Many surface properties are related to their topography. The characteristics of an engineering surface can be recorded as a roughness profile characterized by calculation of roughness parameters. The supposed relevant parameters are used to characterize the surface and to tailor similar surfaces with the same characteristics. The aim of this paper is to propose an alternative method based on information theory to avoid roughness parameters calculation in quantifying the similarity of two roughness profiles. The relevance of this method is emphasized using experimental profiles.
BigerelleM.AnselmeK.NoëlB.RudermanI.HardouinP.IostA.Improvement in the morphology of Ti-based surfaces: A new process to increase in vitro human osteoblast responseBiomater., 2002, 23, 1563–1577.
2.
LangeR.LüthenF.BeckU.RychlyJ.BaumannA.NebeB.Cell-extracellular matrix interaction and physico-chemical characteristics of titanium surfaces depend on the roughness of the materialBiomolecular Engng, 2002, 19, 255–261.
3.
SvahnF.Kassman-RudolphiA.WallénE.The influence of surface roughness on friction and wear of machine element coatingsWear, 2003, 254, 1092–1098.
4.
SalantR. F.ShenD.Hydrodynamic effects of shaft surface roughness on rotary lip seal behaviourSealing Technol., 2003, 7, 5–9.
5.
NajjarD.BigerelleM.IostA.The computerbased bootstrap method as a tool to select a relevant surface roughness parameterWear, 2003, 254, 450–460.
6.
NajjarD.BigerelleM.MigaudH.IostA.About, the relevance of roughness parameters used for characterizing worn femoral headsTribol. Int., 2006, 39, 1527–1537.
7.
NajjarD.BigerelleM.HennebelleF.IostA.Contribution of statistical methods to the study of worn paint coatings surface topographySurf. Coatings Technol., 2006, 200, 6088–6100.
8.
PeitgenH. O.JürgensH.SaupeD.Chaos and fractals: New frontiers of science, 1992 (Springer-Verlag, New York).
9.
EckmanJ.KamphorstS. O.RuelleD.CilibertoS.Liapunov exponents from time seriesPhys. Rev. A, 1986, 34, 4971–4979.
10.
TakensF.Detecting strange attractors in turbulence. In Proceedings of the Symposium on Dynamical systems and turbulence (Eds RandD. A.YoungL. S.), University of Warwick, 1980 (Springer, Berlin).
11.
BigerelleM.IostA.Structure coarsening, entropy and compressed space dimensionChaos, Solitons and Fractals, 2003, 18, 665–679.
12.
BigerelleM.IostA.Characterisation of the diffusion states by data compressionComput. Mater. Sci., 2002, 24, 133–138.
13.
ShannonC. E.A mathematical theory of communicationThe Bell System Tech. J., 1948, 27, 379–423.
14.
ChaitinG. J.Algorithmic information theory, 1987 (Cambridge University Press, Cambridge).
15.
BigerelleM.IostA.A new method to calculate the fractal dimension of an interface application to a Monte Carlo diffusion processComput. Mater. Sci., 2002, 24, 122–127.
AshleyJ.BarberR.FlicknerM.HafnerJ. L.LeeD.NiblackW.PetkovicD.Automatic and semiautomatic methods for image annotation and retrieval in QBIC. In Proceeding of the SPIE Storage and retrieval for image and video databases III, 1995, pp. 24–35.
18.
MaintzJ. B. A.ViergeverM. A.A survey of medical image registrationMed. Image Analysis, 1998, 2, 1–36.
19.
LefébureM.CohenL. D.Image registration, optical flow and local rigidityJ. Math Imaging Vision, 2001, 14, 131–147.
20.
CristianiN.Shaw-TaylorJ.Support vector machines and other kernel-based learning methods, 2000 (Cambridge University Press, Cambridge).
21.
HamzaA.HeY.KrimH.An information divergence measure for ISAR image registration. In IEEE Workshop on Statistical signal processing, Singapore, 2001, pp. 130–133.
22.
KieuT.ViolaP.Boosting image retrieval. In Proceedings of IEEE Conference on Computer vision and pattern recognition, 2000.
23.
BrillouinL.Science and information theory, 1956 (Academic Press, New York).
