Information and Communication Technology Seminar, Vol. 1 No. 1, August 2005
ISSN 1858-1633 2005 ICTS 8
The result using the estimate primitive is shown in d, that using the flat structuring element whose shape is
the same as b is shown in e, and that using the 3 × 3-pixel square flat structuring element is shown in f.
The “MSE” attached to each resultant image is defined as the sum of pixelwise difference between
each image and the original uncorrupted image of c, which is not shown here, divided by the number of
pixels in the image.
Fig. 11. Experimental results 1.
The results d show high effectiveness of our method in noise removal and detail preservation. The
results using the square structuring element contain artifacts since the square shape appears directly in the
results, and the results using the binary primitives yield regions of unnaturally uniform pixel values. The
comparison of d and e indicates that the optimization of binary structuring elements is
insufficient and the grayscale optimization is necessary.
Fig. 12. Experimental results 2.
In these examples, the assumptions that the grains are derived from one primitive by homothetic
magnification and the primitive is expressed by one structuring element are not exactly satisfied. However,
the results indicate that our method is applicable to these cases practically.
5. CONCLUSIONS
This invited talk has explained the fundamental concept of mathematical morphology, the filter
theorem and the relationship to image processing filters, and the concept of size distribution and its
application to texture analysis, which is one of the author’s research topics. The importance of
mathematical morphology is that it gives a “mathematical” framework based on set operations to
operations on shapes and sizes of image objects. Mathematical morphology has its origin in the
research of minerals; If the researchers of
mathematical morphology had concentrated to practical problems only and had not made efforts of
mathematical formalization, mathematical morphology could not have been extended to general
image processing or spatial statistics. It suggests that researches on any topic considering general
frameworks is always important.
Acknowledgements
The author would like to thank Dr. Daniel Siahaan, the Organizing Committee Chairman, and all the
Committee members, for this opportunity of the invited talk in ICTS2005.
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Mathematical Morphology and Its Application – Akira Asano
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Information and Communication Technology Seminar, Vol. 1 No. 1, August 2005
ISSN 1858-1633 2005 ICTS 10
MOLECULAR DYNAMICS SIMULATION ON A METALLIC GLASS-SYSTEM: NON-ERGODICITY PARAMETER
Achmad Benny Mutiara
Dept. of Informatics Engineering, Faculty of Industrial Technology, Gunadarma University Jl.Margonda Raya No.100, Depok 16424, West-Java Indonesia
E-mail: amutiarastaff.gunadarma.ac.id
ABSTRACT
At the present paper we have computed non- ergodicity paramater from Molecular Dynamics MD
Simulation data after the mode-coupling theory MCT for a glass transition. MCT of dense liquids
marks the dynamic glass-transition through a critical temperature Tc that is reflected in the temperature-
dependence of various physical quantities.
Here, molecular dynamics simulations data of a model adapted to Ni0.2Zr0.8 are analyzed to deduce
Tc from the temperature-dependence of corresponding quantities and to check the consistency of the
statements. Analyzed is the diffusion coefficients. The resulting values agree well with the critical
temperature of the non-vanisihing non-ergodicity parameter determined from the structure factors in the
asymptoticsolution of the mode-coupling theory with memorykernels in “One-Loop” approximation.
Keywords: Glass Transition, Molecular Dynamics Simulation, MCT
1. INTRODUCTION
