Skip to main content
SpringerLink
Log in
Book cover

International Symposium on Visual Computing

ISVC 2015: Advances in Visual Computing pp 187–197Cite as

Segmentation of Partially Overlapping Nanoparticles Using Concave Points

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9474))

Abstract

This paper presents a novel method for the segmentation of partially overlapping nanoparticles with a convex shape in silhouette images. The proposed method involves two main steps: contour evidence extraction and contour estimation. Contour evidence extraction starts with contour segmentation where contour segments are recovered from a binarized image by detecting concave points. After this, contour segments which belong to the same object are grouped by utilizing properties of fitted ellipses. Finally, the contour estimation is implemented through a non-linear ellipse fitting problem in which partially observed objects are modeled in the form of ellipse-shape objects. The experiments on a dataset consisting of nanoparticles demonstrate that the proposed method outperforms two current state-of-art approaches in overlapping nanoparticles segmentation. The method relies only on edge information and can be applied to any segmentation problems where the objects are partially overlapping and have an approximately elliptical shape, such as cell segmentation.

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

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Park, C., Huang, J.Z., Ji, J.X., Ding, Y.: Segmentation, inference and classification of partially overlapping nanoparticles. IEEE Trans. Pattern Anal. Mach. Intell. 35, 669–681 (2013)

    Google Scholar 

  2. Zhang, W.H., Jiang, X., Liu, Y.M.: A method for recognizing overlapping elliptical bubbles in bubble image. Pattern Recogn. Lett. 33, 1543–1548 (2012)

    Article  Google Scholar 

  3. Kothari, S., Chaudry, Q., Wang, M.: Automated cell counting and cluster segmentation using concavity detection and ellipse fitting techniques. In: IEEE International Symposium on Biomedical Imaging, pp. 795–798 (2009)

    Google Scholar 

  4. Fisker, R., Carstensen, J., Hansen, M., Bødker, F., Mørup, S.: Estimation of nanoparticle size distributions by image analysis. J. Nanopart. Res. 2, 267–277 (2000)

    Article  Google Scholar 

  5. Shu, J., Fu, H., Qiu, G., Kaye, P., Ilyas, M.: Segmenting overlapping cell nuclei in digital histopathology images. In: 35th International Conference on Medicine and Biology Society (EMBC), pp. 5445–5448 (2013)

    Google Scholar 

  6. Cheng, J., Rajapakse, J.: Segmentation of clustered nuclei with shape markers and marking function. IEEE Trans. Biomed. Eng. 56, 741–748 (2009)

    Article  Google Scholar 

  7. Jung, C., Kim, C.: Segmenting clustered nuclei using h-minima transform-based marker extraction and contour parameterization. IEEE Trans. Biomed. Eng. 57, 2600–2604 (2010)

    Article  Google Scholar 

  8. Zhang, Q., Pless, R.: Segmenting multiple familiar objects under mutual occlusion. In: IEEE International Conference on Image Processing (ICIP), pp. 197–200 (2006)

    Google Scholar 

  9. Ali, S., Madabhushi, A.: An integrated region-, boundary-, shape-based active contour for multiple object overlap resolution in histological imagery. IEEE Trans. Med. Imaging 31, 1448–1460 (2012)

    Article  Google Scholar 

  10. Bai, X., Sun, C., Zhou, F.: Splitting touching cells based on concave points and ellipse fitting. Pattern Recogn. 42, 2434–2446 (2009)

    Article  MATH  Google Scholar 

  11. Tsai, D.M.: An improved generalized hough transform for the recognition of overlapping objects. Image Vis. Comput. 15, 877–888 (1997)

    Article  Google Scholar 

  12. Otsu, N.: A threshold selection method from gray-level histograms. Automatica 11, 23–27 (1975)

    Google Scholar 

  13. Canny, J.: A computational approach to edge detection. IEEE Trans. Pattern Anal. Mach. Intell. 8, 679–698 (1986)

    Article  Google Scholar 

  14. Wu, X., Kemeny, J.: A segmentation method for multi-connected particle delineation. Proc. IEEE Workshop Appl. Computer Vis. 1992, 240–247 (1992)

    Article  Google Scholar 

  15. Wang, W.: Binary image segmentation of aggregates based on polygonal approximation and classification of concavities. Pattern Recogn. 31, 1503–1524 (1998)

    Article  Google Scholar 

  16. He, X., Yung, N.: Curvature scale space corner detector with adaptive threshold and dynamic region of support. In: Proceedings of the 17th International Conference on Pattern Recognition, ICPR 2004, vol. 2, pp. 791–794 (2004)

    Google Scholar 

  17. Fitzgibbon, A., Pilu, M., Fisher, R.B.: Direct least square fitting of ellipses. IEEE Trans. Pattern Anal. Mach. Intell. 21, 476–480 (1999)

    Article  Google Scholar 

  18. Choi, S.S., Cha, S.H., Tappert, C.C.: A survey of binary similarity and distance measures. J. Systemics Cybern. Informatics 8, 43–48 (2010)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Machine Vision and Pattern Recognition Laboratory, School of Engineering Science, Lappeenranta University of Technology, Lappeenranta, Finland

    Sahar Zafari, Tuomas Eerola & Heikki Kälviäinen

  2. Mathematics Laboratory, School of Engineering Science, Lappeenranta University of Technology, Lappeenranta, Finland

    Jouni Sampo & Heikki Haario

  3. School of Information Technology, Monash University Malaysia, Selangor, Malaysia

    Heikki Kälviäinen

Authors
  1. Sahar Zafari
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Tuomas Eerola
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jouni Sampo
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Heikki Kälviäinen
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Heikki Haario
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sahar Zafari .

Editor information

Editors and Affiliations

  1. University of Nevada, Reno, Nevada, USA

    George Bebis

  2. NASA Ames Research Center, Moffett Field, California, USA

    Richard Boyle

  3. Lawrence Berkeley National Laboratory, Berkeley, California, USA

    Bahram Parvin

  4. Desert Research Institute, Reno, Nevada, USA

    Darko Koracin

  5. University of Houston, Houston, Texas, USA

    Ioannis Pavlidis

  6. IBM T.J. Watson Research Center, Yorktown Heights, New York, USA

    Rogerio Feris

  7. Purdue University, West Lafayette, Indiana, USA

    Tim McGraw

  8. Side Effects Software, Santa Monica, California, USA

    Mark Elendt

  9. The DiVE, Durham, North Carolina, USA

    Regis Kopper

  10. Texas A&M University, College Station, Texas, USA

    Eric Ragan

  11. Kent State University, Kent, Ohio, USA

    Zhao Ye

  12. Lawrence Berkeley National Laboratory, Berkeley, California, USA

    Gunther Weber

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Zafari, S., Eerola, T., Sampo, J., Kälviäinen, H., Haario, H. (2015). Segmentation of Partially Overlapping Nanoparticles Using Concave Points. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2015. Lecture Notes in Computer Science(), vol 9474. Springer, Cham. https://doi.org/10.1007/978-3-319-27857-5_17

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-27857-5_17

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27856-8

  • Online ISBN: 978-3-319-27857-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation