Skip to main content

Advertisement

SpringerLink
Log in

The use of combined illumination in segmentation of orthodontic bodies

  • Original Paper
  • Published:
Signal, Image and Video Processing Aims and scope Submit manuscript

Abstract

This paper presents new methods of orthodontic body segmentation using digital records of their plaster cast models under different types of illumination. Selected light conditions are used for the data acquisition to provide more clearly defined contours of the image components. The preliminary stage of the data processing uses the circular Hough transform, digital de-noising, and a separation of the orthodontic objects from their backgrounds employing Otsu’s thresholding method. The region-growing method using multiple seed points in a convex hull is then applied. The proposed general method identifies the common boundary of two neighboring and overlapping orthodontic objects with results enabling the efficient segmentation of digital data and their analysis through the computer network.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  1. Adams, R., Bischof, L.: Seeded region growing. Int. J. Pattern Recogn. Lett. 16(6), 641–647 (1994)

    Google Scholar 

  2. Ballard, D.H.: Generalizing the Hough transform to detect arbitrary shapes. Pattern Recogn. 13(2), 111–122 (1981)

    Article  MATH  Google Scholar 

  3. Bankman, I.N.: Handbook of Medical Image Processing and Analysis, 2nd edn. Elsevier, Amsterdam (2009)

    Google Scholar 

  4. Bhalerao, A.H.: Multiresolution Image Segmentation. Ph.D. Thesis, The University of Warwick (1991)

  5. Burger, W., Burge, M.J.: Digital Image Processing. Springer, Berlin (2008)

    Book  Google Scholar 

  6. Chang, Y.B., Xia, J.J., Gateno, J., Xiong, Z., Zhou, X., Wong, S.T.C.: An automatic and robust algorithm of reestablishment of digital dental occlusion. IEEE Trans. Med. Imaging 29(9), 1652–1663 (2010)

    Article  Google Scholar 

  7. Chapuis, J., Schramm, A., Pappas, I., Hallermann, W., Schwenzer-Zimmerer, K., Langlotz, F., Caversaccio, M.: A new system for computer-aided preoperative planning and intraoperative navigation during corrective jaw surgery. IEEE Trans. Inf. Technol. Biomed. 11(3), 274–287 (2007)

    Article  Google Scholar 

  8. Chen, H., Gururajan, R.: Otsu’s threshold selection method applied in de-noising heart sound of the digital stethoscope record. Adv. Inf. Technol. Ind. Appl. 136, 239–244 (2012)

    Google Scholar 

  9. Coltuc, D., Becker, J.M.: Scan-directional architectures. Vector Parallel Process. VECPAR96 1215, 35–48 (1997)

    Article  Google Scholar 

  10. Dass, R., Priyanka, Devi, S.: Image segmentation techniques. Int. J. Electron. Commun. Technol. 3(1), 66–70 (2012)

  11. Dostálová, T., Racek, J., Tauferová, E., Seydlová, M., Smutný, V., Bartoňová, M.: Composite Veneers, Crowns, and Inlay Bridges after Orthodontic Therapy - A Three-Year Prospective Study. Methods Inf. Med. 45, 191–194 (2006)

  12. Fernandez, V.J., Navarrete, D.M., Arizmendi, C.V., Paxtian, Z.H., Rodriguez, J.R.: Digital circuit architecture for a median filter of grayscale images based on sorting network. NAUN Int. J. Circuits Syst. Signal Process. 5(12), 297–304 (2011)

    Google Scholar 

  13. Fripp, J., Crozier, S., Warfield, S.K., Ourselin, S.: Automatic segmentation of the bone and extraction of the bone-cartilage interface from magnetic resonance images of the knee. IOP J. Phys. Med. Biol. 52(6), 1617 (2007)

    Article  Google Scholar 

  14. Gonzales, R.C., Woods, R.E., Eddins, S.L.: Digital Image Processing Using MATLAB. Prentice Hall, Englewood Cliffs (2004)

    Google Scholar 

  15. González, V.H., Rodríguez, M.A.: Some geometrical results about the convex deficiency of a compact set. Int. J. Appl. Math. Sci. 2(15), 719–723 (2008)

    MATH  Google Scholar 

  16. Hafizah, W.M., Soh, J.Z.E., Supriyanto, E., Nooh, S.M.: Automatic classification of muscle condition based on ultrasound image morphological differences. Int. J. Biol. Biomed. Eng. 6(1), 87–96 (2012)

    Google Scholar 

  17. Harrell, W.E., Hatcher, D.C., Bolt, R.L.: In search of anatomic truth: 3-dimensional digital modeling and the future of orthodontics. Am. J. Orthod. Dentofac. Orthop. 122(3), 325–330 (2002)

    Article  Google Scholar 

  18. Hart, P.E.: How the Hough transform was invented. IEEE Signal Process. Mag 26(6), 18–22 (2009)

    Article  Google Scholar 

  19. Hoad, C.L., Martel, A.L.: Segmentation of MR images for computer-assisted surgery of the lumbar spine. IOP J. Phys. Med. Biol. 47(19), 3503 (2002)

    Article  Google Scholar 

  20. Hough P.V.C.: Methods and Means for Recognizing Complex Patterns. U.S. Patent 3 069 654, Dec. 18 (1962)

  21. Jain, D.N., Jain, N.: Coin recognition using circular Hough transform. Int. J. Electron. Commun. Comput. Technol. 2(3), 1 (2012)

    Google Scholar 

  22. Jain, L., Mahor, D.: Application of Hough transform for finding parametric curves. Int. J. Comput. Appl. Eng. Sci. 1(2), 100–103 (2011)

    Google Scholar 

  23. Keating, A.P., Knox, J., Bibb, R., Zhurov, A.I.: A comparison of plaster, digital and reconstructed study model accuracy. J. Orthod. 35(3), 191–201 (2008)

  24. Nagabhushana, S.: Computer Vision and Image Processing, 2nd edn. New Age International, San Diego (2005)

    Google Scholar 

  25. Nitasha, B., Sharma, S., Sharma, R.: Comparison between circular Hough transform and modified canny edge detection algorithm for circle detection. Int. J. Eng. Res. Technol. 1(3), 15 (2012)

    Google Scholar 

  26. Ogodescu, A.S., Sinescu, C., Ogodescu, E.A., Negrutiu, M., Bratu, E.: Digital tools in the interdisciplinary orthodontic treatment of adult patients. NAUN Int. J. Biol. Biomed. Eng. 4(3), 97–105 (2010)

    Google Scholar 

  27. Petrou, M., Petrou, C.: Image Processing: The Fundamentals, 2nd edn. Wiley, Chichester (2010)

    Book  Google Scholar 

  28. Praveena, S.M., IlaVennila, D.: Optimization fusion approach for image segmentation using K-means algorithm. Int. J. Comput. Appl. 2(7), 18–25 (2010)

    Google Scholar 

  29. Rizon, M., et al.: Object detection using circular Hough transform. Am. J. Appl. Sci. 12(2), 1606–1609 (2007)

    Google Scholar 

  30. Shaneh, M., Golibagh, M.A.: Image enhancement using \(\alpha \)-trimmed mean \(\epsilon \)-Filters. World Acad. Sci. Eng. Technol. 5, 1156–1159 (2011)

  31. Singh, G.D.: Digital diagnostics: three-dimensional modelling. Br. J. Oral Maxillofac. Surg. 46(1), 22–26 (2008)

    Article  Google Scholar 

  32. Smith, S.W.: The Scientist and Engineer’s Guide to Digital Signal Processing, 2nd edn. California Technical, San Diego (1999)

    Google Scholar 

  33. Srinivasan, G.N., Shobha, G.: Segmentation techniques for target recognition. Int. J. Comput. Commun. 1(3) (2007)

  34. Srinivasan, G.N., Shobha, G.: Segmentation techniques for ATDR. NAUN Int. J. Comput. 2(9), 165–171 (2008)

    Google Scholar 

  35. Tomaka, A., Tarnawski, M., Luchowski, L., Lisniewska-Machorowska, B.: Digital Dental Models and 3D Patient Photographs Registration for Orthodontic Documentation and Diagnostic Purposes. In: Kurzynski, M., Puchala, E., Wozniak, M., Zolnierek, A. (eds.) Computer Recognition Systems 2, Advances in Soft Computing, vol. 45, pp. 645–652. Springer, Berlin (2007)

  36. Wider, M., Myint, Y.M., Supriyanto, E.: Comparison of histogram thresholding methods for ultrasound appendix image extraction. NAUN Int. J. Comput. 5(11), 542–549 (2011)

    Google Scholar 

  37. Yamamoto, K., Hayashi, S., Nishikawa, H., Nakamura, S., Mikami, T.: Measurements of dental cast profile and three-dimensional tooth movement during orthodontic treatment. IEEE Trans. Biomed. Eng. 38(4), 360–365 (1991)

    Article  Google Scholar 

  38. Yang, F., Jiang, T.: Pixon based image segmentation with Markov random fields. Int. J. Image Process. 12(12), 1552–1559 (2003)

    Article  MathSciNet  Google Scholar 

  39. Yang, J., Li, X.: Boundary detection using mathematical morphology. Pattern Recogn. Lett. 16(12), 1277–1286 (1995)

    Article  Google Scholar 

  40. Zhang, L., Dong, W., Zhang, D., Shi, G.: Two-stage image denoising by principal component analysis with local pixel grouping. Pattern Recogn. 43, 1531–1549 (2010)

    Article  MATH  Google Scholar 

Download references

Acknowledgments

This research has been supported by the research grant of the Institute of Chemical Technology, Prague No. MSM 6046137306.

Author information

Authors and Affiliations

  1. Department of Computing and Control Engineering, Institute of Chemical Technology, Technická 5, 166 28 , Prague 6, Czech Republic

    Mohammadreza Yadollahi, Aleš Procházka & Oldřich Vyšata

  2. Department of Paediatric Stomatology, 2nd Medical Faculty, Charles University, V Úvalu 84, 150 06 , Prague 5, Czech Republic

    Magdaléna Kašparová

Authors
  1. Mohammadreza Yadollahi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Aleš Procházka
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Magdaléna Kašparová
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Oldřich Vyšata
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Aleš Procházka.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yadollahi, M., Procházka, A., Kašparová, M. et al. The use of combined illumination in segmentation of orthodontic bodies. SIViP 9, 243–250 (2015). https://doi.org/10.1007/s11760-014-0653-4

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11760-014-0653-4

Keywords

Search

Navigation