Comparative study of different digitization techniques and their accuracy

The various manufacturers of digitization systems speak of the effectiveness and accuracy of their tools under optimal conditions, but actual experimentation with simple or complex objects and different materials yields results that on occasions refute the effectiveness of those systems. In order to help choose a digitization system on the basis of its accuracy and the quality of the distribution of points and triangular meshes, in the field of reverse engineering, we compared five digitization techniques (three versions of the laser scanner, a fringe projection version and an X-ray version): (1) an ordered point cloud obtained with a laser incorporated in a CMM, (2) a disordered point cloud obtained with a manual laser the position of which is determined with a Krypton Camera, (3) an Exascan manual laser with targets, (4) an ordered point cloud obtained by high precision Computerized Tomography (CT) and (5) an Atos fringe projection scanner with targets. Each of the three calibrated pieces (a sphere, a cylinder and a gauge block) was measured five times by the five digitization systems to confirm the accuracy of the measurement. A comparison was also made of the meshes generated by the five software packages (Focus-Inspection, Metris, VxScan, Mimics and Atos) of the five digitization systems for the three calibrated pieces and two more complex pieces (a bone and an automobile window winder pulley) to determine meshing quality. Finally, all the pieces were meshed by triangulation in the Catia V5 DSE (Digitized Shape Editor) module in order to test the quality of the points distribution.

[1]  C. Bradley,et al.  Advances in the Field of Reverse Engineering , 2005 .

[2]  Thomas C. Henderson,et al.  Feature-based reverse engineering of mechanical parts , 1999, IEEE Trans. Robotics Autom..

[3]  Ralph R. Martin,et al.  Algorithms for reverse engineering boundary representation models , 2001, Comput. Aided Des..

[4]  Ralph R. Martin,et al.  Reverse engineering of geometric models - an introduction , 1997, Comput. Aided Des..

[5]  Weidong Zhu,et al.  Feature-based reverse modeling strategies , 2006, Comput. Aided Des..

[6]  Paolo Cignoni,et al.  A low cost 3D scanner based on structured light , 2001 .

[7]  Anshuman Razdan,et al.  Reverse Engineering Using a Subdivision Surface Scheme , 2003 .

[8]  J. J. Aguilar,et al.  Stereo vision for 3D measurement: accuracy analysis, calibration and industrial applications , 1996 .

[9]  Alan M. McIvor,et al.  Accurate 3D measurement using a structured light system , 1998, Image Vis. Comput..

[10]  Ioannis Fudos,et al.  On Reconstructing 3D Feature Boundaries , 2008 .

[11]  I.A. Aziz,et al.  3D CT Imaging for Craniofacial Analysis Based on Anatomical Regions , 2005, 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference.

[12]  Zainul Ahmad Rajion,et al.  3D CT Imaging for Craniofacial Analysis Based on Anatomical Regions. , 2005, Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference.

[13]  T. Suk,et al.  Data Reduction Methods for Reverse Engineering , 2001 .

[14]  Uncertainty of measurement — Part 3 : Guide to the expression of uncertainty in measurement ( GUM : 1995 ) Supplement 2 : Extension to any number of output quantities , 2011 .

[15]  M. Colbert,et al.  Applications of high-resolution X-ray computed tomography in petrology, meteoritics and palaeontology , 2003, Geological Society, London, Special Publications.

[16]  Les A. Piegl,et al.  Parametrization for surface fitting in reverse engineering , 2001, Comput. Aided Des..

[17]  Ye Jin,et al.  Accurate calibration for a camera-projector measurement system based on structured light projection , 2009 .

[18]  Jens T. Thielemann,et al.  A flexible 3D vision system based on structured light for in-line product inspection , 2008, Electronic Imaging.

[19]  V. H. Chan,et al.  Automating laser scanning of 3D surfaces for reverse engineering , 1997, Other Conferences.

[20]  Alexander Flisch,et al.  Point cloud reconstruction with sub-pixel accuracy by slice-adaptive thresholding of X-ray computed tomography images , 2004 .

[21]  R. Ketcham,et al.  Acquisition, optimization and interpretation of X-ray computed tomographic imagery: applications to the geosciences , 2001 .

[22]  Jorge Santolaria,et al.  A one-step intrinsic and extrinsic calibration method for laser line scanner operation in coordinate measuring machines , 2009 .

[23]  Azriel Rosenfeld,et al.  Review: B. Jähne, H. Haussecker, and P. Geissler, eds., Handbook of Computer Vision and Applications. 1. Sensors and Imaging. 2. Signal Processing and Pattern Recognition. 3. Systems and Applications , 2000, Artif. Intell..

[24]  Duc Truong Pham,et al.  Reverse engineering: An industrial perspective , 2008 .

[25]  Kiran Jude Fernandes,et al.  Reverse Engineering: An Industrial Perspective , 2007 .

[26]  S. Standard GUIDE TO THE EXPRESSION OF UNCERTAINTY IN MEASUREMENT , 2006 .

[27]  Seokbae Son,et al.  Automated laser scanning system for reverse engineering and inspection , 2002 .

[28]  Basilio Ramos Barbero The recovery of design intent in reverse engineering problems , 2009, Comput. Ind. Eng..

[29]  I. Fudos,et al.  On Reconstructing 3 D Feature Boundaries , 2008 .

[30]  Ralph R. Martin,et al.  Constrained fitting in reverse engineering , 2002, Comput. Aided Geom. Des..

[31]  Kwan H. Lee,et al.  Use of reverse engineering method for rapid product development , 1998 .

[32]  Alexander Flisch,et al.  Adaptive CT scanning—mesh based optimisation methods for industrial X-ray computed tomography applications , 2004 .

[33]  Anshuman Razdan,et al.  A hybrid approach to feature segmentation of triangle meshes , 2003, Comput. Aided Des..

[34]  Ross T. Whitaker,et al.  Partitioning 3D Surface Meshes Using Watershed Segmentation , 1999, IEEE Trans. Vis. Comput. Graph..

[35]  Holly E. Rushmeier,et al.  The 3D Model Acquisition Pipeline , 2002, Comput. Graph. Forum.

[36]  Gábor Renner,et al.  Advanced surface fitting techniques , 2002, Comput. Aided Geom. Des..

[37]  Lei Chen,et al.  Reverse innovative design - an integrated product design methodology , 2008, Comput. Aided Des..

[38]  Andreas Nüchter,et al.  Robust 3D-mapping with time-of-flight cameras , 2009, 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[39]  Vasiliki Stamati,et al.  A feature based approach to re-engineering objects of freeform design by exploiting point cloud morphology , 2007, Symposium on Solid and Physical Modeling.

[40]  S. Lippman,et al.  The Scripps Institution of Oceanography , 1959, Nature.

[41]  J.-Angelo Beraldin,et al.  Basic theory on surface measurement uncertainty of 3D imaging systems , 2009, Electronic Imaging.