Authors:
Fabien Salzenstein
1
and
Abdel-Ouahab Boudraa
2
Affiliations:
1
Université de Strasbourg, Laboratoire ICube, 23 Rue du Loess, Strasbourg, 67037 Cedex 2, France
;
2
Ecole Navale/Arts et Metiers Institute of Technology, IRENav, BCRM Brest, CC 600, Brest, France
Keyword(s):
AM-FM Model, Teager-Kaiser Energy Operator, Gauss-Markov Process, Rugosity, Surface Extraction.
Abstract:
This work deals with the problem of surface extraction using a combination of Teager-Kaiser operators and Gauss-Markov process in the context of coherence scanning (or white light scanning i.e, WLSI) interferometry. Our approach defines a Markov sequence along multiple surface profiles extracting their characteristics by the means of parameters describing the fringe signals along the optical axis, while most studies of the literature are restricted to local extraction of signals in one-dimensional mode. Thus the interest of the proposed strategy is to classify different surfaces present in a material, in particular the information relating to their roughness, by exploiting the statistical dependence between neighboring points where the noise is supposed to be white Gaussian noise. The effectiveness of our unsupervised method is illustrated on both synthetic and real images.