Comparison of surface extraction techniques performance in computed tomography for 3D complex micro-geometry dimensional measurements

  • Marta Torralba
  • Roberto Jiménez
  • José A. Yagüe-Fabra
  • Sinué Ontiveros
  • Guido Tosello


The number of industrial applications of computed tomography (CT) for dimensional metrology in 100–103 mm range has been continuously increasing, especially in the last years. Due to its specific characteristics, CT has the potential to be employed as a viable solution for measuring 3D complex micro-geometries as well (i.e., in the sub-mm dimensional range). However, there are different factors that may influence the CT process performance, being one of them the surface extraction technique used. In this paper, two different extraction techniques are applied to measure a complex miniaturized dental file by CT in order to analyze its contribution to the final measurement uncertainty in complex geometries at the mm to sub-mm scales. The first method is based on a similarity analysis: the threshold determination; while the second one is based on a gradient or discontinuity analysis: the 3D Canny algorithm. This algorithm has proven to provide accurate results in parts with simple geometries, but its suitability for 3D complex geometries has not been proven so far. To verify the measurement results and compare both techniques, reference measurements are performed on an optical coordinate measuring machine (OCMM). The systematic errors and uncertainty results obtained show that the 3D Canny adapted method slightly lower systematic deviations and a more robust edge definition than the local threshold method for 3D complex micro-geometry dimensional measurements.


3D complex geometry Computed tomography Surface extraction Canny algorithm 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


Funding information

The authors acknowledge the support of the Research Foundation MINECO (Spain) via project DPI2015-69403-C3-1-R and the University of Zaragoza and Centro Universitario de la Defensa (Spain) via project UZCUD2016-TEC-09. The present research was carried out within a joint research program between the Department of Mechanical Engineering at DTU (Technical University of Denmark) and the Department of Design and Manufacturing Engineering at the University of Zaragoza (Spain). Collaboration from the Laboratory of Geometrical Metrology of DTU Mechanical Engineering is acknowledged in connection with the optical coordinate measurements.


  1. 1.
    Tosello G, Hansen HN, Gasparin S (2009) Applications of dimensional micro metrology to the product and process quality control in manufacturing of precision polymer micro components. CIRP Ann Manuf Technol 58:467–472CrossRefGoogle Scholar
  2. 2.
    Bos EJC (2011) Aspects of tactile probing on the micro scale. Precis Eng 35:228–240CrossRefGoogle Scholar
  3. 3.
    Petz M, Tutsch R, Christoph R, Andraes M, Hopp B (2012) Tactile–optical probes for three-dimensional microparts. Measurement 45:2288–2298CrossRefGoogle Scholar
  4. 4.
    Claverley JD, Leach RK (2015) A review of the existing performance verification infrastructure for micro-CMMs. Precis Eng 39:1–15CrossRefGoogle Scholar
  5. 5.
    Mathia TG, Pawlus P, Wieczorowski M (2011) Recent trends in surface metrology. Wear 271:494–508CrossRefGoogle Scholar
  6. 6.
    Bešić I, Van Gestel N, Kruth J-P, Bleys P, Hodolič J (2011) Accuracy improvement of laser line scanning for feature measurements on CMM. Opt Lasers Eng 49:1274–1280CrossRefGoogle Scholar
  7. 7.
    De Chiffre L, Carmignato S, Kruth J-P, Schmitt R, Weckenmann A (2014) Industrial applications of computed tomography. CIRP Ann Manuf Technol 63:655–677CrossRefGoogle Scholar
  8. 8.
    Yu J, Lynn R, Tucker T, Saldana C, Kurfess T (2017) Model-free subtractive manufacturing from computed tomography data. Manuf Lett 13:44–47CrossRefGoogle Scholar
  9. 9.
    Hermanek P, Carmignato S (2017) Porosity measurements by X-ray computed tomography: accuracy evaluation using a calibrated object. Precis Eng 49:377–387CrossRefGoogle Scholar
  10. 10.
    Villarraga-Gómez H, Lee C, Smith ST (2018) Dimensional metrology with X-ray CT: a comparison with CMM measurements on internal features and compliant structures. Precis Eng 51:291–307CrossRefGoogle Scholar
  11. 11.
    Heinzl C, Kastner J, Gröller E (2007) Surface extraction from multi-material components for metrology using dual energy CT. IEEE Trans Vis Comput Graph 13:1520–1527CrossRefGoogle Scholar
  12. 12.
    Krämer P, Weckenmann A (2010) Multi-energy image stack fusion in computed tomography. Meas Sci Technol 21:45105CrossRefGoogle Scholar
  13. 13.
    Borges de Oliveira F, Stolfi A, Bartscher M, De Chiffre L, Neuschaefer-Rube U (2016) Experimental investigation of surface determination process on multi-material components for dimensional computed tomography. Case Stud Nondestruct Test Eval 6:93–103CrossRefGoogle Scholar
  14. 14.
    Kiekens K, Welkenhuyzen F, Tan Y, Bleys P, Voet A, Kruth J-P, Dewulf W (2011) A test object with parallel grooves for calibration and accuracy assessment of industrial computed tomography (CT) metrology. Meas Sci Technol 22:115502CrossRefGoogle Scholar
  15. 15.
    Xue L, Suzuki H, Ohtake Y, Fujimoto H, Abe M, Sato O, Takatsuji T (2015) A method for improving measurement accuracy of cylinders in dimensional CT metrology. Comput Des 69:25–34Google Scholar
  16. 16.
    Stolfi A, De Chiffre L (2016) 3D artefact for concurrent scale calibration in Computed Tomography. CIRP Ann Manuf Technol 65:499–502CrossRefGoogle Scholar
  17. 17.
    Andreu V, Georgi B, Lettenbauer H, Yague JA (2009) Analysis of the error sources of a computer tomography machine. In Proc. Lamdamap conference, pp 462–471Google Scholar
  18. 18.
    Kruth JP, Bartscher M, Carmignato S, Schmitt R, De Chiffre L, Weckenmann A (2011) Computed tomography for dimensional metrology. CIRP Ann Manuf Technol 60:821–842CrossRefGoogle Scholar
  19. 19.
    Hiller J, Reindl LM (2012) A computer simulation platform for the estimation of measurement uncertainties in dimensional X-ray computed tomography. Meas J Int Meas Confed 45:2166–2182CrossRefGoogle Scholar
  20. 20.
    Weckenmann A, Krämer P (2009) Assessment of measurement uncertainty caused in the preparation of measurements using computed tomography. Proc. IMEKO XIX World Congress, pp. 1888–1892Google Scholar
  21. 21.
    Ferrucci M, Ametova E, Carmignato S, Dewulf W (2016) Evaluating the effects of detector angular misalignments on simulated computed tomography data. Precis Eng 45:230–241CrossRefGoogle Scholar
  22. 22.
    Ferrucci M, Leach RK, Giusca C, Carmignato S, Dewulf W (2015) Towards geometrical calibration of x-ray computed tomography systems—a review. Meas Sci Technol 26:92003CrossRefGoogle Scholar
  23. 23.
    Müller P, Cantatore A, Andreasen JL, Hiller J, De Chiffre L (2013) Computed tomography as a tool for tolerance verification of industrial parts. Procedia CIRP 10:125–132CrossRefGoogle Scholar
  24. 24.
    Müller P, Hiller J, Cantatore A, De Chiffre L (2012) A study on evaluation strategies in dimensional X-ray computed tomography by estimation of measurement uncertainties. Int J Metrol Qual Eng 3:107–115CrossRefGoogle Scholar
  25. 25.
    Stolfi A, Thompson MK, Carli L, De Chiffre L (2016) Quantifying the contribution of post-processing in computed tomography measurement uncertainty. Procedia CIRP 43:297–302CrossRefGoogle Scholar
  26. 26.
    Hiller J, Hornberger P (2016) Measurement accuracy in X-ray computed tomography metrology: toward a systematic analysis of interference effects in tomographic imaging. Precis Eng 45:18–32CrossRefGoogle Scholar
  27. 27.
    Kraemer A, Lanza G (2016) Assessment of the measurement procedure for dimensional metrology with X-ray computed tomography. Procedia CIRP 43:362–367CrossRefGoogle Scholar
  28. 28.
    Ontiveros S, Yagüe-Fabra JA, Jiménez R, Tosello G, Gasparin S, Pierobon A, Carmignato S, Hansen HN (2012) Dimensional measurement of micro-moulded parts by computed tomography. Meas Sci Technol 23:125401CrossRefGoogle Scholar
  29. 29.
    Jiménez R, Ontiveros S, Carmignato S, Yagüe-Fabra JA (2013) Fundamental correction strategies for accuracy improvement of dimensional measurements obtained from a conventional micro-CT cone beam machine. CIRP J Manuf Sci Technol 6:143–148CrossRefGoogle Scholar
  30. 30.
    Yagüe-Fabra JA, Ontiveros S, Jiménez R, Chitchian S, Tosello G, Carmignato S (2013) A 3D edge detection technique for surface extraction in computed tomography for dimensional metrology applications. CIRP Ann Manuf Technol 62:531–534CrossRefGoogle Scholar
  31. 31.
    Ontiveros S, Yagüe JA, Jiménez R, Brosed F (2013) Computed tomography 3D edge detection comparative for metrology applications. Procedia Eng 63:710–719CrossRefGoogle Scholar
  32. 32.
    Ruddle CJ (2001) The ProTaper endodontic system: geometries, features, and guidelines for use. Dent Today 20:60–67Google Scholar
  33. 33.
    Ruddle CJ (2005) The ProTaper technique. Endod Top 10:187–190CrossRefGoogle Scholar
  34. 34.
    ISO 3630-1 2008 Dentistry. Root-canal instruments. Part 1: General requirements and test methods 2008Google Scholar
  35. 35.
    Kiekens K, Welkenhuyzen F, Tan Y, Bleys P, Voet A, Kruth J-P (2010) A test object for calibration and accuracy assessment in X-ray CT metrology. Proc. IMEKO 10th Int. Symp. Meas. Qual. Control, B6_86_1–4Google Scholar
  36. 36.
    ISO 14253-2 2011 Geometrical product specifications (GPS). Inspection by measurement of workpieces and measuring equipment. Part 2: Guidance for the estimation of uncertainty in GPS measurement, in calibration of measuring equipment and in product verifi 2011Google Scholar
  37. 37.
    Guide to the Expression of Uncertainty in Measurement (GUM) 2008Google Scholar
  38. 38.
    VDI/VDE 2630 Part 1.3 (2011) Guideline for the application of DIN EN ISO 10360 for coordinate measuring machines with CT-sensorsGoogle Scholar
  39. 39.
    VDI/VDE 2630 Part 2.1 (2015) Determination of the uncertainty of measurement and the test process suitability of coordinate measurement systems with CT sensorsGoogle Scholar
  40. 40.
    ISO/IEC 17043 (2010) Conformity assessment. General requirements for proficiency testingGoogle Scholar
  41. 41.
    ISO 286-2 2010 Geometrical product specifications (GPS). ISO code system for tolerances on linear sizes. Part 2: Tables of standard tolerance classes and limit deviations for holes and shaftsGoogle Scholar

Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2018

Authors and Affiliations

  • Marta Torralba
    • 1
  • Roberto Jiménez
    • 1
  • José A. Yagüe-Fabra
    • 2
  • Sinué Ontiveros
    • 3
  • Guido Tosello
    • 4
  1. 1.Centro Universitario de la DefensaA.G.MZaragozaSpain
  2. 2.I3AUniversidad de ZaragozaZaragozaSpain
  3. 3.Department of Industrial EngineeringAutonomous University of Baja CaliforniaSan FernandoMexico
  4. 4.Department of Mechanical EngineeringTechnical University of DenmarkKgs. LyngbyDenmark

Personalised recommendations