The present disclosure relates to surface profilometry, and more particularly, the present disclosure relates to interferometric surface profilometry.
White-light scanning interferometry is a non-contact optical method that is widely used for measuring three-dimensional surface profiles of materials with microns or sub-microns resolution. Many algorithms and methods have been proposed for determining the peak position of an interferogram and improving the accuracy of the detection. Most of these algorithms, such as methods disclosed in U.S. Pat. Nos. 7,119,907, 5,398,113, 5,953,124, and 5,133,601, require that clear and high contrast of an interferogram be present.
Unfortunately, such methods often fail when applied to diffusely scattering surfaces, such as paper surfaces. Paper is made of various types of pulp fibers, which are separated to individual fibers from wood or other fiber resources through chemical or mechanical processes or a combination of both. The fiber wall of native plant fibers consists of a variety of materials. Cellulose is the major structural component of the cell wall of wood fibers, which have a high tendency to form intra- and intermolecular hydrogen bonds and thus aggregate together into microfibrils, a crystalline, filamentous material. The other compositions of wood fiber include lignin, an extensively branched, three-dimensional, amorphous polymer, and hemicelluloses, which are partially paracrystalline polymers of a variety of molecular sizes. Those components are organized layer by layer, thus the fiber wall is typically a non-continuous, layered structure that contains many interfaces. These internal interfaces behave as scattering centers. Therefore, diffuse reflection is the major type of light reflection from fiber surfaces, which implies that all the light that was sent out is returned in all directions rather than at just one angle as in the case of specular reflection.
The lack of visibility in the white light interferogram for such diffuse surfaces renders simple processing techniques ineffective in determining the peak position in the interferogram. In order to overcome this problem, complex algorithms have been developed for processing the interferogram in order to infer the surface location. Unfortunately, the complexity of these algorithms place high demands on the processing power of the computing system employed, often rendering such solutions expensive and overly cumbersome for many applications.