wang L, Wang W, Shen C, Duan F (2016) A convex relaxation optimization algorithm for multi-camera calibration with 1D objects. NeurocomputingRicolfe-Viala C, Sanchez-Salmeron A. Lens distortion models evaluation. Appl Opt 2010;49:5914–5928.Percoco G, Lavecchia F, Salmerón AJS (2015) Preliminary study on the 3D digitization of millimeter scale products by means of photogrammetry. Procedia CIRP 33:257–262. doi: 10.1016/j.procir.2015.06.046Bradski G (2000) The OpenCV Library. Dr Dobb’s J Softw ToolsRicolfe-Viala C, Sanchez-Salmeron A-J (2011) Optimal conditions for camera calibration using a planar template. 2011 18th IEEE. Int Conf Image Process, IEEE 2011:853–856. doi: 10.1109/ICIP.2011.6116691Lowe DG (1999) Object recognition from local scale-invariant features. Proc Seventh IEEE Int Conf Comput Vis 2:1150–1157. doi: 10.1109/ICCV.1999.790410Triggs B, Mclauchlan P, Hartley R, Fitzgibbon A, Triggs B, Mclauchlan P, et al. (2010) Bundle adjustment—a modern synthesis to cite this version: bundle adjustment—a modern synthesisCignoni P, Callieri M, Corsini M, Dellepiane M, Ganovelli F, Ranzuglia G (2008) Meshlab: an open-source mesh processing tool. Eurographics Ital Chapter Conf 2008:129–136Besl P, McKay N (1992) A method for registration of 3-D shapes. IEEE Trans Pattern Anal Mach Intell 14:239–256. doi: 10.1109/34.12179

Computer Numerical Controlled Grinding and Physical Vapor Deposition for Fused Deposition Modelled Workpieces

he use of additive manufacturing (AM) enables companies to directly produce complex end-use parts. Fused deposition modelling (FDM) is an AM technology based on an extrusion process of fabricating parts. This layer-by-layer method results in a poor surface finish, and as a result, manual finishing is often required, which consequentially reduces the definition of the geometrical features. This research proposes a novel way of achieving high surface finishing by using additive and finishing processes, followed by a physical vapor deposition (PVD) coating. Two test pieces were produced, the first one was subjected to computer numerical controlled (CNC) mechanical grinding with appropriate grades of grindstones; the second one was subjected to microsandblasting to remove excess material and the stair-stepping effect. Both test pieces were then subjected to a PVD coating process to provide a metal thin film. To benchmark the test pieces, the authors used a coordinate measure machine for dimensions and a roughness meter to verify the effectiveness of this postprocessing approach

Robber's Personal Identification by Morphometric Comparison Between Recorded Images and 3D Avatar of the Suspect

Personal identification based on 3D digital photogrammetry presents a natural evolution of a previous research in this field by "parameterized superimposition" (PS). The authors' experience was based on 2D/2D comparison between video frames taken from the surveillance camera system during the robbery and frames of the suspect brought back in the same place where the robbery was perpetrated. This technique involves four steps: The PREPARATORY PHASE, in which the recorded images of the robber are studied and improved. Frames with better view of robber's face landmarks are then chosen. The 3D ACQUISITION PHASE, during which a 3D photogrammetric avatar of the suspect face is created; this phase only requires 4 photos made simultaneously with a calibrated camera. The SUPERIMPOSITION PHASE is preparatory for the final step and involves a meticulous spatial orientation of the 3D avatar in the same position taken by the offender in the selected frames. A snapshot of the 3D avatar is now taken. During the METRIC IMAGE ANALYSIS a quantitative comparison between the image of the robber's face and the snapshot obtained is used. To perform this step it is necessary to clearly recognize at least five landmarks on the robber's face using a suitable software

Three-dimensional methodology for photogrammetric acquisition of the soft tissues of the face: a new clinical-instrumental protocol.

BACKGROUND: The objective of this study is to define an acquisition protocol that is clear, precise, repeatable, simple, fast and that is useful for analysis of the anthropometric characteristics of the soft tissue of the face. METHODS: The analysis was carried out according to a new clinical-instrumental protocol that comprises four distinct phases: (1) setup of portable equipment in the space in which field analysis will be performed, (2) preparation of the subject and spatial positioning, (3) scanning of the subject with different facial expressions, and (4) treatment and processing of data. The protocol was tested on a sample comprising 66 female subjects (64 Caucasian, 1 Ethiopian, and 1 Brazilian) who were the finalists of an Italian national beauty contest in 2010. To illustrate the potential of the method, we report here the measurements and full analysis that were carried out on the facial model of one of the subjects who was scanned. RESULTS: This new protocol for the acquisition of faces is shown to be fast (phase 1, about 1 h; phase 2, about 1.5 min; phase 3, about 1.5 min; phase 4, about 15 min), simple (phases 1 to 3 requiring a short operator training period; only phase 4 requires expert operators), repeatable (with direct palpation of anatomical landmarks and marking of their positions on the face, the problem of identification of these same landmarks on the digital model is solved), reliable and precise (average precision of measurements, 0.5 to 0.6 mm over the entire surface of the face). CONCLUSIONS: This standardization allows the mapping of the subjects to be carried out following the same conditions in a reliable and fast process for all of the subjects scanned