Skip to main content
Springer Nature Link
Log in

Entropy Based Surface Quality Assessment of 3D Prints

  • Conference paper
  • First Online:
Artificial Intelligence Trends in Intelligent Systems (CSOC 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 573))

Included in the following conference series:

  • 1256 Accesses

Abstract

In the paper the automatic method of visual quality assessment of surfaces of 3D prints is presented. The proposed approach is based on the use of entropy and may be applied for on-line inspection of 3D printing progress during the printing process. In case of observed decrease of the printed surface quality the emergency stop may be used allowing saving the filament, as well as possible correction of the printed object. The verification of the validity of the proposed method has been made using several prints made from different colors of the PLA filaments. Since the entropy of the image is related to the presence of structural information, the color to grayscale conversion of the test images has been applied in order to simplify further calculations. The analysis of the impact of the chosen color to grayscale conversion method on the obtained results is presented as well.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Battisti, F., Bosc, E., Carli, M., Callet, P.L., Perugia, S.: Objective image quality assessment of 3D synthesized views. Sig. Process. Image Commun. 30, 78–88 (2015)

    Article  Google Scholar 

  2. Benoit, A., Le Callet, P., Campisi, P., Cousseau, R.: Quality assessment of stereoscopic images. EURASIP J. Image Video Process. 2008(1), 659024 (2008)

    Google Scholar 

  3. Chauhan, V., Surgenor, B.: A comparative study of machine vision based methods for fault detection in an automated assembly machine. Procedia Manufact. 1, 416–428 (2015)

    Article  Google Scholar 

  4. Chen, M.J., Cormack, L.K., Bovik, A.C.: No-reference quality assessment of natural stereopairs. IEEE Trans. Image Process. 22(9), 3379–3391 (2013)

    Article  MathSciNet  Google Scholar 

  5. Chen, M.J., Su, C.C., Kwon, D.K., Cormack, L.K., Bovik, A.C.: Full-reference quality assessment of stereopairs accounting for rivalry. Sig. Process. Image Commun. 28(9), 1143–1155 (2013)

    Article  Google Scholar 

  6. Cheng, Y., Jafari, M.A.: Vision-based online process control in manufacturing applications. IEEE Trans. Autom. Sci. Eng. 5(1), 140–153 (2008)

    Article  Google Scholar 

  7. Fang, T., Jafari, M.A., Bakhadyrov, I., Safari, A., Danforth, S., Langrana, N.: Online defect detection in layered manufacturing using process signature. In: Proceedings of IEEE International Conference on Systems, Man and Cybernetics, vol. 5, pp. 4373–4378, San Diego, California, USA (1998)

    Google Scholar 

  8. Fastowicz, J., Okarma, K.: Texture based quality assessment of 3D prints for different lighting conditions. In: Chmielewski, L.J., Datta, A., Kozera, R., Wojciechowski, K. (eds.) ICCVG 2016. LNCS, vol. 9972, pp. 17–28. Springer, Cham (2016). doi:10.1007/978-3-319-46418-3_2

    Chapter  Google Scholar 

  9. Goldmann, L., Simone, F.D., Ebrahimi, T.: A comprehensive database and subjective evaluation methodology for quality of experience in stereoscopic video. In: 3D Image Processing (3DIP) and Applications, vol. 7526 in Proceedings of SPIE (2010)

    Google Scholar 

  10. Guo, J., Vidal, V., Cheng, I., Basu, A., Baskurt, A., Lavoue, G.: Subjective and objective visual quality assessment of textured 3D meshes. ACM Trans. Appl. Percept. 14(2), 11:1–11:20 (2016)

    Article  Google Scholar 

  11. International Telecommunication Union: Recommendation ITU-R BT.601-7 - Studio encoding parameters of digital television for standard 4:3 and wide-screen 16:9 aspect ratios (2011)

    Google Scholar 

  12. International Telecommunication Union: Recommendation ITU-R BT.709-6 - Parameter values for the HDTV standards for production and international programme exchange (2015)

    Google Scholar 

  13. Lin, Y., Wu, J.: Quality assessment of stereoscopic 3D image compression by binocular integration behaviors. IEEE Trans. Image Process. 23(4), 1527–1542 (2014)

