Hostname: page-component-848d4c4894-wg55d Total loading time: 0 Render date: 2024-05-12T10:57:37.475Z Has data issue: false hasContentIssue false
  • English
  • Français

Measuring Surface Topography with Scanning Electron Microscopy. I. EZEImage: A Program to Obtain 3D Surface Data

Published online by Cambridge University Press:  09 December 2005

Ezequiel Ponz ,
Juan Luis Ladaga  and
Rita Dominga Bonetto
Ezequiel Ponz
Affiliation:
Centro de Investigación y Desarrollo en Ciencias Aplicadas Dr. Jorge J. Ronco (CINDECA) CONICET—UNLP, 47 No. 257-CC 59, 1900 La Plata, Argentina
Juan Luis Ladaga
Affiliation:
Facultad de Ingeniería de la Universidad Nacional de Buenos Aires, Departamento de Física—Laboratorio de Láser, Paseo Colón 850, Ciudad Autónoma de Buenos Aires, Argentina
Rita Dominga Bonetto
Affiliation:
Centro de Investigación y Desarrollo en Ciencias Aplicadas Dr. Jorge J. Ronco (CINDECA) CONICET—UNLP, 47 No. 257-CC 59, 1900 La Plata, Argentina
Get access

Abstract

Scanning electron microscopy (SEM) is widely used in the science of materials and different parameters were developed to characterize the surface roughness. In a previous work, we studied the surface topography with fractal dimension at low scale and two parameters at high scale by using the variogram, that is, variance vs. step log–log graph, of a SEM image. Those studies were carried out with the FERImage program, previously developed by us. To verify the previously accepted hypothesis by working with only an image, it is indispensable to have reliable three-dimensional (3D) surface data. In this work, a new program (EZEImage) to characterize 3D surface topography in SEM has been developed. It uses fast cross correlation and dynamic programming to obtain reliable dense height maps in a few seconds which can be displayed as an image where each gray level represents a height value. This image can be used for the FERImage program or any other software to obtain surface topography characteristics. EZEImage also generates anaglyph images as well as characterizes 3D surface topography by means of a parameter set to describe amplitude properties and three functional indices for characterizing bearing and fluid properties.

Keywords

dense height mapdynamic programmingfast cross correlationprogram3D surface topography in SEM
Type
MICROSCOPY TECHNIQUES
Information
Microscopy and Microanalysis , Volume 12 , Issue 2 , April 2006 , pp. 170 - 177
Copyright
© 2006 Microscopy Society of America

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Bianchi, F.D. & Bonetto, R.D. (2001). FERImage: An interactive program for fractal dimension, dper and dmin calculation. Scanning 23, 193–197.Google Scholar
Bonetto, R.D, Forlerer, E., & Ladaga, J.L. (2002). Texture characterization of digital images which have a periodicity or a quasi-periodicity. Measure Sci Technol 13, 1458–1466.Google Scholar
Bonetto, R.D. & Ladaga, J.L. (1998). The variogram method for characterization of SEM images. Scanning 20, 457–463.Google Scholar
Bonetto, R.D., Ladaga, J.L., & Ponz, E. (2005). Measuring surface topography by scanning electron microscopy. II. Analysis of three estimators of surface roughness in second dimension and third dimension. Microsc Microanal 12, 178–186 (this issue).Google Scholar
Buckley, M. & Yang, J. (1997). Regularised shortest-path extraction. Patt Recogn Lett 18 (7), 621–629.Google Scholar
Dong, W.P., Sullivan, P.J., & Stout, K.J. (1994). Comprehensive study of parameters for characterizing third-dimensional surface topography. III: Parameters for characterizing amplitude and some functional properties. Wear 178, 29–43.Google Scholar
Ladaga, J.L & Bonetto, R.B. (2002). Characterisation of texture in scanning electron microscope images. In Advances in Imaging and Electron Physics, Vol. 120 Hawkes, Peter W. (Ed.), pp. 136–189. San Diego, CA: Academic Press.
Lane, G.S. (1972). Dimensional measurements. In The Use of the Scanning Electron Microscope, Hearle, J.W.S., Sparrow, J.T. & Cross, P.M. (Eds.), pp. 219–238. New York: Pergamon Press.
Russ, J.C. (1994). Fractal Surfaces. New York, London: Plenum Press.
Sayles, R.S. & Thomas, T.R. (1978). Surface topography as a nonstationary random process. Nature 271, 431–434.Google Scholar
Stout, K.J., Sullivan, P.J., Dong, W.P., Mainsah, E., Luo, N., Mathia, T., & Zahouani, H. (1993). In The Development of Methods for the Characterization of Roughness in 3 Dimensions. Commission of the European Communities (BCR-3374/1/0/170/90/2). Report EUR 15178EN. London: Kogan Page.
Sun, C. (1998). Multi-resolution rectangular subregioning stereo matching using fast correlation and dynamic programming techniques. CSIRO Mathematical and Information Sciences, Australia, Technical Report 98/246.
Sun, C. (2002). Fast stereo matching using rectangular subregioning and 3D maximum-surface techniques. Inter J Comput Vision 47 (1/2/3), 99–117.Google Scholar
Thomas, T.R., Rosén, B.G., & Amini, N. (1999). Fractal characterization of the anisotropy of rough surfaces. Wear 232, 41–50.Google Scholar