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Topological Homogeneity for Electron Microscopy Images

  • Helena Molina-AbrilEmail author
  • Fernando Diaz del Rio
  • Maria P. Guerrero-Lebrero
  • Pedro Real
  • Guillermo Barcena
  • Veronica Braza
  • Elisa Guerrero
  • David Gonzalez
  • Pedro L. Galindo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11382)

Abstract

In this paper, the concept of homogeneity is defined, from a topological perspective, in order to analyze how uniform is the material composition in 2D electron microscopy images. Topological multiresolution parameters are taken into account to obtain better results than classical techniques.

Keywords

Topology Homogeneity Electron microscopy Images 

References

  1. 1.
    Miller, R.L., Kahn, J.S.: Statistical Analysis in the Geological Sciences. Wiley, New York (1962)Google Scholar
  2. 2.
    Yaglom, A.M.: An Introduction to the Theory of Stationary Random Functions. Prentice Hall, Englewood Cliffs (1962)zbMATHGoogle Scholar
  3. 3.
    Materm, B.: Spatial variation. Comm. Swed. For. Res. Inst. 49, 144 (1960)Google Scholar
  4. 4.
    Ripley, B.: Spatial Statistics. Wiley, New York (1981)CrossRefGoogle Scholar
  5. 5.
    Cramer, H., Leadbetter, M.R.: Stationary and Related Stochastic Processes. Wiley, New York (1967)zbMATHGoogle Scholar
  6. 6.
    Ahsan, N., Miyashita, N., Islam, M., Yu, K., Walukiewicz, W., Okada, Y.: Effect of Sb on GaNAs intermediate band solar cells. IEEE J. Photovoltaics 3(2), 730–736 (2013)CrossRefGoogle Scholar
  7. 7.
    Braza, V., et al.: Sb and N incorporation interplay in GaAsSbN/GaAs Epilayers near lattice-matching condition for 1.0–1.16-eV photonic applications. Nanoscale Res. Lett. 12(1), 356 (2017)CrossRefGoogle Scholar
  8. 8.
    Cheah, W.K., Fan, W.J., Wicaksono, S., Yoon, S.F., Tan, K.H.: Low antimony-doped GaNxAs1-x on GaAs grown by solid-source molecular-beam epitaxy. J. Cryst. Growth 254(3–4), 305–309 (2003)CrossRefGoogle Scholar
  9. 9.
    Gonzalo, A., et al.: Strain-balanced type-II superlattices for efficient multi-junction solar cells. Sci. Rep. 7(1), 4012 (2017)CrossRefGoogle Scholar
  10. 10.
    Ho, I.H., Stringfellow, G.B.: Solubility of nitrogen in binary III–V systems. J. Cryst. Growth 178(1–2), 1–7 (1997)CrossRefGoogle Scholar
  11. 11.
    Reyes, D.F., et al.: Modelling of the Sb and N distribution in type II GaAsSb/GaAsN superlattices for solar cell applications. Appl. Surf. Sci. 442, 664–672 (2018)CrossRefGoogle Scholar
  12. 12.
    Ruiz-Marin, N., et al.: Nitrogen mapping from (HA) ADF analysis in quaternary dilute nitride superlattices 1 introduction. Appl. Surf. Sci. (in Review)Google Scholar
  13. 13.
    Stringfellow, G.B.: Thermodynamic considerations for epitaxial growth of III/V alloys. J. Cryst. Growth 468, 11–16 (2017)CrossRefGoogle Scholar
  14. 14.
    Wu, L.J., et al.: MBE growth and properties of GaAsSbN/GaAs single quantum wells. J. Cryst. Growth 279(3–4), 293–302 (2005)CrossRefGoogle Scholar
  15. 15.
    Wu, Z.H., et al.: Spontaneous formation of highly regular superlattice structure in InGaN epilayers grown by molecular beam epitaxy. Appl. Phys. Lett. 98(14), 4–7 (2011)CrossRefGoogle Scholar
  16. 16.
    Zhang, S.B., Wei, S.H.: Nitrogen solubility and induced defect complexes in epitaxial GaAs:N. Phys. Rev. Lett. 86(9), 1789–1792 (2001)CrossRefGoogle Scholar
  17. 17.
    Barros Neiva, M., Vacavant, A., Martinez Bruno, O.: Improving texture extraction and classification using smoothed morphological operators. Digit. Sig. Process. 83, 24–34 (2018)MathSciNetCrossRefGoogle Scholar
  18. 18.
    Mantz, H., Jacobs, K., Mecke, K.: Utilizing Minkowski functionals for image analysis: a marching square algorithm. J. Stat. Mech. Theory Exp. 12, 12015 (2008)CrossRefGoogle Scholar
  19. 19.
    Pikazi, A., Averbuch, A.: An efficient topological characterization of gray-levels textures, using a multiresolution representation. Graph. Models Image Process. 59(1), 1–17 (1997)CrossRefGoogle Scholar
  20. 20.
    Sonali Dash, S., Ranjan Jena, U.: Multi-resolution Laws’ Masks based texture classification. J. Appl. Res. Technol. 15, 571–582 (2018)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Helena Molina-Abril
    • 1
    Email author
  • Fernando Diaz del Rio
    • 1
  • Maria P. Guerrero-Lebrero
    • 2
  • Pedro Real
    • 1
  • Guillermo Barcena
    • 2
  • Veronica Braza
    • 3
  • Elisa Guerrero
    • 2
  • David Gonzalez
    • 3
  • Pedro L. Galindo
    • 2
  1. 1.H.T.S. Informatics’ EngineeringUniversity of SevilleSevilleSpain
  2. 2.Department of Computer Science and EngineeringUniversity of CadizPuerto RealSpain
  3. 3.University Research Institute on Electron Microscopy and Materials (IMEYMAT)University of CadizPuerto RealSpain

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