    Article  MathSciNet  Google Scholar 

  14. Okarma, K., Fastowicz, J.: No-reference quality assessment of 3D prints based on the GLCM analysis. In: 2016 21st International Conference on Methods and Models in Automation and Robotics (MMAR), pp. 788–793 (2016)

    Google Scholar 

  15. Okarma, K.: On the usefulness of combined metrics for 3D image quality assessment. In: Choraś, R.S. (ed.) Image Processing and Communications Challenges 6. AISC, vol. 313, pp. 137–144. Springer, Heidelberg (2015). doi:10.1007/978-3-319-10662-5_17

    Google Scholar 

  16. Okarma, K., Fastowicz, J.: Quality assessment of 3D prints based on feature similarity metrics. In: Choraś, R.S. (ed.) Image Processing and Communications Challenges 8, pp. 104–111. Springer, Heidelberg (2017). doi:10.1007/978-3-319-47274-4_12

    Chapter  Google Scholar 

  17. Okarma, K., Fastowicz, J., Tecław, M.: Application of structural similarity based metrics for quality assessment of 3D prints. In: Chmielewski, L.J., Datta, A., Kozera, R., Wojciechowski, K. (eds.) ICCVG 2016. LNCS, vol. 9972, pp. 244–252. Springer, Cham (2016). doi:10.1007/978-3-319-46418-3_22

    Chapter  Google Scholar 

  18. Starch, J., Kilner, J., Hilton, A.: Objective quality assessment in free-viewpoint video production. In: Proceedings of the 3DTV Conference: The True Vision - Capture. Transmission and Display of 3D Video, pp. 225–228, Istanbul, Turkey (2008)

    Google Scholar 

  19. Straub, J.: Initial work on the characterization of additive manufacturing (3D printing) using software image analysis. Machines 3(2), 55–71 (2015)

    Article  Google Scholar 

  20. Szkilnyk, G., Hughes, K., Surgenor, B.: Vision based fault detection of automated assembly equipment. In: Proceedings of ASME/IEEE International Conference on Mechatronic and Embedded Systems and Applications, Parts A and B, vol. 3, pp. 691–697, Washington, DC, USA (2011)

    Google Scholar 

  21. Tourloukis, G., Stoyanov, S., Tilford, T., Bailey, C.: Data driven approach to quality assessment of 3D printed electronic products. In: Proceedings of 38th International Spring Seminar on Electronics Technology (ISSE), pp. 300–305, Eger, Hungary, May 2015

    Google Scholar 

  22. Yang, J., Hou, C., Zhou, Y., Zhang, Z., Guo, J.: Objective quality assessment method of stereo images. In: Proceedings of the 3DTV Conference: The True Vision - Capture. Transmission and Display of 3D Video, pp. 1–4, Potsdam, Germany (2009)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Signal Processing and Multimedia Engineering, Faculty of Electrical Engineering, West Pomeranian University of Technology, Szczecin, 26 Kwietnia 10, 71-126, Szczecin, Poland

    Jarosław Fastowicz & Krzysztof Okarma

Authors
  1. Jarosław Fastowicz
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Krzysztof Okarma
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jarosław Fastowicz .

Editor information

Editors and Affiliations

  1. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlin, Czech Republic

    Radek Silhavy

  2. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlin, Czech Republic

    Roman Senkerik

  3. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlin, Czech Republic

    Zuzana Kominkova Oplatkova

  4. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlin, Czech Republic

    Zdenka Prokopova

  5. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlin, Czech Republic

    Petr Silhavy

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Cite this paper

Fastowicz, J., Okarma, K. (2017). Entropy Based Surface Quality Assessment of 3D Prints. In: Silhavy, R., Senkerik, R., Kominkova Oplatkova, Z., Prokopova, Z., Silhavy, P. (eds) Artificial Intelligence Trends in Intelligent Systems. CSOC 2017. Advances in Intelligent Systems and Computing, vol 573. Springer, Cham. https://doi.org/10.1007/978-3-319-57261-1_40

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-57261-1_40

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-57260-4

  • Online ISBN: 978-3-319-57261-1

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics